U.S. patent application number 16/275476 was filed with the patent office on 2019-08-22 for controlled agricultural systems and methods of managing agricultural systems.
The applicant listed for this patent is OSRAM GmbH. Invention is credited to Guido Angenendt, Timo Bongartz, Marek Burza, Norbert Haas, Norbert Magg, Sebastian Olschowski.
Application Number | 20190259108 16/275476 |
Document ID | / |
Family ID | 67482289 |
Filed Date | 2019-08-22 |
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United States Patent
Application |
20190259108 |
Kind Code |
A1 |
Bongartz; Timo ; et
al. |
August 22, 2019 |
Controlled Agricultural Systems and Methods of Managing
Agricultural Systems
Abstract
The present disclosure relates to different techniques of
controlling an agricultural system, as for example a controlled
agricultural system, an agricultural light fixture and a method for
agricultural management. Furthermore, the disclosure relates to an
agricultural system, which comprises a plurality of processing
lines for growing plants of a given plant type, wherein a first
processing line in the plurality of processing lines is configured
to move a first plurality of plants through the agricultural system
along a route; and apply a first growth condition to the first
plurality of plants to satisfy a first active agent parameter for
the first plurality of plants.
Inventors: |
Bongartz; Timo; (Munich,
DE) ; Olschowski; Sebastian; (Munich, DE) ;
Haas; Norbert; (Langenau, DE) ; Angenendt; Guido;
(Munich, DE) ; Burza; Marek; (Munich, DE) ;
Magg; Norbert; (Berlin, DE) |
|
Applicant: |
Name |
City |
State |
Country |
Type |
OSRAM GmbH |
Munich |
|
DE |
|
|
Family ID: |
67482289 |
Appl. No.: |
16/275476 |
Filed: |
February 14, 2019 |
Current U.S.
Class: |
1/1 |
Current CPC
Class: |
A01G 9/247 20130101;
G06Q 50/02 20130101; A01B 79/005 20130101; A01G 7/045 20130101;
A01C 21/005 20130101; A01G 31/02 20130101; A01G 9/0297
20180201 |
International
Class: |
G06Q 50/02 20060101
G06Q050/02; A01B 79/00 20060101 A01B079/00; A01C 21/00 20060101
A01C021/00 |
Foreign Application Data
Date |
Code |
Application Number |
Feb 20, 2018 |
DE |
10 2018 202 552.5 |
Mar 23, 2018 |
DE |
10 2018 204 524.0 |
Apr 6, 2018 |
DE |
10 2018 205 193.3 |
Apr 13, 2018 |
DE |
10 2018 205 654.4 |
May 18, 2018 |
DE |
10 2018 207 877.7 |
Jun 5, 2018 |
DE |
10 2018 208 843.8 |
Jul 16, 2018 |
DE |
10 2018 211 810.8 |
Jul 25, 2018 |
DE |
10 2018 212 402.7 |
Jul 31, 2018 |
DE |
10 2018 212 752.2 |
Aug 7, 2018 |
DE |
10 2018 213 214.3 |
Aug 13, 2018 |
DE |
10 2018 213 632.7 |
Aug 22, 2018 |
DE |
10 2018 214 193.2 |
Aug 29, 2018 |
DE |
10 2018 214 676.4 |
Aug 31, 2018 |
DE |
10 2018 214 888.0 |
Sep 28, 2018 |
DE |
10 2018 216 800.8 |
Oct 8, 2018 |
DE |
10 2018 217 145.9 |
Oct 15, 2018 |
DE |
10 2018 217 664.7 |
Oct 18, 2018 |
DE |
10 2018 217 830.5 |
Oct 18, 2018 |
DE |
10 2018 217 848.8 |
Oct 18, 2018 |
DE |
10 2018 217 855.0 |
Oct 22, 2018 |
DE |
10 2018 218 004.0 |
Oct 25, 2018 |
DE |
10 2018 218 295.7 |
Oct 25, 2018 |
DE |
10 2018 218 297.3 |
Oct 30, 2018 |
DE |
10 2018 218 578.6 |
Nov 5, 2018 |
DE |
10 2018 218 779.7 |
Nov 13, 2018 |
DE |
10 2018 219 367.3 |
Nov 20, 2018 |
DE |
10 2018 219 875.6 |
Nov 20, 2018 |
DE |
10 2018 219 883.7 |
Nov 28, 2018 |
DE |
10 2018 220 493.4 |
Dec 4, 2018 |
DE |
10 2018 220 902.2 |
Dec 12, 2018 |
DE |
10 2018 221 544.8 |
Dec 12, 2018 |
DE |
10 2018 221 552.9 |
Claims
1. An agricultural system, comprising: a plurality of processing
lines for growing plants of a given plant type, wherein a first
processing line in the plurality of processing lines is configured
to: move a first plurality of plants through the agricultural
system along a route; and apply a first growth condition to the
first plurality of plants to satisfy a first active agent parameter
for the first plurality of plants.
2. The system of claim 1, wherein each of the plurality of
processing lines is configured to apply a different growth
condition to their respective plants.
3. The system of claim 1, wherein the first active agent parameter
comprises an amount and/or concentration of an active agent.
4. The system of claim 3, wherein the active agent is a biological
or chemical component that provides a nutritional and/or
health-related benefit to the first plurality of plants.
5. The system of claim 1, wherein the first processing line
comprises a conveyor belt or an autonomous vehicle.
6. The system of claim 1, the system further comprising a memory
configured to store data about the first plurality of plants.
7. The system of claim 6, wherein the data comprises at least one
of a location in the agricultural system of the first plurality of
plants at a corresponding time, amount of time that the first
growth condition has been applied to the first plurality of plants,
the first active agent parameter, growth data at least one of the
first plurality of plants, the first growth condition, and an
identifier for each plant in the first plurality of plants.
8. The system of claim 6, the system further comprising at least
one sensor configured to collect at least a portion of the data
about at least one of the first plurality of plants as it is moved
along the route.
9. The system of claim 6, wherein at least a portion of the data is
stored in a blockchain.
10. The system of claim 1, wherein the route is segmented into a
plurality of growth zones, and in each growth zone the first
processing line is configured to apply a different growth condition
to the first plurality of plants.
11. The system of claim 10, wherein the plurality of growth zones
comprises at least one of a germination zone, a maturation zone,
and a flowering/fructification zone.
12. The system of claim 10, wherein a route for each of the
plurality of processing lines is segmented into the plurality of
growth zones.
13. The system of claim 10, wherein each of the different growth
conditions is based on growth data received from one or more
users.
14. The system of claim 1, wherein the first growth condition is
defined by a user that owns the plants.
15. The system of claim 1, wherein the first growth condition is
constructed by applying machine learning on growth data received
from one or more users.
16. The system of claim 1, wherein: the first growth condition
comprises a plurality of parameters relevant for growth of the
first plurality of plants; and applying the first growth condition
to the plurality of plants comprises adjusting one or more of the
parameters in the first processing line.
17. The system of claim 16, wherein the plurality of parameters
comprises at least one of an illumination level, one or more
illumination wavelengths, a temperature, a humidity, a
concentration of one or more gases in the air, and a fertilizer
amount or concentration.
18. A method of operating an agricultural system, comprising:
defining a plurality of growth zones for a plurality of plants of a
given plant type; and applying, in each of the plurality of growth
zones, a different growth condition to the plurality of plants,
wherein a first growth condition applied in a first growth zone of
the plurality of growth zones causes the plurality of plants to
satisfy a first active agent parameter.
19. The method of claim 18, wherein the first active agent
parameter comprises an amount and/or concentration of an active
agent.
20. The method of claim 19, wherein the active agent is a
biological or chemical component that provides a nutritional and/or
health-related benefit to the plurality of plants.
21. The method of claim 18, wherein the plurality of growth zones
comprises at least one of a germination zone, a maturation zone,
and a flowering/fructification zone.
22. The method of claim 18, further comprising: receiving the first
growth condition from a user that owns the plurality of plants.
23. The method of claim 18, further comprising: determining each of
the different growth conditions based on growth data one or more
users.
24. The method of claim 18, wherein the first growth condition is
constructed by applying machine learning on growth data received
from one or more users.
25. The method of claim 18, further comprising: storing data about
the plurality of plants.
26. The method of claim 25, wherein the data comprises at least one
of a location in the agricultural system of the plurality of plants
at a corresponding time, amount of time that the first growth
condition has been applied to the plurality of plants, the first
active agent parameter, growth data at least one of the plurality
of plants, the first growth condition, and an identifier for each
plant in the plurality of plants.
27. The method of claim 25, further comprising: collecting, by one
or more sensors, at least a portion of the data about at least one
of the plurality of plants.
28. The method of claim 25, wherein at least a portion of the data
is stored in a blockchain.
29. The method of claim 18, further comprising: moving the
plurality of plants between the plurality of growth zones using a
processing line.
30. The method of claim 18, wherein: the first growth condition
comprises a plurality of parameters relevant for growth of the
first plurality of plants; and the first growth condition is
applied in the first growth zone by adjusting one or more of the
parameters in the first growth zone.
31. The method of claim 30, wherein the plurality of parameters
comprises at least one of an illumination level, one or more
illumination wavelengths, a temperature, a humidity, a
concentration of one or more gases in the air, and a fertilizer
amount or concentration.
Description
INTRODUCTION
[0001] The present disclosure relates to a Controlled Agricultural
System, an Agricultural Light Fixture for use in a Controlled
Agricultural System and a Method for Agricultural Management.
[0002] Agriculture has been a success story for thousands of years.
Technical improvements, from the very first ploughshare to today's
state of the art harvesting machines, from the early use of
minerals and manure by Egyptians, Romans, and Babylonians to
today's tailor-made fertilizers, from early plant breeding to
genetic engineering, farming culture allowed for a steady increase
of the harvest. In spite of these extensive changes, one underlying
principle remained the same, the plant growth was ever since and
still is today driven by the natural sunlight. This success story,
which began at the end of the ice age, was about [0003] bringing
the plants to the light.
[0004] The story of the present application is about [0005]
bringing the light to the plants. It is even more about designing
not only the light, but the whole environment of the farm around
the plants. As far as the plants have been adapted to the natural
environment by breeding and genetic engineering in the past, the
present approach is to customize and adapt the farm to the specific
needs of the plants. One important enabler for moving agriculture
indoors is the energy efficiency of state of the art light
sources.
[0006] While the energy consumption of artificial lighting has been
lowered continuously, in particular driven by LED technology,
traditional farming is facing more and more limits. There are not
only the disadvantages of monocultural farming, over-fertilized and
depleted soils, but there is also an excessive use of fuel by the
large harvesting machines on the giant fields. Furthermore, this
decentralized crop production implies long transport routes and
world-wide shipping, with a respective impact on the food quality
and the ecological footprint.
[0007] From this point of view, it is again climatic change that is
driving a transition. In traditional farming, irrigating
agricultural land requires enormous amounts of water, particularly
in view of increasing periods of drought. Apart from that, people
are moving to cities with an ever more growing distance from field
to fork. In this respect, going indoors and in particular vertical
farming allows for a production of high-quality food close to the
consumer.
[0008] With plants being organic goods having very specific needs,
a farm or agricultural system discussed here can have a quite
different design and setup in detail, for instance depending on the
type and size of the plants grown, but also on the location of the
farm (e.g. vertical farm in a city) or other local
requirements.
[0009] The embodiment of claim 1 relates to an agricultural system
or farm with processing lines for growing plants. Therein, a first
processing line is configured to move a first plurality of plants
through the agricultural system along a route and to apply a first
growth condition to the first plurality of plants to satisfy a
first active agent parameter for the first plurality of plants. An
active agent can for instance be a pharmaceutical ingredient, see
the element "Medical Certificates" in detail.
[0010] Embodiments relating to the functionality of the farm as a
whole are described in Chapter I "System Setup". The farm, in
particular a fully automated farm, can manage the entire growth
system, applying not only a customized illumination to the plants
(light recipes), but even customized environmental conditions
(growth recipes) and solutions for maintaining or restoring plant
health, see Chapter II "Plant Health/Growth" and Chapter III
"Light/Growth Recipe".
[0011] Thinking about the starting point again, bringing the light
to the plants, the embodiments of Chapter IV "Luminaire" give a
more detailed view of a possible light source and fixture setup in
the farm.
[0012] A highly automated farm or agricultural system allows not
only for intelligent solutions inside the farm, but also for an
enhanced linkage of the farm to the outside world.
[0013] From this point of view, the farm is one element in a supply
chain. Amongst others, electrical energy is one of the most
important ingoing goods, which is described in detail in Chapter V
"Smart Grid", particularly the interaction between a controlled
agricultural system and a smart grid power supply.
[0014] Further, an automated farm can also enable an alignment with
downstream entities of food industry, in particular food producers.
In simple words, exactly that crop (specific taste or nutrient
content or the like) required in a food fab for processing a
certain lot can be grown in the farm.
[0015] Finally, customers can address their requests for customized
plants to the farm, which can be preprocessed and fed into the
digital supply chain of the agricultural system. The customer can
monitor the growth of the customized plants by means of information
on the respective growth stages provided by the farm to the
customer. Such interaction between farm and customer is described
in more detail in Chapter VI "Customer Interaction".
[0016] System Setup
[0017] The elements of the disclosure discussed in this chapter
"System Setup" relate to the setup and functionality of the farm as
a whole.
[0018] A major risk for farmers and food producers is a crop damage
or even total failure, which might end up in a total economic loss.
Even though going indoors can reduce the risk of for instance a
storm damage, other hazards remain, as for example an infection of
the plants with fungi or diseases. One major, though not the only,
path of infection can be the interaction with an operating
personnel bringing for instance spores from the environment outside
into the farm. This can be one reason why a widely or even fully
automated farm is advantageous.
[0019] Therein, the automatization in farming is hardly comparable
to the production process optimization known from industrial goods.
Apart from various plant specific needs, these "organic goods"
change their morphology and size during production. To consider
this, the element "Resizable Growth Area" proposes a growth area
adjustable in size. The distance between the individual growth
locations can be adapted based on the size of the plants grown
there, allowing for a compact arrangement and efficient
illumination at the beginning of the growth cycle and sufficient
space as well as efficient illumination for the plants at the end
thereof. In another aspect of "Resizable Growth Area" (but also in
"Hydroponics" or "Horticulture Processing Line", see below), the
growth area can be moved through the farm, wherein at different
locations different illumination setups are provided, which are
perfectly adapted to the actual size of the growth area at the
respective location.
[0020] One way of moving plants through the farm is described in
"Hydroponics", showing an assembly-line perfectly adapted to the
specific needs of plants. In this case, the growth locations can be
trays floating on a waterway. Likewise, the transportation through
the farm, for instance along different illumination areas adapted
to the respective growth stage, can be combined with an inherent
water or also nutrient supply in the waterway. In case of an
infection or other abnormality, detected for instance by a sensor
device (e.g. camera), the respective growth tray can be unloaded
from the waterway to a specific treatment location, as discussed in
"Horticulture Processing Line" in detail.
[0021] The specific treatment location can be comparable to a
quarantine area, which can further reduce the interaction of an
operating personnel at the standard processing line and the risk of
a contamination. As an alternative to the waterway, the trays with
the seeds or plants can also be moved on rails or elevators along
the standard processing line (but also by transportation cars or
moving arms or robots in general).
[0022] Even though moving the plants through the farm may initially
cause a certain effort, this invest pays off when the different
locations or zones of the farm are highly customized regarding the
specific growth stage. A perfect illumination setup emits only
spectral portions required in the specific growth stage (spectral
customization), so, ideally, all photons will hit the plants
(geometrical customization). In the long run, this optimization of
the energy footprint pays off. A method or tool for planning a
highly automated farm is described in "Light Recipes and Workflow".
As mentioned already, the setup of a sensor device or array can be
crucial for the automatization, for instance to detect infected
plants and trigger their unloading or treatment. An optimal
arrangement or distribution of the sensors in a farm can be
achieved by the method described in "Measuring Patterns".
[0023] In general, the plant production, as described for instance
in "Hydroponics" or "Horticulture Processing Line" can use plant
health detection systems as for instance described in "Disease
& Pest Control", "Prophylaxis", "Discolored Spots Detection"
and/or light treatments as for instance described in "Light
Guides", "Temperature Control", "Fungi Growth Inhibition". The
speed of the production may even be adapted to allow for a proper
sensing or treatment of the plants. Regarding a proper function of
the light fixtures, in particular in the long run over their
lifetime, data obtained according to the method described in
"Failure Detection" is helpful. The approach described there can
also reduce human interaction and the risk of infection thus.
[0024] Ideally, the conditions in the farm or different zones
thereof are customized to the specific needs of the plants in the
respective growth stages. This customization can be supported or
achieved by various sensor measurements. Therein, feedback loops
can be implemented so that the plants but also the sensors
themselves are monitored. In case of an error or extreme deviation
from a predefined value or interval, the respective location or
zone of the farm, possibly also the farm as a whole, can switch
into a kind of preservation mode. There, the illumination,
temperature, humidity and other important factors can be set to a
point, which keeps the plants in a most comfortable condition
without losing quality until the error (defect sensor or actual
problem in the farm) is eliminated. As mentioned, avoiding a crop
failure, a reduction in crop quality or a reduced harvested biomass
are a primary objectives.
[0025] Plant Health/Growth
[0026] The elements of the disclosure discussed in this chapter
"Plant Health/Growth" addresses the health and growth of
plants.
[0027] While plants are growing, ideally in line with dedicated
growth recipes, it is advantageous to monitor their growth and
health status and even predict the yield. In case any problems are
detected, measures should be taken quickly.
[0028] Agricultural Facilities, particularly horticultural
facilities such as greenhouses are not completely shielded from the
external surroundings. Thus, pathogens or pests may occasionally be
introduced or released in a horticultural farm, for example via the
ventilation system, the watering and drainage removal system or
when introducing seeds and germ buds. Additionally, humans or
machines deployed from the outside into the facility, for example,
automated guided agricultural robots, may introduce pests into a
greenhouse. Therefore, it is important to detect stress or diseases
of plants at an early stage, especially in a closed environment
like a vertical farm, where diseases can spread easily. Then, these
critical conditions may be countered by way of appropriate measures
(e.g., pesticides) in order to contain the outbreak.
[0029] It would be advantageous if there were no outbreak of
diseases at all in the first place or if pests were not given the
opportunity at all in the first place to spread. The element
"Prophylaxis" of the disclosure describes a controlled agricultural
system that is able to detect conditions that may be critical to
the health of the plants and, optionally, suggests appropriate
countermeasures.
[0030] Diseases or stress can be detected, for example, by color
changes of the leaves or modifications of the fluorescence of the
chlorophyll system, measurement of leaf reflectivity and/or false
color imaging.
[0031] Particularly, diseases and stress, e.g. caused by
temperature, salinization, drought, can lead to changes in
morphological leaf-parameters. Such changes may comprise
inclination of the leaves, form of the leaves (leaves will roll-up
in case of stress, leaf wilting) or symmetry of the leaves (e.g. a
damaged leaf will lose its symmetry) or necrosis, caused by fungi
or viruses. The element "Stress Detection" of the disclosure
describes a stress detection based on leaf parameters.
[0032] Different kinds of diseases or stress can cause different
symptoms at a plant, for example on plant leaves, petals, stem or
roots. Some can lead to a reduced growth of the plant, others, like
the Tobacco mosaic virus, which can infect tobacco, pepper, tomato
and cucumber, mainly cause "mosaic"-like mottling and discoloration
on the leaves. Causes of discolorations, depending on plant type,
can for example be caused by lack of nutrients or lack of chemical
elements like Nitrogen (N), Phosphor (P), Potassium (K), Sulfur
(S), Manganese (Mn), over-supply of nutrients, too much light, too
rapid temperature changes, lack of air circulation, too dry air,
too much irrigation, bacterial and virus infestation causing for
example bacterial blight and bacterial wilt, soil contamination,
soil temperature and many others. In addition to discoloration
effects, plant leaves can develop holes.
[0033] Therefore, cameras may be used to observe plants and detect
color changes that could be associated with diseases, i.e. when the
discolored parts have changed from their naturally provided colors
(according to their actual growth stage) to a changed color
impression, in other words when they have become discolored.
Discolorations can affect only parts or small segments of a plant
body (stem, petals, and leaves) or greater areas.
[0034] However, some of these color changes, particularly in an
early stage of a disease, only affect small parts of the leaves, or
the contrast between the discolored part and the normal colored
part is small, thus making it easy to overlook the discolored
areas. The element "Discolored Spots Detection" of the disclosure
targets to intensify the contrast between discolored and normal
colored parts of a plant.
[0035] Furthermore, some color changes (discoloration) signal a
next stage of ripening, e.g. the change of color in fruits. For
instance, tomatoes discolor from green to red while ripening,
eventually triggering harvesting.
[0036] In any case, if plants are affected by diseases (by viruses,
bacteria or fungi) or pests (such as spider mites or aphids), a
quick reaction is desirable so that the disease and/or the pests
cannot spread any further. Therefore, it would be advantageous if
an outbreak of a plant disease could be detected in a very early
stage. The element "Disease & Pest Control" of the disclosure
proposes to calculate a probability whether the plants have been or
will be affected by pests or diseases based on measured plant
parameters.
[0037] Furthermore, it would be advantageous to have precise and
early yield and harvesting time prediction at one's disposal.
[0038] Since plant health and plant growth can be influenced by
several parameters like light intensity (photon flux), light
spectrum, nutrients or temperature it is important to control at
least the most relevant parameters. Especially when experimenting
with new settings of those parameters, a fast feedback about the
plant growth, i.e. the morphological parameters, is necessary.
Plant growth can mean the height of the plant, the size and number
and orientation of the leaves, the diameter of the plant, the plant
morphology, and the height of the Apikalmeristem etc.
[0039] However, even when the parameters to grow plants in an
agriculture system are set, a regular control whether the plants
are growing as expected is necessary, as undetected changes in the
parameters, diseases or pests can affect the plant growth. It would
also be beneficial to track plant growth data or growth indicators
continuously, by day and night, and correlate the data to other
external parameters like temperature, nutrients, photon flux,
applied spectra, etc.
[0040] The element "Yield Prediction" of the disclosure proposes a
yield prediction for flowering plants by detecting the number of
plants and considering the ripening probability.
[0041] Plants can be affected by several diseases, some of them
caused by fungi. Therefore, it would be advantageous if growth of
fungi could be inhibited automatically. The element "Fungi Growth
Inhibition" of the disclosure describes a controlled agricultural
system configured for applying a fungi prevention illumination.
[0042] Monitoring the health and growth stage of ideally each
individual plant cultivated in agricultural facilities like
greenhouses and vertical farms usually requires appropriate
sensors, in some embodiments/implementations covering the entire
cultivated area.
[0043] Therefore, it would be advantageous to be able to equip
agricultural facilities in a sufficient, yet economical manner. The
element "Sensor Retrofit" of the disclosure describes how to make
use of already existing equipment for conducting the sensor
measurements in the necessary extent.
[0044] Furthermore, it would be advantageous to have a flexible
sensor system for measuring the morphological or growth indicative
parameters, which does not contain mechanically moving parts,
because it is difficult to move across the plants, particularly in
a vertical farm with stacked shelves. The element "LiDAR Plant
Surveillance" of the disclosure describes using LiDAR for 3D plant
surveillance, commissioning the system.
[0045] For detecting plant diseases or pests, the sensing of
relevant parameters is essential. The controlled agricultural
system is configured to be able to analyze the measured parameters
and infer a disease or pest. Furthermore, the controlled
agricultural system may also be configured to be able to predict
the yield based on measured parameters. Some of the parameters that
can be measured are: [0046] Leaf Area Index (LAI) (lowering of LAI
can give a hint to loosing leaves by a disease) [0047] Chlorophyll
fluorescence (stress detection due to wormholes or
fungi/virus/bacterial infection) [0048] Shape of leaves (e.g.
wormhole) [0049] Coloration of leaves (e.g. spots, necrosis,
mildew, veins, rust, browning and yellowing) [0050] Leaf and
ambient temperature and humidity (ambient and within the crops);
humidity and temperature help to calculated the dew point. If the
temperature is below the dew point, there is a high risk of water
condensation on plants promoting growth of diseases [0051]
Substrate moisture (substrate includes, soil, rock wool, perlite
etc.) and temperature [0052] Dissolved oxygen in NFT (nutrient film
technique), Deep water systems etc. [0053] EC (Electric
Conductivity) and pH Value (salinity and acidity of substrate or
nutrient solution) [0054] Microclimate [0055] Plant parameters
like: Plant height, Leaf area, number of flowers and/or fruits
[0056] Leaf thickness (if possible with a 3D scanner) [0057] The
NDVI (Normal density vegetation index) determines the density of
green on a patch of land [0058] Chlorophyll strongly absorbs
visible light 400-700 nm [0059] Cell structure strongly reflects
near infrared (NIR) 700-1100 nm [0060] Healthy vegetation absorbs
visible light and reflects large portion of NIR [0061] Unhealthy
vegetation reflects more visible light and less NIR [0062] In case
of bad vegetation the reflected NRI or the NDVI is close to zero
[0063] In case of good vegetation the reflected NRI or the NDVI is
close to 0.8 [0064] The CRI (Carotenoid reflectance Index)
determines the concentration of carotenoids in plants [0065]
Weakened vegetation contains higher concentration of carotenoids,
the index is thus a measure of stressed vegetation [0066] Higher
CRI1 values mean greater carotenoid concentration relative to
chlorophyll [0067] CRI2 uses a modified calculation of CRI which
provides better results in areas with high carotenoid concentration
[0068] Value Index for CRI ranges from 0 to >15 [0069]
Chlorophyll index [0070] Anthocyanin index [0071] Water Index
[0072] Volatile compounds released by plants to signal stress
(pests, etc.)
[0073] Some of the sensors, which can be used in the controlled
agricultural system are: [0074] Optical sensors [0075] Combination
of camera and IR laser [0076] Stereo camera system [0077] Kinect
system and other depth sensing cameras (relatively simple and
cheap) [0078] RGB Camera (with removing the IR-filter, we also
could increase the spectrum which is seen by the camera) [0079]
High Resolution camera (for detecting small spots of
rust/bugs/aphids etc.) [0080] Multispectral camera [0081]
Camera-based motion detector [0082] Gas chromatography (detection
of volatile compounds) [0083] Environmental sensors (Capacitive
sensors. E.g.): [0084] Temperature [0085] Humidity [0086] Leaf
temperature [0087] VPD (Vapor pressure deficit) [0088] Substrate
moisture [0089] Substrate temperature [0090] EC and pH-Value [0091]
Velocity [0092] Sensor to track nutrients (macro and micro
elements)
[0093] The time interval between measurements depends on the kind
of sensor. Environmental factors should be tracked every minute.
Measurements with a camera systems for disease detection can be
done 3-5 times per day. For example, mildew can occur over
night.
[0094] Furthermore, the triggering of a measurement can be
dependent on signals/events/levels/thresholds from other sensors
(e.g. to cross-check/confirm detection by other means, or make the
detection more specific).
[0095] One manner to detect the growth stage of plants and to
detect infected plants is by using the BBCH codes (BBCH=Biologische
Bundesanstalt, Bundessortenamt und Chemische Industrie), which are
available for some major crops like tomatoes, leafy greens, etc.
The BBCH Codes describe the development stage with a number and
provide some general drawings how it looks like. This code provides
means to distinguish between different stages, discriminate the
optimum of respective stage, and gives guidance with regard to
disease detection and yield prediction.
[0096] Data can be collected and stored locally and/or in the
cloud, i.e. the global internet network. In some
embodiments/implementations, the data is transferred wireless (e.g.
radio, via light) to the computing device of the controlled
agricultural system und then processed, to be shown at the
dashboard in the typical units (e.g. temperature .degree. C., rel.
humidity %, absolute humidity g/m.sup.3, etc.), but also wired data
transfer can be an option.
[0097] For big data packages, e.g. images (still or even video) the
data processing in the edge, i.e. directly at the sensors, may be
preferred (Edge Computing). This way, only processed and usually
reduced data streams are transferred to the computing device of the
controlled agricultural system for storage and analysis.
[0098] In any case, the data may be transformed in values according
to the metric system or systems used in other countries (like the
imperial system). The data may be processed first to render a
space-resolved mapping. For example, if five sensors for
temperature measurements are distributed in an area of 1 ha, the
average value of the temperature may be compute as well as a kind
of a temperature map for the greenhouse. Such map data can be 2D or
also 3D as a point cloud. Especially if data for tracking plant
growth is collected by a moving robot, a variety of sensors,
including temperature sensors, can easily be added to the robot or
any other automated vehicle. Furthermore, derived parameters may be
calculated from measured values, for example the dew point, which
is derived from temperature and humidity.
[0099] Another way to process the data could be to estimate the
relative number of plants affected, like approx. 65% of your plants
are infected, e.g. by detecting a necrosis or the infection with a
fungi.
[0100] Most of the pre-processing may also be offloaded to the
cloud--this option can advantageously allow: [0101] to process the
data in bulk; [0102] lower the costs of a sensor unit (if
processing consumes processing power); [0103] potentially extend
the battery life (if pre-processing consumes battery power); [0104]
lower the costs of data transmission (if pre-processing leads to
generating additional information); [0105] keeping original,
unprocessed data (raw data) in the cloud may open up possibilities
for deriving other values later, which might be closed off by
pre-processing.
[0106] The data can be stored in the "original" or "raw" format or
in a processed format. For example, images can be stored (raw data)
or the analyzed information retrieved by analyzing the image, e.g.
that x % of the plants are affected by a certain disease (processed
data). Storing the original picture can be useful in case the
algorithm is improved and certain values need to be
re-calculated.
[0107] The data analysis may include calculating averages and
relative values (percentages) and a combination of different sensor
data (sensor fusion).
[0108] The data may also be manually and/or automatically
annotated, e.g. what crop species was grown, when and where a
disease/pest occurred. Then the controlled agricultural system may
be configured to apply machine learning/AI to learn automatically
the conditions for detection of the stressors or disease causing
conditions.
[0109] Reference data for the comparison with measured data and
subsequent analysis of the result can be generally available
reference data (i.e. some generic data and not data generated at
the particular agricultural system), particularly as an initial
step. In the next steps, the controlled agricultural system may be
configured to start using historical on-site data, for example,
data from one of the previous years.
[0110] The collection of reference data may not only include
specific values, but also a range of values (min., max.) including
a plausibility-check of the limit values. For example, a completely
unrealistic value of 5 kg for the weight of a tomato would be
excluded. Update of new data, which leads to a more precise
calculation process, can be provided online via cloud. It can also
be possible, that growers with the same crop actively decide to
upload their data to the platform connected to the controlled
agriculture system. The data may be used anonymously.
[0111] The measured data may be analyzed periodically, in real-time
and/or dependent on what the customer is willing to pay.
[0112] The controlled agriculture system may be configured to
inform the grower if a certain threshold (min. or max. value) of a
critical parameter is reached or if, for example, a certain
percentage of leaves is affected. The trigger for detecting or
verifying a disease may also be a certain combination of
environmental factors like EC or pH values. The trigger may also be
provided by a trained AI system. The system might continue to learn
while used, e.g. by supervised learning. In this case it may be
beneficial to include a feedback-loop between the system and the
operator to train and improve the system. To this purpose, the
operator may feed back to the system whether he/she confirms or
dismisses a potential issue flagged by the system.
[0113] Data storage, retrieval and processing may be managed
on-site or by means of cloud-computing services, which enable
on-demand access to a shared pool of computing resources (servers,
applications, data, storage, processing) that can be rapidly
provisioned and released via the Internet, e.g. Platform as a
Service (PaaS), Software as a Service (SaaS).
[0114] Light/Growth Recipes
[0115] A vision behind the elements of the disclosure discussed in
this chapter is a farm that manages the entire growth system. It
can not only apply light recipes, namely a specific illumination
based on the growth status, but also adjust further growth
conditions. Apart from the illumination, respective control
programs of the farm can for instance apply the required
irrigation, fertilization, fertigation and/or plant movement.
[0116] Thinking about bringing the light to the plants, a light
recipe can even go a step further. Beyond mimicking the sunlight,
it can be about tailoring the illumination to a specific type of
plant, in terms of the intensity and spectral composition.
Different illumination setups can stimulate or trigger a difference
in growth or the creation of certain ingredients (for instance
primary and secondary metabolites). Even the taste or vitamin
content of the crop can be influenced via the light recipe. In
"Flexible growth", the light or growth recipe is for instance used
for delaying or speeding up the harvesting time to meet new target
values arising during the production of the plants, namely while
plants are already growing. Such target values can for instance be
the growth rate, but also vitamin content, biomass or color of the
plants.
[0117] A light recipe can also be about an intensity or spectral
modulation over time. The illumination can be adapted to different
growth stages of the plants, for instance from germination over
growth to fructification. As discussed for instance in "Resizable
growth area", "Hydroponics" or "Horticulture processing line",
different illumination setups can be arranged at different
locations or zones of the farm, allowing for light fixtures or
arrangements to be customized regarding the specific recipe.
However, for sure, different lighting conditions can also be
applied with an adjustable light fixture having tuneable light
sources with different spectral properties. Independently of the
setup in detail, the failure handling of the "Automatic failure
compensation" may be of interest, since light recipes rely on
working light fixtures. With this intrinsic compensation of a
failing light source (e.g. LED), the functionality of the light
recipe can be assured.
[0118] In an automated farm, the light recipe can be part of a
growth recipe comprising or defining further parameters, as for
instance the temperature, humidity, CO.sub.2-level, airspeed EC,
pH-value or the like. In "Temperature Dependent Illumination", the
interaction of these parameters is discussed, in particular the
interaction between temperature and illumination. In a vertical
farm for instance, a different illumination can be applied at
different height levels to counteract for example a spread in time
to flower, which could result from a higher temperature at the
upper shelves due to convection.
[0119] In general, one can strive for a perfectly adapted
illumination, in particular regarding the spectral composition of
the light. According to the "Adaptive Spectrum", the difference or
gap between the ambient light in the farm and an ideal illumination
is measured, and the illumination is adapted to "fill up" this gap.
The ambient light can for instance be residual daylight, allowing
for an overall energy efficient and still customized
illumination.
[0120] A growth or in particular light recipe can be a fixed data
set comprising spectral properties and also information on time
intervals and the like. Even though the spectral data is available
in this generic form, there can be a missing link to the actual
control parameters for operating or controlling a specific light
fixture or luminaire. "Spectrum Calculation" is about translating a
generic recipe into parameters for a light fixture actually used in
the farm. Such a translation may also be relevant for any change of
the light recipe.
[0121] A change of the recipe may not only depend on a customer
request ("Flexible Growth"), the ambient illumination ("Adaptive
spectrum") or a temperature gradient ("Temperature Dependent
Illumination"), but might be also used to induce a "Plant
Movement". According to "Plant Movement", the light intensity is
moved above the plants to induce them to follow, comparable to
sunflowers following the sun. The movement can strengthen the
plants.
[0122] For transmitting amended control parameters to a light
fixture or its control unit, a wire based or wireless communication
is possible. An interesting option is described in "Light Recipes
and VLC", namely a data transfer via a modulation of the light
itself. By modulating the emission, for instance, a change in
control parameters can be communicated from one light fixture to
the other across the farm or respective zone of the farm. On the
other hand, "Light Recipes and VLC" considers an adaption of the
light recipes to assure that, despite of a reduced intensity
resulting from the modulation, for instance the required DLI Level
is met.
[0123] As described in "Extended Recipes", apart from a spectral
adjustment (intensity of certain colors), light recipes can also be
implemented by other means to save energy, for instance by optics.
Beyond illumination, plant growth can also be modified using a
"Temperature control" or by adjusting other parameters, like for
instance CO.sub.2, humidity or the like. Comparable to the light
recipes, also the other parameters can be adapted to a specific
growth stage of the plants and change over time.
[0124] Luminaire
[0125] The elements of the disclosure discussed in this chapter
"Luminaire" address an agricultural light fixture, particularly
horticultural light fixture.
[0126] An agricultural light fixture or agricultural luminaire
provides illumination for an agricultural arrangement, e.g. a
cultivated area or any other target area or target space, in a
controlled agricultural system. The illumination may comprise light
in the visible range (VIS), the ultraviolet range (UV) and infrared
range (IR) of the electromagnetic spectrum. Luminaires can contain
a variety of light sources, sensors, actuators and heat dissipation
elements, and may be connected to the controlled agricultural
system. Furthermore, luminaires can have adaptable features like
form change and change of optics.
[0127] In an outdoor farm or in a greenhouse, the plants are
typically illuminated by the sunlight, wherein artificial lighting
can be a supplementation in terms of the spectral composition or
amount of light. The latter can be described by the daily light
integral (DLI) describing the number of photosynthetically active
photons delivered to a specific area over a 24 hour period. On the
other hand, indoor farming is also possible without any natural
light at all but artificial lighting only.
[0128] Traditional luminaires or lighting fixtures are arranged
above a target region, which is to be illuminated. Thus, plants
grown in or on such target regions commonly will only be
illuminated from the top, mainly with vertical light incidence.
Consequently, those parts of the plants, which are closest to the
light source will receive most of the light. Leaves or bigger plant
parts will block light from reaching the lower parts of the plants
and therefore sufficient illumination or delivery of light to lower
plant parts cannot be guaranteed. In particular, for ranking
plants, such as tomatoes, or for fast growing plants, like
Cannabis, the upper plant parts will block a significant portion of
the light. A homogeneous light distribution over the entire plant
therefore might not be achieved.
[0129] Further, traditional luminaires often have an illumination
profile, which decreases toward the edge and therefore might not
illuminate an area homogeneously. In addition, in particular modern
luminaires based on semiconductors produce significant heat, which
may cause a local heating of the illuminated products in such
vertical farms.
[0130] LED light-sources used in existing systems may cause
irregular illumination, if the distances to the plants are too
small, while higher distances may result in light intensities lower
as desired, in particular for specific purposes, such as pest or
disease control (see also element "Disease & Pest Control" in
group "Plant Health & Growth"), or influencing plant growth
morphology or the enrichment of enzymes in an illuminated plant, or
such.
[0131] Therefore, it would be advantageous if the light irradiated
by the light sources of a light fixture could be directed or guided
or distributed such that the illumination of plants would be
improved with respect to the disadvantages described above. The
element "Light Guides" of the disclosure describes a light module
comprising at least one light guide, which enables improved
illumination of plants (see below).
[0132] A failing light source, in particular a failing light
fixture or light fixture module, can lead to an insufficient
illumination of the plants grown in a controlled agricultural
system. This does not only relate to the intensity, for instance a
reduced DLI (Daily Light Integral), but also to the spectral
composition of the light.
[0133] Typically, light sources having different spectral
properties are provided for achieving light with a defined spectrum
optimized for the type of plants grown in the farm, even in terms
of their growth stage. Vice versa, one or more failing light
sources with a reduced emission or even no emission at all (total
failure) can have a negative impact on the health and growth
behaviour of the plants.
[0134] Thus, it would be advantageous to be able to detect a
failing light source quickly so that a repair or replacement
action, or any other countermeasure, can be taken promptly. The
element "Failure Detection" of the disclosure describes how to
detect and locate a failing light source (see below).
[0135] Furthermore, it would be advantageous to be able to
compensated, at least temporarily, a failing light source until the
failed light source, or the affected module, or the light fixture
as a whole, is replaced or repaired. The element "Failure
Compensation" of the disclosure describes how to compensate a
failing light source, at least temporarily (see below).
[0136] Agricultural light fixtures used in greenhouses or indoor
farms are increasingly LED-based as they can provide a more
specific spectrum (light recipe) and use less energy. However, the
LEDs nevertheless produce a significant amount of heat, which is
usually taken away from the agricultural light fixture using heat
spreaders, heat pipes or other solutions to cool the LEDs and
prevent an overheating of the LEDs and the surrounding electronics.
The thus removed heat-energy is usually lost for further usage.
[0137] It has been observed that providing heat to plants from
above or sideways can support the growth of the plants and their
fruits. Furthermore, if the surrounding temperature moves below the
dew point at the plants, there is an increased risk of fungus
infection due to higher condensation on the leaves.
[0138] Therefore, it would be advantageous to be able to use the
waste heat from the LEDs for the plants. The element "Heat
Reflector" of the disclosure describes how to direct the waste heat
to the plants in a controlled manner (see below).
[0139] Smart Grid
[0140] Agricultural Facilities, for example, horticultural
facilities in Controlled Environment Agriculture (CEA), such as
greenhouses and vertical farms, need significant amounts of
electrical energy. In fact, vertical farms and similar devices
(agricultural plants) are major electricity consumers for their
illumination and further components (water supply, etc.).
[0141] In a conventional grid power supply, the supply of
electricity is determined by the consumption by consumers. In a
smart grid power supply, the consumption by the consumers can be
determined by the supply of the grid power supply since the
consumer obtains information about the availability of the
electricity (as a rule, by way of the price, which drops when the
supply is high) in this case. In particular, there may be a price
difference between the energy supply during the day and at night,
when less energy is consumed (the day and night rhythm may be
inverted).
[0142] Therefore, it would be advantageous if an agricultural
facility could benefit from low energy price without loss of yield.
The element "Smart Grid" of the disclosure describes a controlled
agricultural system that is able to make an optimal use of
cost-effective electricity.
[0143] Customer Interaction
[0144] The elements of the disclosure discussed in this chapter
"Customer Interaction" address communications and interactions
between the controlled agricultural system and customers. For
instance, the controlled agricultural system may receive inputs
from the customer and provide information to the customer.
[0145] These days, customers are only able to order the amount of a
plant (biomass). The quality of the plant to be ordered is only
determined by quality classes, i.e. size, color, certification
marks such as eco- or organic product and fair trade, from which
the customer can make a selection. However, it would be
advantageous if a more specific definition and/or influence on the
quality could be possible when ordering plants, fruit or
vegetables. The element "Customer Requirements" of the disclosure
describes a controlled agricultural system and a method for
customized plant growth.
[0146] However, growth recipes, that is, control parameters
regarding e.g. illumination, temperature, humidity, nutrients,
etc., do not only depend on the specific plant but also on the
environment in which the plant is growing. Furthermore, growth
recipes for specific customer demands might not be available and
need to be extrapolated from existing growth recipes. Therefore, it
would be advantageous if a kind of success score for meeting the
customer's request were available. The element "Success Score" of
the disclosure describes a controlled agricultural system, which is
able to provide a probability (success score) to reach the desired
goal, namely a customized plant growth.
[0147] Growers who grow plants in controlled environments want to
constantly monitor, track and optimize plant growth to decrease
risk of mold and pest infestation, predict yield and optimize
conditions to increase plant quality and yield. These controlled
environments can include greenhouses, vertical farms, indoor farms,
smart gardening kitchen appliances or instore farms. Climate
control systems and ambient sensors collect relevant data like PAR,
humidity, CO2, temperature, pH, EC, etc.
[0148] Furthermore, growers may want to share pictures and the
overall plant growth results on social media platforms like
Instagram. Therefore, growers may want to take pictures with their
smartphones or any similar mobile device (e.g. tablet PC) or even a
camera.
[0149] The element "Picture Taking & Evaluation" of the
disclosure proposes a method for agricultural management, which
targets these needs.
[0150] Customers may also prefer produce from eco-farming, i.e.
produce that have been grown and delivered with low carbon-food
print or without the use of pesticides. The element "Eco
Certificates" of the disclosure proposes a method for agricultural
management, which considers and tracks ecological aspects with the
help of a life-cycle assessment. Furthermore, by means of
certificates, customers can verify that the products have been
produced eco-friendly.
[0151] It is well known that medical plants, which also include
cannabis products, play an important role for the health of humans
and animals. By way of example, these can contribute to the
provision of relief in the case of atopic dermatitis, erythema,
pruritus, nervous restlessness, allergies, psoriasis (skin
disorder), asthma, intolerance to light, rheumatic ailments, muscle
weakness, period pain, epilepsy, tumor and many more.
[0152] Medical products can be purchased or ordered in a pharmacy,
in relevant specialist stores or already, in part, by mail order as
well. However, a customer has no direct influence on the quality of
the wares in this case, for example on the light recipe for plant
illumination or further growth conditions, and consequently they
are also unable to purchase a product that has been adapted or
optimized to the personal situation or requirements.
[0153] Thus, it would be advantageous if customers could order a
medical plant with knowledge of the illumination scenarios the
latter experienced during its seedling, growth and maturing stage
and with knowledge of what growth conditions were applied.
[0154] The element "Medical Certificates" of the disclosure
proposes a method for agricultural management, which align to these
customer demands by providing products grown under conditions
tailored for a specific use, particularly medical use. The intended
use and/or content of active agents of the plants may also be
certified.
SUMMARY OF THE DISCLOSURE
[0155] System Setup
[0156] "Resizable Growth Area"
[0157] Below, various aspects and details of the "Resizable Growth
Area" are discussed.
[0158] 1.sup.st aspect of the "Resizable Growth Area": A growth
area having a plurality of growth locations, each growth location
being provided for growing a plant respectively, wherein a distance
between the growth locations is adjustable.
[0159] Across the growth area, a plurality of growth locations are
provided, for instance carriers like trays or shells or the like.
With the growth area adjustable in size, the distance between the
growth locations can be adjusted depending on the plant's growth
(morphology) or other needs.
[0160] The growth area can have a rather small size at the
beginning of a growth cycle, for instance after seeding or bedding
the plants. Having the plants close to each other can be
advantageous in regard to the artificial lighting, as only a
comparably small area has to be illuminated. When the plants grow,
the distance between the growth locations can be increased, and the
illuminated area can be adapted accordingly. In general, this can
be an adaption in distance, size, inclination, spectrum, heating,
etc. In particular, the inclination of the light fixtures and/or
light sources and/or the optics could be beneficial. In addition,
the spectrum and intensity could be changed.
[0161] Due to the resizable growth area, each plant has sufficient
space to allow a proper growth. On the other hand, the plants can
be kept close to each other as far as possible, enabling an energy
efficient artificial lighting. Assuring small or even no
intermediate spaces between the plants prevents a waste of light
there.
[0162] In contrast, in case of a growth area having a fixed size,
the percentage of the area covered by the plants/leaves with
respect to the uncovered area would be rather small at the
beginning of the growth cycle. The photon energy would be wasted to
a large extent, because many photons would just reach the ground
without being absorbed by the plants/leaves. On the other hand,
placing the plants too close to each other in a predefined distance
would negatively impact the growth later on.
[0163] 2.sup.nd aspect of the "Resizable Growth Area": The growth
area according to the 1.sup.st aspect of the "Resizable Growth
Area", comprising a foil that forms the growth locations, the foil
being stretchable to adjust the distance between the growth
locations.
[0164] The foil can for instance be a plastic or synthetic film or
foil. By stretching the foil, the size of the growth area and the
distance between the growth locations can be increased. The growth
locations can for instance be plant pots or trays attached to the
foil, for instance by gluing.
[0165] 3.sup.rd aspect of the "Resizable Growth Area": The growth
area according to the 1.sup.st or 2.sup.nd aspect of the "Resizable
Growth Area", comprising a plurality of bars that forms the growth
locations, interconnected with each other in joints in an
articulated manner allowing for folding, in particular lateral
folding.
[0166] By folding the bars together, the distance between the
growth locations can be decreased, unfolding the bars increases the
size of the growth area and thus the distance between the growth
locations. "Lateral" refers to a direction parallel to the growth
area. In a typical application, the growth area can lie
horizontally so that the lateral directions are horizontal
directions. However, in general, the growth area can also be
oriented in the vertical direction, for instance in case of a
vertical farm.
[0167] In other words, the growth locations are in some
embodiments/implementations connected with each other such that
they are linked independently of the size of the growth area. In
other words, a connecting means (e.g. the foil or bars) holds the
growth locations together when different sizes of the growth area
are adjusted. Basically, the aforementioned foil can also be
combined with the interconnected bars. The latter can for instance
provide a mechanical support, the foil can prevent a dirtying of
the bars. In some embodiments/implementations, the foil and the
bars are alternatives.
[0168] 4.sup.th aspect of the "Resizable Growth Area": The growth
area according to the 3.sup.rd aspect of the "Resizable Growth
Area", wherein the interconnected bars form a scissors mechanism,
the joints being connected operatively with each other.
[0169] This means that a position adjustment of one of the joints
causes also a position adjustment of one or more other joints.
Accordingly, the size of the growth area can be adjusted with a
reduced number of actuators, it is not necessary to equip each
joint/bar with its own actuator.
[0170] 5.sup.th aspect of the "Resizable Growth Area": The growth
area according to the 3.sup.rd or 4.sup.th aspect of the "Resizable
Growth Area", wherein the bars form a flexible grid, the bars
extending parallelly to each other in groups, the bars of the
different groups crossing each other.
[0171] Seen in a top view, the bars form a plurality of
parallelograms. At the crossing locations, the joints are provided,
interconnecting the bars of the different groups with each other.
The growth area can be adjusted in size comparable to a vertical or
stair-case like scissor lift.
[0172] 6.sup.th aspect of the "Resizable Growth Area": The growth
area according to the 3.sup.rd or 4.sup.th aspect of the "Resizable
Growth Area", wherein the bars form a flexible Hoberman-type ring
which can expand in at least two directions, in particular two
directions lying perpendicular to each other.
[0173] A Hoberman-sphere is for instance described in U.S. Pat. No.
5,024,031, this sphere is assembled from a plurality of
Hoberman-rings. In the present case, the Hoberman-ring is used as
the growth area, enabling for instance a more or less rotationally
symmetrical size adjustment. Of course, other geometrical shapes
are also possible, for example trapezoidal and polygonal
structures, foldable structures that form a tessellated area,
rotational arrangements with coplanar sides, pivotably linked
support brackets, scissor-like extendable structures and the
like.
[0174] 7.sup.th aspect of the "Resizable Growth Area": The growth
area according to the 1.sup.st aspect of the "Resizable Growth
Area", being assembled from a plurality of subareas forming a
growth location respectively, wherein the subareas are designed for
floating on water like a raft and can be connected and disconnected
to adjust the distance between the growth locations.
[0175] At the beginning of a growth cycle, the connected subareas
are held together closely, resulting in a growth area of a rather
small overall size. As the plants reach the next growth stage, the
subareas are disconnected so that the growth area is split up. The
subareas will then float independently providing sufficient space
for the plants to grow.
[0176] The connection/disconnection of the subareas can be achieved
by a reversible mechanism, for instance a form-fit or snap-in
mechanism. On the other hand, an irreversible mechanism is possible
as well, and the disconnection can be achieved by for instance
scissors or saws.
[0177] In particular, the floating subareas can be designed as
carriers penetrable for liquids like water, as described in the
element "Aquaponics", they can float on a waterway described in
this element of the disclosure.
[0178] The aspects below relate to an Agricultural System
comprising a resizable growth area.
[0179] 8.sup.th aspect of the "Resizable Growth Area": An
Agricultural System, particularly for plant breeding, growing,
cultivating and harvesting, comprising: [0180] a growth area
according to one of the 1.sup.st to 7.sup.th aspect of the
"Resizable Growth Area", [0181] a light fixture for illuminating at
least a part of the growth area, wherein the Agricultural System is
configured for adjusting the size of the growth area by adjusting
the distance between the growth locations.
[0182] In particular, a plurality of light fixtures can be
provided, see below. In some embodiments/implementations, the size
adjustment is motor-driven, the agricultural system comprising an
actuator device with one or more actuators to adjust the size. For
instance, the actuators can stretch the foil or move the bars, as
described above.
[0183] 9.sup.th aspect of the "Resizable Growth Area": The
Agricultural System according to the 8.sup.th aspect of the
"Resizable Growth Area", the Agricultural System configured for an
adaptive illumination of illumination areas having different
sizes.
[0184] With the adaption, illumination areas differing in size can
be illuminated so that the illumination can be adapted to the size
adjustment of the growth area. Illuminating only the area actually
occupied by plants is advantageous in terms of energy consumption,
see above. The Agricultural System being "configured" means in
particular that it can comprise a computing and/or control device
programmed accordingly (to trigger an actuator and/or the
illumination).
[0185] 10.sup.th aspect of the "Resizable Growth Area": The
Agricultural System according to the 9.sup.th aspect of the
"Resizable Growth Area", wherein the illumination areas of
different sizes are arranged at the same location, wherein only
some light sources or light fixtures are switched on for
illuminating a small growth area and additional light sources or
light fixtures are switched on for illuminating a larger growth
area.
[0186] In other words, the small area(s) is/are contained in the
larger one(s). Therein, only one or some light sources/light
fixtures are switched on for illuminating a small growth area and
additional light sources/light fixtures are switched on for
illuminating larger growth areas.
[0187] 11.sup.th aspect of the "Resizable Growth Area": The
Agricultural System according to the 10.sup.th aspect of the
"Resizable Growth Area", the Agricultural System configured to
shift and/or rotate the growth area and the illumination areas with
respect to each other to control an overlap of the growth area and
a respective illumination area.
[0188] By controlling the overlap, the illumination and/or
irradiance of the growth area can for instance be optimized. In a
stationary reference system, either the growth area or the
illumination setup can be moved for this optimization. In general,
optimizing the overlap can support an efficient use of the light
sources. For instance in case of elongated luminaires, the size
adjustment of the growth area could result in a disadvantageous
partial coverage. Adjusting the relative position of the growth
area allows, as the case may be, also switching off some light
sources or fixtures even though more light sources are used in
total (in case of a larger growth area).
[0189] Depending on the construction of the growth area, a length
elongation of the carrier can lead to a width reduction, for
instance in case of a scissor mechanism described above. There,
light sources/fixtures that are no longer needed due to the width
reduction can be switched off.
[0190] In general, the adaptive illumination can be achieved by
switching light fixtures on or off as a whole. However,
alternatively or in addition, it is also possible to switch
individual light sources belonging to the same light fixture.
Depending on the illumination area required, for instance one half
of the light fixture could be switched on, the other half being
added if required.
[0191] 12.sup.th aspect of the "Resizable Growth Area": The
Agricultural System of the 9.sup.th aspect of the "Resizable Growth
Area", wherein the illumination areas of different sizes are
arranged at different locations which are respectively equipped
with a respective light fixture, the different sizes of the
illumination areas being adapted to different sizes of the growth
area, the Agricultural System configured to move the growth area
from one illumination area at one location to another illumination
area at another location, based on the size of the growth area.
[0192] The illumination areas differing in size are not arranged at
the same location, instead the growth area is moved to another part
of the farm. In addition to the relocation, the growth area can be
rotated to control an overlap. The different illumination areas can
be arranged side by side, but they can also be provided in
different rooms of the farm. For the transportation, a conveyer
belt or roller mechanism can be used for instance. Further, also a
waterway can be used for transporting the growth area, in
particular in case of the connected/disconnectable subareas.
[0193] 13.sup.th aspect of the "Resizable Growth Area": The
Agricultural System according to any one of the 8.sup.th to
12.sup.th aspect of the "Resizable Growth Area", comprising an
actuator device with one or more actuators able to adjust the size
of the growth area, namely the distance between the growth
locations.
[0194] 14.sup.th aspect of the "Resizable Growth Area": The
Agricultural System according to the 13.sup.th aspect of the
"Resizable Growth Area", comprising a sensor device for sensing
growth data of the plants and a computing device configured to
processing the growth data measured by the sensor device and to
initiate the actuator device to adjust the distance between the
growth locations based on the growth data, namely to vary the
distance between the growth locations and hence the size of the
growth area as the plants grow.
[0195] The data measured by the sensor device can be processed by a
computing device, which initiates the actuator device to adjust the
size of the growth area as required. The distance between the
growth location can for instance be increased as the plants
grow.
[0196] 15.sup.th aspect of the "Resizable Growth Area": The
Agricultural System according to the 14.sup.th aspect of the
"Resizable Growth Area", wherein the sensor device comprises an
image capture device and the processing by the computing device
comprises image recognition.
[0197] The image capture device can for example be a camera, it can
be used to determine the actual size of the plants. The images
taken can be processed by a picture recognition. In a simple
approach, for instance, the number of independent plants can be
counted, and the size of the growth area can be increased if two
plants become so close that they appear as one.
[0198] 16.sup.th aspect of the "Resizable Growth Area": An
Agricultural System, comprising:
[0199] a growth area having a plurality of growth locations for
growing plants,
[0200] a sensor device for sensing growth data of the plants,
[0201] an actuator device, and
[0202] a computing device,
[0203] wherein the actuator device is configured for adjusting a
distance between the growth locations and hence a size of the
growth area,
[0204] and wherein the computing device is configured to process
the growth data measured by the sensor device and initiate the
actuator device to adjust the size of the growth area based on the
growth data, namely to vary the distance between the growth
locations and hence the size of the growth area as the plants
grow.
[0205] 17.sup.th aspect of the "Resizable Growth Area": The
Agricultural System of the 16.sup.th aspect of "Resizable Growth
Area", comprising
[0206] a plurality of bars that forms the growth locations of the
growth area,
[0207] a plurality of light fixtures for illuminating illumination
areas, and
[0208] an image capture device comprised in the sensor device,
[0209] wherein the bars form a flexible grid, interconnected with
each other in joints in an articulated manner allowing for folding,
the joints being operatively connected with each other forming a
scissors mechanism,
[0210] wherein, in the flexible grid, the bars extend parallel to
each other in groups, the bars of the different groups crossing
each other,
[0211] wherein the illumination areas have different sizes and are
arranged at different locations the different sizes of the
illumination areas being adapted to different sizes of the growth
area,
[0212] the Agricultural System configured to move the growth area
from one illumination area at one location to another illumination
area at another location, based on the size of the growth area,
[0213] and wherein the growth data, based on which the size of the
growth area is adjusted, comprises images, the processing by the
computing device comprising an image recognition.
[0214] 18.sup.th aspect of the "Resizable Growth Area": A Method
for using a growth area according to any one of the 1.sup.st to
7.sup.th aspect of the "Resizable Growth Area", or an Agricultural
System according to any one of the 8.sup.th to 17.sup.th aspect of
the "Resizable Growth Area", comprising the steps:
[0215] growing plants at the growth locations,
[0216] adjusting the distance between the growth locations based on
the growth of the plants.
[0217] In some embodiments/implementations, this adjustment is done
or triggered automatically by a computing device connected with a
sensor device for sensing the growth and an actuator device,
triggered by the computing device (e.g. via a control unit), for
adjusting the size of the growth area.
[0218] 19.sup.th aspect of the "Resizable Growth Area": A Method
for agriculture, comprising at least one Agricultural System, and
comprising:
[0219] growing plants.
[0220] 20.sup.th aspect of the "Resizable Growth Area": A Computer
program product, comprising:
[0221] a plurality of program instructions, which when executed by
a computing device of an Agricultural System, cause the
Agricultural System to apply defined growing conditions to the
plants.
[0222] The application of "defined growing conditions" may for
instance be: applying a light recipe, adjusting a temperature,
and/or adjusting a CO.sub.2 content. The defined growing conditions
can for instance be comprised in growth recipe, see below for
illustration.
[0223] 21.sup.th aspect of the "Resizable Growth Area": Computer
program product, comprising:
[0224] a plurality of program instructions, which when executed by
a computing device of an Agricultural System according to any one
of the 8.sup.th to 17.sup.th aspect of the "Resizable Growth Area",
cause the Agricultural System to execute an adjustment of the
distance between the growth locations.
[0225] Regarding further details, reference is made to the
description above. The program instructions can be pre-programmed
or calculated based on measurement values. Pre-programmed
instructions can for instance follow linear or non-linear function
over time (or over total Photon Flux or any other photometric
value, or assumed plant leaf density index), or first exponential,
then logarithmic etc.
[0226] "Hydroponics"
[0227] This element of the disclosure relates in particular to
floating grow fields and a respective waterway for moving them
through the farm.
[0228] 1.sup.st aspect of "Hydroponics": A Grow field for a
hydroponic arrangement, comprising a carrier for carrying plants,
wherein the carrier is designed to be penetrable for liquids like
water.
[0229] This element of the disclosure solves the problem of how to
provide irrigation and nutrients to the plants and yet allows for
transportation of the plants through the farm over the growth
cycle. It is proposed that the plants grow in small grow fields
filled with materials as used in hydroponics, e.g. expanded clay
aggregates, growstones, perlite, pumice, rock wool etc. The grow
fields are surrounded by water. Each grow field may contain a
single plant or several plants. The roots of the plants may be
hanging in the water. The water is used to provide irrigation and
nutrients. However, the small grow fields are not fixed and
surrounded by flowing water, but movable within the surrounding
water.
[0230] 2.sup.nd aspect of "Hydroponics": The Grow field according
to the 1.sup.st aspect of "Hydroponics", wherein the carrier is
designed for floating on water like a raft.
[0231] The preferred design is thus not the form of a plant pot,
but a form that resembles a raft and allows floating on the water
without tilting over. The sides of the small grow fields,
especially the backside lying in the water, comprise a grid-like
structure, so they hold back the plants and the grow materials but
let in the water.
[0232] Seen in a top view, the shape of the grow fields can be
quadratic, rectangular, hexagonal, circular, or freeform. Grow
fields for the same kind of plant can have the same form. Grow
fields for another kind of plant can have a different form. In this
way, different shapes may facilitate identification of various
kinds of plants. Furthermore, the shape can influence the drift
velocity. Grow fields may be connected with each other (e.g. by
magnets or any other connecting means like for instance form-fit
members, see also the 7.sup.th aspect of "Resizable Growth Area"),
so that they form a chain of grow fields and float
collectively.
[0233] The grow fields may be equipped with a variety of sensors
and e.g. RFID or WLAN chips that transpond/repeat/send information
to a reading device for asset tracking. Such reading devices may be
arranged in light fixtures that may be arranged above the grow
fields for irradiating/illuminating the plants.
[0234] 3.sup.rd aspect of "Hydroponics": The Grow field according
to the 1.sup.st aspect of "Hydroponics", wherein wheels are
connected to the carrier for rolling on the bottom of an area
covered with water, while keeping the carrier like floating on the
water surface.
[0235] In this case, the rafts floating on the water could be
replaced by trays with wheels, which are rolling on the bottom of
the water tank. In this case, the movement of the grow
fields/plants can be assured by the inclination of the water tank
alone.
[0236] 4.sup.th aspect of "Hydroponics": A Hydroponic arrangement,
comprising one or more grow fields according to any one of the
preceding aspects of "Hydroponics", and further comprising a
waterway, wherein the grow fields are movably arranged on the
surface of the waterway.
[0237] The waterway, in which the small grow fields are floating,
may be an elongated water tank, which is open on its upper side,
i.e. the water surface. The small grow fields are floating on the
water surface from one side of the water tank (start) to the other
(end), along its long side. In some embodiments/implementations,
the time it takes a grow field to reach the end coincides with the
time it takes for the respective plant to be ready for harvesting.
A distance between start and end can for instance be at least 2 m,
4 m, 6 m or 8 m (with possible upper limits of for instance not
more than 500 m, 200 m or 100 m).
[0238] 5.sup.th aspect of "Hydroponics": The Hydroponic arrangement
according to the 4.sup.th aspect of "Hydroponics", configured to
establish a water flow on the surface of the waterway.
[0239] The water flow can move the grow fields along the
waterway.
[0240] 6.sup.th aspect of "Hydroponics": The Hydroponic arrangement
according to the 4.sup.th or 5.sup.th aspect of "Hydroponics",
further comprising one or more inlets arranged at the waterway for
the inflow of water.
[0241] In particular, the inflowing water can generate the water
flow for moving the grow fields.
[0242] 7.sup.th aspect of "Hydroponics": The Hydroponic arrangement
according to the 5.sup.th or 6.sup.th aspect of "Hydroponics",
wherein the grow fields are able to float on the surface of the
waterway along the water flow.
[0243] To summarize, the floating of the plants from the first end
(start) to the final end (where they can be harvested) can be
assured e.g. by:
[0244] An inclination of the ground of the water tank, which
provides the waterway (or an inclination of the whole water tank)
towards the final end, where the waterway contains a sink for the
water, so that the water automatically flows towards the final end
and/or,
[0245] Water inlets or nozzles attached at the first end and/or at
the side of the water tank (in some embodiments/implementations
arranged close to the water surface) pointing towards the final end
and thus inducing a direction of flow on the water.
[0246] The water inlets do not only provide fresh water, they also
provide the nutrients needed for the plants (like phosphor, oxygen
dissolved in the water, . . . ). Therefore, in some
embodiments/implementations, the water inlets are attached to the
side of the water tank in any case, although they do not
necessarily have to point to the final end of the water tank if the
water flow is assured by the inclination of the tank.
[0247] In a preferred embodiment, the water tank also contains at
least one sink to remove the water from the water tank as the water
inlets add water. In this way, a flow on the surface of the water
may be established without raising the level of the water in the
water tank.
[0248] 8.sup.th aspect of "Hydroponics": The Hydroponic arrangement
according to any one of the 4.sup.th to 7.sup.th aspect of
"Hydroponics", further comprising one or more light fixtures
arranged above the surface of the waterway.
[0249] The floating speed of the small grow fields can be
controlled by the inclination of the water tank and/or the speed
with which the water inlets blow the water into the tank. However,
it may be advantageous, e.g. in a small tank (i.e. where the small
grow fields would only need to move very slowly to reach the final
end) to add grids across the tank, which can hold back the small
grow fields.
[0250] 9.sup.th aspect of "Hydroponics": The Hydroponic arrangement
according to any one of the 4.sup.th to 7.sup.th aspect of
"Hydroponics", further comprising one or more grids arranged across
the waterway, wherein the grids are able to hold back the grow
fields.
[0251] With the grids, the water tank can be separated into several
grow areas or zones. In each grow area (which is a growth sector or
zone), the growth parameters may be different, e.g. nutrients may
be added in another concentration or the light intensity or the
light spectrum of the light sources of the light fixtures might be
different for each grow area. If the plants have reached the end of
the growth cycle, the grid is moved aside (to a side, up or down,
or open like a water lock) and the grow fields move on to the next
growth area where they can be exposed to one or several different
grow parameters like illumination, temperature or nutrients.
Furthermore, the light intensity and/or light spectrum may also be
adjusted to the water flow speed. The waterway at each station/grow
area may have a different depth level and temperature than the
previous or subsequent one.
[0252] Below, an Agricultural System with a waterway (Hydroponic
arrangement) is discussed.
[0253] 10.sup.th aspect of "Hydroponics": A Controlled Agricultural
System, particularly for hydroponic growth, comprising at least one
hydroponic arrangement according to any one of the 4.sup.th to
8.sup.th aspect of "Hydroponics", further comprising:
[0254] an actuator device, comprising one or more actuators able to
adjust parameters of the hydroponic arrangement, e.g., water inlet,
water sink, water grid, nutrient dosing feeder, light fixture.
[0255] a data storage device for storing reference data of the
parameters of the hydroponic arrangement,
[0256] a computing device, configured to control the parameters of
the hydroponic arrangement by means of the actuator device and
based on the data of the parameters stored on the data storage
device.
[0257] The computing device can control the water flow, and the
grow parameters like nutrient concentration and illumination by
means of respective actuators. The system may control these
parameters based on fixed values provided in a database or based on
sensor inputs e.g. from cameras, light sensors, temperature sensors
or chemical sensors. The database is stored in a data storage
device that may be based locally, in a network or the cloud.
[0258] 11.sup.th aspect of "Hydroponics": The Controlled
Agricultural System according to the 10.sup.th aspect of
"Hydroponics", further comprising a sensor device.
[0259] The sensor device can comprise one or more sensors able to
sense/detect growth parameters of the plants on the grow fields
and/or control parameters of the hydroponic arrangement, e.g. flow
speed indicator, thermometer, photometer, color detector,
camera.
[0260] 12.sup.th aspect of "Hydroponics": The Controlled
Agricultural System according to the 10.sup.th or 11.sup.th aspect
of "Hydroponics", further comprising a user interface configured to
deliver the growth status of the plants on the grow fields and/or
the status of the hydroponic arrangement.
[0261] The information about the growth status or the status of the
grow system can be provided to customers, the farmer or other third
parties.
[0262] 13.sup.th aspect of "Hydroponics": A Method for agricultural
management, particularly for hydroponic growth, comprising:
[0263] at least one controlled agricultural system according to any
of the 10.sup.th to 12.sup.th aspect of "Hydroponics", and the
steps of
[0264] planting one or more plants into one or more grow
fields,
[0265] putting the grow fields at a first position on the water
surface of the waterway of the hydroponic arrangement,
[0266] adjusting the parameters of the hydroponic arrangement, e.g.
water flow, illumination, controlling of the grids, concentration
of nutrients in the water of the waterway, temperature of water
and/or ambient air, by means of the actuator device and based on
respective data of the parameters retrieved from the data storage
device, with the goal that the plants are ready for harvest when
they arrive downstream at a final position,
[0267] moving the grow fields on the water surface from the first
position of the waterway downstream to the final position of the
waterway,
[0268] removing the grow fields from the water surface at the final
position of the waterway.
[0269] 14.sup.th aspect of "Hydroponics": A Method for agricultural
management according to the 13.sup.th aspect of "Hydroponics",
further comprising the step of
[0270] Sensing growth parameters of the plants by means of the
sensor device, and
[0271] readjusting the parameters of the hydroponic arrangement
according to the sensed growth parameter.
[0272] 15.sup.th aspect of "Hydroponics": A Computer program
product, comprising:
[0273] a plurality of program instructions, which when executed by
a computing device of a Controlled Agricultural System according to
any one of the 10.sup.th to 12.sup.th aspect of "Hydroponics",
cause the Controlled Agricultural System to execute the method for
Agricultural Management according to any one of the 13.sup.th to
14.sup.th aspect of "Hydroponics".
[0274] "Horticulture Processing Line"
[0275] This element of the disclosure describes an automated
processing line for growing plants.
[0276] 1.sup.st aspect of the "Horticulture Processing Line": A
Controlled Agricultural System comprising
[0277] a processing line having different growth zones where
defined growth conditions can be applied,
[0278] growth trays for respectively growing at least one plant,
the growth trays being moveable along the processing line from a
first growth zone to a last growth zone,
[0279] a treatment location where defined treatment conditions can
be applied,
[0280] wherein the Controlled Agricultural System is configured for
moving the growth trays along the processing line,
[0281] wherein at least one tray, but not all trays, is unloaded
from the processing line to the treatment location prior to having
reached the last growth zone.
[0282] In each growth zone, defined growth conditions can be
applied, for instance a defined illumination (intensity/spectral
composition), temperature, humidity or the like. At each growth
zone, the growth conditions can be optimized regarding a certain
growth stage of the plants. In case of a Hydroponic arrangement
(see "Hydroponics"), the growth zone can be a "grow area" discussed
there (see in particular the 9.sup.th aspect of "Hydroponics").
[0283] In general, the first growth zone can for instance be
optimized for the sawing or seeding or for an early growth stage.
After having reached a certain size or growth stage, the plants may
require other growth conditions to maximize the yield. Humidity and
temperature may for instance be lower than during early seeding.
Accordingly, the plants can be moved to the next growth zone of the
processing line. After a further growth there, the plants are moved
to the next growth zone until they reach their final growth stage,
becoming ready for harvesting in the last growth zone.
[0284] For moving the plants along the processing line, the
agricultural system is equipped with growth trays (e.g. grow fields
in "Hydroponics"). Depending on the size, the trays can receive a
container or receptible or the like, they can also have a bowl- or
receptible-like shape themselves. In general words, a defined
volume for receiving soil or hydroponics or any other matrix
material for growing plants is provided at each growth tray.
Depending on the type of plants grown, at least one or also a
plurality of plants can be grown at or on each growth tray.
[0285] The agricultural system is configured for moving the growth
trays along the processing line, either continuously (like in a
conveyer oven) or in steps from sector to sector. In the latter
case, the growth trays are moved on further after having stayed a
certain time at the respective growth zone, which can be predefined
or depend from growth data measured with a sensor device, for
instance a camera or the like. Regarding a possible design of
growth trays and/or a setup for moving them, reference is again
made to "Hydroponics". Further, the growth trays can also be
connected in groups, each group forming or being a resizable growth
area. Those growth areas can be moved through the farm as described
in in "Resizable Growth Area".
[0286] According to the element "Horticulture Processing Line", the
agricultural system additionally comprises a treatment location.
There, defined treatment conditions can be applied, see in detail
below. Therein, the agricultural system is configured to unloading
one or some of the trays from the processing line prior to having
reached the last growth zone, while other trays pass by on the
processing line. In some embodiments/implementations, this is done
automatically. The other trays are moved further from sector to
sector along the processing line.
[0287] 2.sup.nd aspect of the "Horticulture Processing Line": The
Controlled Agricultural System of the 1.sup.st aspect of the
"Horticulture Processing Line", configured for reloading the at
least one tray to the processing line after the treatment at the
treatment location.
[0288] Thus, the at least one tray is reloaded to the processing
line later on. In a simple setup, it might be reloaded via the
first growth zone, even though the growth conditions there might
not be appropriate for plants having been unloaded at a later
stage.
[0289] 3.sup.rd aspect of the "Horticulture Processing Line": The
Controlled Agricultural System of the 2.sup.nd aspect of the
"Horticulture Processing Line", configured for reloading the at
least one tray to the processing line at that growth zone where it
has been unloaded.
[0290] In case of a preferred system with a clocked operation
(trays moved from sector to sector after a respective time
interval), a gap can be left between two trays fed one after the
other to the first growth zone. Due to the clocked movement, the
gap propagates along the processing line, until the tray of the
treatment location is reloaded into the gap at the appropriate
processing stage.
[0291] 4.sup.th aspect of the "Horticulture Processing Line": The
Controlled Agricultural System of one of the preceding aspects of
"Horticulture Processing Line", wherein the trays are moved along
the processing line from one growth zone to another pursuant to a
predefined clocking.
[0292] 5.sup.th aspect of the "Horticulture Processing Line": The
Controlled Agricultural System of the 3.sup.rd and 4.sup.th aspect
of the "Horticulture Processing Line", configured for leaving a gap
between two trays fed one after the other to the first growth zone,
wherein the at least one tray is reloaded to the processing line
into the gap.
[0293] Providing a treatment location for selectively unloading
trays from the processing line can enable a high output and good
quality, while only a minor or even no human interaction or support
is required. Since only a few trays are unloaded selectively, the
overall throughput remains high. For instance, not more than 40%,
30%, 20% or 15% of the trays can be unloaded to the treatment
location (with possible lower limits of for example 1%, 2% or 3%).
Unloading individual trays from the processing line can also
protect the trays remaining on the processing line, for instance in
case of a pest or fungal infestation or other contamination.
Further criteria for unloading plants from the processing line can
be their size (too small/too large) or fruit yield (too few/too
many fruits).
[0294] 6.sup.th aspect of the "Horticulture Processing Line": The
Controlled Agricultural System of one of the preceding aspects,
configured for unloading the at least one tray based on at least
one of
[0295] a plant size,
[0296] a plant morphology,
[0297] a fruit yield,
[0298] a biological or chemical fruit ripeness indicator,
[0299] a pest infestation,
[0300] a fungal infestation,
[0301] a contamination.
[0302] As described above, the growth conditions at each growth
zone may be optimized regarding the respective growth stage. The
unloading of individual trays can also be used for a further
optimization of the growth conditions applied at a specific sector.
For instance, the light recipe, e.g. the spectral composition or
intensity of the light, can be adapted, not only to the plant type,
but even to individual lots.
[0303] 7.sup.th aspect of the "Horticulture Processing Line": The
Controlled Agricultural System of one of the preceding aspects,
wherein the treatment applied at the treatment location is at least
one of
[0304] an illumination treatment,
[0305] a low or high temperature treatment,
[0306] a gas absorption treatment,
[0307] an insect attraction treatment,
[0308] a controlled humidity treatment,
[0309] an UV-radiation treatment,
[0310] a non-lighting treatment.
[0311] To summarize, the treatment applied in the treatment
location can be an illumination treatment (specific lighting with
VIS, UV and/or IR light), a low or a high temperature treatment, a
gas absorption (for instance of ethylene), an insect attraction
treatment (to treat a pest infestation) and/or a humidity treatment
and/or a non-lighting treatment (OFF-period) in a dark environment.
Basically, a manual treatment of an operating personnel is
possible, even though a fully automated treatment is preferred.
[0312] A target of the treatment applied may be to reduce or
eliminate any deviation having been the reason for unloading the
tray from the processing line. Alternatively or in addition, a
specific measurement may be performed in the treatment location,
see above. The tray unloaded from the processing line to the
treatment location can be used for optimizing not only the light
recipe but also other control parameters like temperature, humidity
or the like. In case that the treatment conditions applied at the
treatment location have a positive effect on the plant growth, they
can be transferred to one or more growth zones of the processing
line.
[0313] To protect the plants remaining on the processing line, the
treatment location can be a quarantine area. In a worst-case
scenario, the plants unloaded could be destroyed to prevent an
infestation/contamination of the plants remaining on the processing
line.
[0314] 8.sup.th aspect of the "Horticulture Processing Line": The
Controlled Agricultural System of one of the preceding aspects,
wherein the treatment location is a quarantine area.
[0315] In general, the tray or trays unloaded from the processing
line might be predefined (e.g. every 10th tray) or chosen in a
stochastic procedure. The unloading from the processing line to the
treatment location could be kind of a lot control, allowing a
detailed inspection/monitoring of the plants. In some
embodiments/implementations, the unloading is triggered by a sensor
measurement.
[0316] 9.sup.th aspect of the "Horticulture Processing Line": The
Controlled Agricultural System of one of the preceding aspects,
comprising a sensor device for sensing plant growth, harvesting
time, plant morphology and/or plant health and ripeness, the
Controlled Agricultural System being configured for unloading the
at least one tray based on a measurement by the sensor device.
[0317] In some embodiments/implementations, the agricultural system
comprises a plurality of sensor systems, which can be cameras,
distance measuring devices or the like. A sensor device can for
instance be integrated into a light fixture comprising the light
sources for the lighting. Alternatively or in addition, a sensor
device can be integrated into the tray. A sensor device at the tray
can monitor the conditions that have been applied to the plants so
far (e.g. temperature, illumination and so on).
[0318] 10.sup.th aspect of the "Horticulture Processing Line": The
Controlled Agricultural System of one of the preceding aspects,
configured for storing growth data, namely data about the growth
conditions applied to the growth trays and/or sensor data about
plant growth, harvesting time, plant morphology and/or plant
health, in a data storage device.
[0319] The data storage device can be an internal part of the
agricultural system, connected or integrated into the computing
device. However, the data storage device can also be provided
externally, for instance in the cloud. Data storage and handling
can be done using for example a distributed Blockchain ledger
system that ensures accuracy and data permanency for each tray
and/or sub-tray and/or plant thus allowing a producer or customer
to track the history of a specific plant product.
[0320] 11.sup.th aspect of the "Horticulture Processing Line": The
Controlled Agricultural System of the 10.sup.th aspect of the
"Horticulture Processing Line", configured for storing the growth
data individually for the trays, namely assigned to a respective
tray.
[0321] The growth data can be data about growth conditions or
sensor data measured, is stored individually for the trays.
Accordingly, for some or all of the trays, the growth conditions
which have been applied/measured for the specific tray are assigned
to the tray. In some embodiments/implementations, the trays can be
provided with a respective identifier, for instance a barcode,
RFID-tag or the like. An identifier can simplify the correlation
between the growth data and a specific tray.
[0322] 12.sup.th aspect of the "Horticulture Processing Line": The
Controlled Agricultural System of one of the preceding aspects,
wherein the growth trays are provided with a respective identifier
allowing an individualization of the trays.
[0323] 13.sup.th aspect of the "Horticulture Processing Line": The
Controlled Agricultural System of one of the preceding aspects,
wherein a transfer gate for unloading growth trays from the
processing line is provided at each growth zone.
[0324] In some embodiments/implementations, a plurality of
treatment locations are provided along the processing line so that
the trays can be unloaded at different growth zones (in different
growth stages) to a different treatment location respectively.
Therein, in a basic setup, each of the treatment locations can be
linked to the processing line solely. Likewise, the trays can be
unloaded from and reloaded to the processing line, or be destroyed
at the treatment location, but not transferred from one treatment
location to the other directly.
[0325] 14.sup.th aspect of the "Horticulture Processing Line": The
Controlled Agricultural System of one of the preceding aspects,
wherein a plurality of treatment locations are provided, linked
with each other by a second processing line.
[0326] Thus, the trays unloaded from the first processing line can
also be moved along the second processing line from one treatment
location to another. They can be processed on the second processing
line until a final growth stage has been reached or can be reloaded
to the first processing line before. Alternatively, the treatment
location can be a "blind end" to which the plants are unloaded for
treatment or destruction.
[0327] 15.sup.th aspect of the "Horticulture Processing Line": The
Controlled Agricultural System of one of the preceding aspects,
wherein at least a section of the processing line extends
horizontally, the growth trays being transported horizontally by
vehicles or on a conveyer belt from one growth location to the
other.
[0328] Horizontally, the growth trays can be transported by
vehicles, in particular vehicles driving autonomously.
Alternatively or in addition, a conveyer belt can be used for a
horizontal transportation. Further, the growth trays could also
float along a waterway, see for instance "Hydroponics". A vertical
transportation can be achieved by an elevator, in particular of a
paternoster-type elevator.
[0329] 16.sup.th aspect of the "Horticulture Processing Line": The
Controlled Agricultural System of one of the preceding aspects,
wherein at least a section of the processing line extends
vertically, the growth trays being transported vertically by an
elevator.
[0330] 17.sup.th aspect of the "Horticulture Processing Line": The
Controlled Agricultural System of the 16.sup.th aspect of the
"Horticulture Processing Line", wherein the elevator is of a
paternoster type.
[0331] 18.sup.th aspect of the "Horticulture Processing Line": The
Controlled Agricultural System of one of the preceding aspects,
wherein the growth zones are respectively equipped with a light
fixture for agricultural lighting.
[0332] Each growth zone can be equipped with a plurality of light
fixtures, wherein each light fixture can comprise a plurality of
light sources, like halogen lamps, discharge lamps, semiconductor
LEDs, OLEDs and Laser, and the like. In particular, light sources
having different spectral properties can be mixed to adjust a
spectral composition which is optimized regarding the specific
plants or the growth status. The light fixtures can be installed
having a fixed distance to a processing line, for example, a
conveyor belt, though the light fixtures in different sectors can
have different distances. In another embodiment, the light fixtures
can be installed in a flexible way, so that their distance to the
plants can be varied over time, in some embodiments/implementations
automatically.
[0333] 19.sup.th aspect of the "Horticulture Processing Line": A
Method for Controlling a Controlled Agricultural System according
to one of the preceding aspects,
[0334] wherein plants are grown in the growth trays and the growth
trays are moved along the processing line,
[0335] wherein at least one tray is automatically unloaded from the
processing line to the treatment location prior to having reached
the last growth zone.
[0336] 20.sup.th aspect of the "Horticulture Processing Line": A
Computer program product, comprising:
[0337] a plurality of program instructions, which when executed by
a computing device of a Controlled Agricultural System according to
any one of the 1.sup.st to 18.sup.th aspect of the "Horticulture
Processing Line", cause the Controlled Agricultural System to
execute the Method for Controlling a Controlled Agricultural System
according to the 19.sup.th aspect of the "Horticulture Processing
Line".
[0338] The program instructions can use the data to
calculate/generate a `virtual twin facility`, see also "Measuring
Patterns" below, of such a controlled agricultural system and show
it graphically to a producer or customer for an informed
interaction and control.
[0339] "Measuring Patterns"
[0340] Growers have different demands regarding the plant growth.
Furthermore, they want to monitor the plant growth continuously.
Demands may comprise plant quantity, plant quality, post-harvesting
quality, and/or storage and delivery time. Plant quality is mainly
defined by primary and secondary metabolites as well as appearance
(color, morphology). Plant quantity is defined by yield (fresh or
dry weight). Plants comprise herbs, vine crops, microgreens, leafy
greens, fruits and the like.
[0341] A growth recipe comprises values for a light recipe
(spectrum, intensity, photoperiod), content of CO.sub.2-- and other
gases in the air, temperature (air, soil), humidity, nutrients, EC
(electrical conductivity), pH, H.sub.2O, chemical and biological
composition of the soil, Hydroponics and aeroponics parameters,
etc. A light recipe may comprise a time-sequential set of
individual light recipes. However, the actual setup of the
agricultural facility/plant growing facility (light sources, light
fixtures, placement of light fixtures, actuators, sensors) will be
different for almost every grower so that a pre-defined growth
recipe might not provide the optimal result. New requirements that
have not been tested before might also not lead to the desired
results. A recipe may be suited and applicable to generate desired
growth conditions in a 2D and 3D agricultural environment.
[0342] This is one example, why a group of sensors or a sensor
device system, which comprises a plurality of sensors, for
measuring the actual plant-growth relevant data can be of interest.
This data can for instance be used for triggering actuators and/or
can be stored, for example in a general platform, e.g. a digital
platform like an online-platform (e.g. in the cloud) or a local
data storage device.
[0343] 1.sup.st aspect of "Measuring Patterns": A Method for
arranging a plurality of sensors in an agricultural facility, e.g.
in a plant growing facility, [0344] the sensors being of the same
type (first type), wherein [0345] i) the sensors are placed in a
first relative arrangement in the agricultural facility; [0346] ii)
a measurement is performed with the sensors being in the first
relative arrangement; [0347] iii) at least some of the sensors are
removed and/or re-positioned.
[0348] "Re-positioning" means that the sensors are placed at
another location in the agricultural facility and/or are oriented
in another direction. Thus, the sensors are re-located and/or
re-oriented. For instance in case of optical sensors, e.g. cameras,
the re-orientation can change the detection field even without a
re-location.
[0349] From steps i)/ii) to step iii), the distribution of the
sensors can be optimized. This means that the farm is covered
sufficiently while the overall number of sensors is kept as low as
possible. This can reduce the overall cost of the facility. With
the approach described here, an optimum coverage can be achieved
nevertheless. In simple words, the agricultural facility is
measured with a high (global or local) sensor density initially
(first relative arrangement, steps i/ii). In the final setup (step
iii), sensors are for instance placed only where the measured
values differed significantly (in time or locally). In other words,
sensors which do not provide new information, as the data that they
are providing is almost identical to neighboring sensors, will be
removed/re-positioned. Likewise, the overall number of sensors can
be reduced.
[0350] The measurement of step ii can for instance cover a time
interval of at least 1 hour, 2 hours, 4 hours, or 6 hours. Possible
upper limits are for instance 8, 6, 4, or 2 weeks, further possible
upper limits being for instance 10 days, 8 days, 6 days or 4 days.
Advantageously, a time interval covering one or more days can give
an impression over the circadian rhythm of the plants (covering
day/night cycles).
[0351] The sensors being "of the same type" are adapted for
measuring the same physical quantity. In some
embodiments/implementations, these sensors are identical in
construction. A physical quantity measured can for instance be the
temperature, humidity, leaf temperature, VPD (vapor pressure
deficit), substrate moisture, substrate temperature, or EC
(electrical conductivity), further, the pH-value, wind/air
velocity, or PAR (photosynthetically active radiating) can be
measured. It is also possible to measure vibrations, or sound, but
also camera imaging solutions (including hyperspectral imaging) can
be implemented. The sensor system may also be configured to measure
the geometrical layout and texture of an agricultural environment,
like a vertical farm or a greenhouse.
[0352] The "plurality" of sensors can for instance be at least 5,
10, 20, 30 or 40 sensors (with possible upper limits of for
instance not more than 1000, 500 or 100).
[0353] 2.sup.nd aspect of "Measuring Patterns": The Method of the
1.sup.st aspect of "Measuring Patterns", wherein, in the first
relative arrangement, a local areal density of the sensors is
higher than after step iii).
[0354] The local areal density is taken locally, namely in a
subarea of the growth area of the farm. The growth area is the
total area used for growing plants in the farm. A subarea, in which
the local aerial density is taken, can for instance cover not more
than 70%, 50% or 30% of the growth area (possible lower limits are
for instance at least 1%, 5% or 10%).
[0355] 3.sup.rd aspect of "Measuring Patterns": The Method of the
2.sup.nd aspect of "Measuring Patterns", wherein the sensors are
placed in a second relative arrangement prior to step iii), the
local areal density of the sensors being higher in the second
relative arrangement than after step iii).
[0356] The first and the second relative arrangement differ at
least partly. From the first to the second relative arrangement, at
least some of the sensors are re-positioned.
[0357] 4.sup.th aspect of "Measuring Patterns": The Method of the
3.sup.rd aspect of "Measuring Patterns", wherein all sensors are
re-positioned from the first to the second relative
arrangement.
[0358] Likewise, prior to step iii, the growth area of the farm can
be scanned successively. In each relative arrangement, the sensors
form a scan field with a high local areal density of the sensors,
these scan fields cover the growth area step by step. In a sense,
the scan fields are moved across the farm.
[0359] 5.sup.th aspect of "Measuring Patterns": The Method of the
3.sup.rd or 4.sup.th aspect of "Measuring Patterns", wherein the
local areal density of the sensors is the same in the first and the
second relative arrangement.
[0360] 6.sup.th aspect of "Measuring Patterns": The Method of any
of the 3.sup.rd to 5.sup.th aspect of "Measuring Patterns", wherein
a first measuring area covered by the sensors in the first relative
arrangement and a second measuring area covered by the sensors in
the second relative arrangement overlap at most partly, if at
all.
[0361] The measuring areas are respectively smaller than the
overall growth area of the farm (the area of the farm used for
growing plants).
[0362] 7.sup.th aspect of "Measuring Patterns": The Method of any
of the 3.sup.rd to 6.sup.th aspect of "Measuring Patterns", wherein
the number of sensors after step iii) is the same as in step i).
Thus, no sensors are removed in step iii).
[0363] During the initialization/setup phase, the sensors are moved
across the growth area in the high density arrangements (scan
fields), thereafter the same sensors are placed with a smaller
local aereal to monitor the farm during normal operation.
[0364] 8.sup.th aspect of "Measuring Patterns": The Method of any
of the preceding aspects of "Measuring Patterns", wherein, after
step iii), a local areal density of the sensors is varying across
the farm, the local areal density being [0365] smaller in a
subarea, where a smaller deviation between the sensors was observed
prior to step iii);
[0366] and [0367] larger in a subarea, where a larger deviation
between the sensors was observed prior to step iii).
[0368] Therein, "smaller"/"larger" relates to a comparison between
the different subareas of the farm.
[0369] 9.sup.th aspect of "Measuring Patterns": The Method of any
of the preceding aspects of "Measuring Patterns", wherein a
plurality of additional sensors, which are of a second type
(different from the first type), are provided, wherein [0370] iv)
the additional sensors are placed in a first relative arrangement
in the agricultural facility; [0371] v) a measurement is performed
with the additional sensors being in the first relative
arrangement; [0372] vi) at least some of the additional sensors are
removed or re-positioned.
[0373] Therein, the measurements with the first sensors and the
additional sensors can be performed one after the other or
simultaneously. In other words, steps ii) and v) can be performed
at the same time or subsequently.
[0374] 10.sup.th aspect of "Measuring Patterns": The Method of the
9.sup.th aspect of "Measuring Patterns", wherein, after step iii),
[0375] a local areal density of the first sensors is smaller in a
region where a local areal density of the additional sensors is
larger;
[0376] and/or [0377] a local areal density of the additional
sensors is smaller in a region where a local areal density of the
first sensors is larger.
[0378] Likewise, correlations or dependencies between the different
sensor types are taken into account to reduce the overall number of
sensors. A correlation can for instance exist between temperature
and humidity.
[0379] 10.sup.th aspect of "Measuring Patterns": The Method of any
of the preceding aspects of "Measuring Patterns", wherein a digital
model of the plant growing facility, namely a digital facility
twin, is rendered to indicate/suggest the positions of the sensors
in the digital model.
[0380] In particular, a computing device can be configured to
render the digital facility twin. The rendering can be performed
based on the data stored in the data storage device. In the digital
facility twin, the positions of the sensors for the first relative
arrangement (of the first and/or additional sensors) can be
indicated/suggested, but also the sensor positions for step iii)
and/or step vi).
[0381] "Measuring Patterns" can also be implemented into an
Agricultural System, configured for performing a method according
to any of the preceding aspects of "Measuring Patterns".
[0382] The Agricultural System can be configured to be able to
manage the positioning (including orientation and inclination) and
re-positioning of the sensors of the sensor devices for monitoring
the plant growth and, optionally, the status of the plant growing
facility (e.g. for the maintenance of the equipment used in the
plant growing facility) based on the data stored in the data
storage device. In particular, this element of the disclosure can
relate to a Controlled Agricultural System, particularly for
breeding, growing, cultivating and harvesting in an agricultural
facility, e.g. in a plant growing facility, comprising at least one
sensor device, comprising a group of sensors able to measure
environmental parameters (e.g. temperature, light intensity,
etc.).
[0383] In particular, the Agricultural System can comprise a
computing device, configured to be able to access and control the
at least one sensor device and the data storage device. In some
embodiments/implementations, the computing device is configured for
the positioning and re-positioning of the sensor.
[0384] The Agricultural System can also comprise a data storage
device (e.g. platform/cloud) for storing data about the plant
growing facility (e.g. layout, size, placement of light fixtures,
actuators, etc.) and the at least one sensor device (e.g. types of
sensors in the groups, number of sensors per group, range of
sensors, etc.), The positioning and/or re-positioning can be
managed based on the data stored in the cloud.
[0385] In particular, the computing device can be configured to
access and control the sensor device system and the data storage
device/platform. Furthermore, the computing device is configured to
access the set of measurement data, to analyze them and to compare
them with other data sets, for example, stemming from other
controlled agricultural systems, or from standardized or ideal data
sets or current or historical user data sets.
[0386] The sensor device system may comprise a variety of different
sensor types in order to measure a variety of relevant plant growth
data as well as post-harvest plant data, like the concentration of
certain enzymes or the concentration of vitamins and glucose. The
sensor device system may comprise a variety of different sensor
types in order to measure and recognize pest-related and/or disease
related parameters. The sensor device may be configured to
establish a communication and/or data processing and analyzing
network between themselves.
[0387] To create and update the growth recipes, the status of the
plant growth and of the plant growth facility needs to be
understood. To record the status, a set of sensors need to be
deployed in the facility. These sensors may include ambient
sensors.
[0388] The group of sensors can be able to measure one or more of
the following parameters: temperature, humidity, leaf temperature,
VPD (vapor pressure deficit), substrate moisture, substrate
temperature, EC (electrical conductivity) and pH-value, velocity,
PAR (photosynthetically active radiating). Alternatively or in
addition, sensors measuring vibrations, sound but also camera
imaging solutions including hyperspectral imaging may be used. The
sensor system may also be configured to measure the geometrical
layout and texture of an agricultural environment, like a vertical
farm or a greenhouse. A sensor can also be an optical detection
device, particularly for imaging methods, e.g. a camera.
[0389] In an aspect of "Measuring Patterns", the sensors are able
to communicate with each other or with a control unit. The sensors
may form local sub-systems with a respective control unit. The
local sub-systems can be adaptively reconfigured based on output
data from an artificial intelligence network system. An overall
control unit (e.g. the computing device) may manage data fusion of
different sensors and subsequent data analysis as well as data
forecasting. The sensor data may be fed into an Artificial
Intelligence system that, after calculating, outputs data that can
be used for plant modelling and the steering of actuators.
[0390] It can be advantageous to find the optimal place for the
different sensors to optimize the use of sensors (minimum number
needed) and nevertheless get a comprehensive overview about the
growth situation.
[0391] Therefore, the computing device, is configured to manage the
positioning and re-positioning of sensors for monitoring plant
growth, plant harvesting, plant placement on empty places and,
optionally, the status of the plant growth facility (e.g. for the
maintenance of the equipment used in the plant growth
facility).
[0392] The Controlled Agricultural System can comprise an actuator
device able to adjust growth parameters of plants (e.g. water,
nutrient, light (intensity, spectrum), humidity, temperature, air
ventilation, water circulation, pesticides) and/or to adjust the
position and shape of a light fixture and/or to change the layout
of variable building design parameters of a building or housing or
cabinet of the agricultural facility and/or to close or open the
roof of the agricultural facility (e.g. greenhouse) and/or to
change a location of a moveable agricultural growth cabinet inside
the agricultural facility.
[0393] 11.sup.th aspect of "Measuring Patterns": The Method of any
of the preceding aspects of "Measuring Patterns", particularly for
breeding, growing, cultivating and harvesting in an agricultural
facility, e.g. a plant growing facility, comprising a controlled
agricultural system,
the method comprising the steps of
[0394] Uploading/Entering the layout of the plant growth facility
into a data storage device of the controlled agricultural
system;
[0395] Uploading/Entering data of the sensors into the data storage
device;
[0396] Rendering a digital model of the plant growing facility
(digital facility twin) including indicating the positions of the
sensors by means of the computing device based on the data stored
in the data storage device;
[0397] Positioning the sensors in the real plant growing facility
according to the model.
[0398] First (initial setup), a layout of the plant growth facility
is uploaded to the platform (data storage device) incl. all
relevant dimensions of the facility and growing zones (length,
height, height of traces, distance between rows, amount of rows,
etc.). Additionally, the available amount of sensor types and
amount of different sensors is entered into the controlled
agricultural system, e.g. via a user dashboard. The computing
device of the controlled agricultural system is configured to
generate a 3D model and/or a texture map of the facility, in other
words a digital facility twin, and suggests where to position and
how to orientate the sensors (e.g. horizontally and vertically in
the facility, angle and direction of orientation), based on the
input data.
[0399] 12.sup.th aspect of "Measuring Patterns": The Method of any
of the preceding aspect of "Measuring Patterns", comprising the
step of: [0400] Positioning the sensors in the plant growing
facility according to similar facility setups stored in a data
storage device.
[0401] Furthermore, the computing device may be configured to
suggest, how long to keep the sensors at the respective
places/positions and (if needed/optionally) where to put them for a
2.sup.nd or 3.sup.rd time period to generate a (even more) complete
overview of the facility and microclimate within the facility. The
suggestions may be based on experience with similar facilities or a
calculation how the sensors should be placed on a 3D-grid in the
facility to collect data (based on the (spatial) range of the
specific sensor). A goal may be to leave a respective sensor as
short as possible at a specific location to gather the required
data.
[0402] The computing device (platform) is configured to suggest the
positioning for the sensors based on the farm layout and size. It
is also configured to suggest the minimum requirements of sensor
data acquisition for a given agricultural system so that for each
growth stage and plant maturity the acquired farm data can be
considered representative for the digital facility twin database.
It is preferred to collect the relevant data as fast as possible so
that the farm is "understood and approved" by and for the
controlled agricultural system (i.e. as a first/initial setup).
[0403] 13.sup.th aspect of "Measuring Patterns": The Method of any
of the preceding aspects of "Measuring Patterns", further
comprising the step of including the range of the sensors into the
calculation of the positions of the sensors.
[0404] 14.sup.th aspect of "Measuring Patterns": The Method of any
of the preceding aspects of "Measuring Patterns", further
comprising the steps of
[0405] Measuring and collecting data by means of the sensors;
[0406] Analyzing the measured and collected data and suggesting a
re-positioning of the sensors to improve the measurements by means
of the computing device.
[0407] As mentioned already, this element of the disclosure also
relates to a Controlled Agricultural System:
[0408] 15.sup.th aspect of "Measuring Patterns": A Controlled
Agricultural System configured for performing a method according to
any of the preceding aspects of "Measuring Patterns".
[0409] The controlled agricultural system may be configured to
automatically suggest missing sensors or how additional sensors
could help to accelerate/improve/optimize the growth process. For
example, if an array of humidity sensors, or a single humidity
sensor, is moved over time across an agricultural system, and
detects conditions promoting fungi growth, the system might suggest
deployment of camera-based detectors in order to catch the issue
before it spreads.
[0410] The controlled agricultural system may also be configured to
show tutorials how to correctly install and use the different
sensors. Once the data of a location (of a sensor) is collected,
the system/platform informs the grower and suggests the next
possible sensor location.
[0411] For short or temporary measurements, drones, other mobile
robots (automated agricultural vehicles AGV) or humans may also be
used to create/collect the sensor data.
[0412] When the initial setup is done, i.e. the controlled
agricultural system "understands" the different regions of the
facility, the controlled agricultural system is able to suggest
placing/permanently installing the sensors in relevant/problematic
zones.
[0413] Furthermore, the computing device of the controlled
agricultural system may also be configured to show the locations of
the sensors in a kind of "heat maps" to constantly monitor these
locations. If different seasons are to be considered, seasonal maps
may be relevant/comprised.
[0414] The sensors can also be used to assess the status of the
equipment of the plant growing facility and to plan for maintenance
or crop rotation (bringing the plants in another area of the
facility if the maintenance can affect the yield).
[0415] The Sensors may also be able to change their position during
the growth of the plants (e.g. angle of inclination or height above
ground for positioning). The sensors may also be included in the
earth/ground or in the water. The sensors may also be configured to
provide real-time data about growth--for example growth of fruits
in kg/m.sup.2/day.
[0416] During the execution of the plant-growing project, all
relevant data are acquired and considered/analyzed. For instance,
the controlled agricultural system may establish all relevant
documentation, e.g. in a project report, regarding input factors
used and results achieved, including for example agricultural risk
assessments. Additionally, post-harvest measurements and risk
assessments may be executed and documented as well. The data may be
transferred via software interfaces automatically, e.g. stored on
the platform.
[0417] 16.sup.th aspect of "Measuring Patterns": A computer program
product, comprising:
a plurality of program instructions, which when executed by a
computer system of a Controlled Agricultural System according to
the 15.sup.th aspect of "Measuring Patterns", cause the Controlled
Agricultural System to execute the Method according to any one of
the 1.sup.st to 14.sup.th aspect of "Measuring Patterns".
[0418] 17.sup.th aspect of "Measuring Patterns": An agricultural
facility (plant growing facility, (vertical) farm, greenhouse,
etc.) with at least one Controlled Agricultural System according to
the 15.sup.th aspect of "Measuring Patterns".
[0419] "Light Recipes & Workflow"
[0420] Horticulture facilities like greenhouses and vertical farms
are getting more and more automated. An interesting approach
discussed here is to move the plants through the
horticulture/agricultural facility, namely to transport them
through the facility depending on the specific growth phase.
Therein, different light or growth recipes can be applied in
different zones along the workflow (and thus plant flow). The
recipes can be pre-designed in terms of the respective plant type
and growth phase. Each recipe can define a specific lighting
scenario, e.g. regarding the intensity and spectral composition,
adapted to the growth phase of the plants in the respective zone.
As discussed below, also other parameters, like temperature,
humidity, air flow, etc., can be customized in the different
zones.
[0421] This element of the disclosure is about designing and
operating a plant production line of an agricultural facility, and
it also relates to the production line and facility itself.
[0422] 1.sup.st aspect of "Light Recipes & Workflow": A Method
for designing an agricultural facility for growing plants, the
method comprising the steps of [0423] determining a number N of
different grow scenarios to be applied to the plants in different
growth phases GP.sub.n (n=2 . . . N); [0424] dividing the facility
into N zones Z.sub.n; [0425] assigning to each of the N zones an
area A.sub.n; wherein a sum, derived from summing up all areas
A.sub.n, is smaller than or equal to a total growth area available
in the agricultural facility (.SIGMA.A.sub.n<total growth
area);
[0426] and wherein, for at least some of the areas A.sub.n, the
size of the areas A.sub.n is increasing with increasing number n
(A.sub.n<A.sub.n+1).
[0427] Therein, n is an integral number, and N is greater than 1
(i.e. N=2, 3, 4 or 5); upper limits can for instance be N=50, 40,
30, 20 or 10. The growth of the plants proceeds with increasing
number n, so that GP.sub.n+1 is the growth phase subsequent to the
growth phase GP.sub.n (which applies for all values of n from 1 to
N). In operation, the plants can be moved through the facility from
zone to zone, namely from Z.sub.n to Z.sub.n+1, see in detail
below.
[0428] The grow scenarios can in particular be derived from a
growth recipe. These can for instance be or comprise lighting
scenarios. In each zone, for instance light fixtures can be adapted
to emit light with a spectral composition required by the plants in
the actual growth phase. Therein, the light fixtures can be fixed
or pre-defined in their respective spectral properties, which can
give a cost benefit in comparison to providing light fixtures with
adaptable spectral properties, even though a conveyer mechanism or
the like is may be required for transporting the plants.
Alternatively or in addition to providing specifically adapted
light fixtures in the different zones, other actuators for
adjusting other environmental conditions (temperature . . . ) can
be provided and adapted to the specific zone.
[0429] 2.sup.nd aspect of "Light Recipes & Workflow": The
Method according to the 1.sup.st aspect of "Light Recipes &
Workflow", wherein, for some of the areas A.sub.n, the size of the
areas A.sub.n remains unchanged with increasing number n
(A.sub.n=A.sub.n+1).
[0430] Typical growth phases can for instance be germination,
growth and maturation. Depending on the specific plant type, there
may be growth phases in which the size of the plants remains
unchanged. Accordingly, some of the zones Z.sub.n can have the same
area A.sub.n. For instance, in case that the size of the plants
remains basically unchanged during maturation, the zones for
maturation and growth can have the same size. On the other hand,
providing different zones while the size remains unchanged can be
advantageous, as for instance growth and maturation may require a
different illumination.
[0431] 3.sup.rd aspect of "Light Recipes & Workflow": The
Method according to the 1.sup.st or 2.sup.nd aspect of "Light
Recipes & Workflow", wherein the zones Z.sub.n are arranged in
the facility in such a way, that a length of a production line
connecting the different zones Z.sub.n is minimized.
[0432] This optimization can be done for instance numerically,
comparable to solving a "Travelling salesman problem". Apart from
minimizing the length of the production line, other boundary
conditions can be the accessibility of the plants in the different
growth phases, in particular after maturation/fructification.
Further, when arranging the zones in the farm, not only the size
but also the shape of the building can be taken into account.
[0433] 4.sup.th aspect of "Light Recipes & Workflow": The
Method according to the any of the preceding aspects of "Light
Recipes & Workflow", wherein the area A.sub.n of a respective
zone Z.sub.n is determined depending on a space factor, namely the
space assigned to a plant in the specific growth phase
GP.sub.n.
[0434] The larger the space factor (the more space assigned to a
plant), the larger A.sub.n.
[0435] 5.sup.th aspect of "Light Recipes & Workflow": The
Method according to the any of the preceding aspects of "Light
Recipes & Workflow", wherein the area A.sub.n of a respective
zone Z.sub.n is determined depending on a time factor, namely the
time a plant is kept in the specific zone Z.sub.n.
[0436] The larger the time factor, namely the longer the plant is
kept in the specific zone Z.sub.n, the larger A.sub.n.
[0437] The method described here can be in particular a computer
implemented method. It can for instance be a program part of a
light recipe design tool (LRDT) software program.
[0438] 6.sup.th aspect of "Light Recipes & Workflow": A
Controlled Agricultural System, particularly for breeding, growing,
cultivating and harvesting in an agricultural facility,
particularly a plant growing facility and/or an hydroponics
facility, comprising:
an actuator device for moving plants along a plant production line
according to a workflow, the plant production line being grouped
into a number of N zones Z.sub.n(Z.sub.1 . . . Z.sub.N), wherein N
is an integral number greater than 1 (i.e. 2, 3, 4, . . . ); a
number of N groups of agricultural light fixtures, the agricultural
light fixtures of each one of the groups being arranged to
illuminate a dedicated zone, respectively (i.e. group 1 illuminates
zone 1, group 2 illuminates zone 2, etc.); a data storage device
(e.g. platform/cloud) for storing data comprising the agricultural
light fixtures, light recipes for the plants and the workflow, a
computing device, configured to control the agricultural facility
by means of the actuator device and agricultural light fixtures
according to the workflow.
[0439] 7.sup.th aspect of "Light Recipes & Workflow": The
Controlled Agricultural System of the 6.sup.th aspect of "Light
Recipes & Workflow", the Agricultural System being designed in
a Method according to any of the 1.sup.st to 5.sup.th aspect of
"Light Recipes & Workflow".
[0440] 8.sup.th aspect of "Light Recipes & Workflow": The
Controlled Agricultural System of the 6.sup.th or 7.sup.th aspect
of "Light Recipes & Workflow", wherein the light fixtures have
a specific, fixed spectrum.
[0441] 9.sup.th aspect of "Light Recipes & Workflow": The
Controlled Agricultural System of any of the 6.sup.th to 8.sup.th
aspect of "Light Recipes & Workflow", wherein the light
fixtures have a specific, fixed intensity.
[0442] Further, also other photometric values (see above), which
are deployed at various stages of the workflow (growth phases), can
be fixed. For example, a horticulture light fixture may be deployed
at the beginning of the production/workflow configured to provide a
specific light spectrum, e.g. for the initial growth phase of the
respective plant species. Along the workflow (in different zones of
the facility), horticulture light fixtures with other specific,
fixed spectra and intensities may be deployed (according to the
needs of the plants in subsequent growth phases). With this
approach, maximum use of the functionalities of and investment in
the agricultural/horticultural facility is ensured. The various
fixed spectra may be selected based on plant need, environmental
conditions and other requirements (user demands, Bio-mass to be
produced, time to harvest, etc.).
[0443] An agricultural/horticultural light fixture that offers a
fixed spectrum may include means for dimming the spectral
intensity. In addition, the geometrical layout of an agricultural
light fixture and beam spread are important features. All these
features of those light fixtures may be stored in a database
(local, cloud) available to users via a platform. The distance
between light fixtures and plants (canopy) may also be taken into
consideration for a suited agricultural/horticultural facility
layout/setup.
[0444] The controlled agricultural system according to this element
of the disclosure further comprises a computing device, which may
be based locally (on-site) or in a (centralized) network or the
cloud. The computing device may be configured to be able to run the
LRDT software program. The computing device may also have access to
the database containing data about the features of the agricultural
light fixtures of the controlled agricultural system.
[0445] 10.sup.th aspect of "Light Recipes & Workflow": The
Controlled Agricultural System according to any of 6.sup.th to
9.sup.th aspect of "Light Recipes & Workflow", wherein the
actuator device further comprises actuators able to adjust growth
parameters of the plants, e.g. water, nutrients, light (intensity,
spectrum), humidity, temperature, air ventilation, water
circulation, pesticides.
[0446] 11.sup.th aspect of "Light Recipes & Workflow": The
Controlled Agricultural System of any of the 6.sup.th to 10.sup.th
aspect of "Light Recipes & Workflow", the Agricultural System
being configured to provide, in addition to the illumination with
the light fixtures, in at least one of the Zones Z.sub.n a defined
temperature, humidity and/or CO.sub.2 level.
[0447] The computing device may be configured to control the
agricultural facility by means of the actuators, light fixtures,
etc., according to the workflow.
[0448] 12.sup.th aspect of "Light Recipes & Workflow": The
Controlled Agricultural System according any of the 6.sup.th to
11.sup.th aspect of "Light Recipes & Workflow", further
comprising a sensor device able to measure distinctive
characteristics of the plants, particularly for detecting the
growth status of the plants.
[0449] The sensors may sense the growth status/growth phase of the
plants as well as a health status of the plants. Health checkpoints
along the flow paths can be planned/suggested by the LDRT and
implemented into the horticultural plant layout and function.
[0450] 13.sup.th aspect of "Light Recipes & Workflow": The
Controlled Agricultural System according to any one of the 6.sup.th
to 12.sup.th aspect of "Light Recipes & Workflow", wherein the
computing device is further configured to trigger the next step of
the workflow and/or synchronize the workflow with the growth status
of the plants.
[0451] 14.sup.th aspect of "Light Recipes & Workflow": The
Controlled Agricultural System according to any one of the 6.sup.th
to 13.sup.th aspect of "Light Recipes & Workflow", further
configured to track and/or monitor the plants during the workflow,
e.g. by using a distributed Blockchain ledger method.
[0452] The entire through-put cycle of a specific plant can be
monitored and correlated with this specific plant, for example by
using a distributed Blockchain ledger method thus allowing that the
entire treatment cycle of each (individual) plant as well as the
plant's health condition is documented accurately and
permanently.
[0453] 15.sup.th aspect of "Light Recipes & Workflow": The
Controlled Agricultural System according to any one of the 6.sup.th
to 14.sup.th aspect of "Light Recipes & Workflow", wherein the
data storage device further comprises data about the agricultural
facility including its equipment (e.g. layout, size, placement of
light fixtures, actuators, sensors, etc.) and growth recipes for
the plants.
[0454] To facilitate this approach, the present element of the
disclosure further proposes a Light Recipe Design Tool (LRDT),
which is a software program with executable program steps. In the
LRDT, the facility layout and the workflow are inserted (per upload
of layouts or pictures, grouping of zones/production stages, insert
of dwell (delay or rest)) times, etc.). Furthermore, user demand
(bio-mass), post-harvesting treatment, environmental conditions,
can be factored in. The LRDT is connected to a database of light
recipes for a variety of plants, growth stages, dwell times,
On-Off-cycle, and the like, including the light fixture-related and
light fixture-plant related data sets (see above).
[0455] 16.sup.th aspect of "Light Recipes & Workflow": A method
for agricultural management, particularly for breeding, growing,
cultivating and harvesting in an agricultural facility, e.g. a
plant growing facility, comprising:
at least one controlled agricultural system according to one or
more of the 6.sup.th to 15.sup.th aspect of "Light Recipes &
Workflow", and the steps of Uploading the layout of the
agricultural facility and the workflow into the data storage
device; Entering data of user demand (e.g. plant species) into the
data storage device; Fetching a light recipe appropriate for the
user demand, including the light fixture-related and light
fixture-plant-related data sets from the database stored on the
data storage device; Rendering a light recipe design (LRD) by
proposing a setup of the facility including its equipment (light
fixtures, actuators, sensors, etc.), which setup is adapted to the
fetched light recipe and the workflow, by means of the computing
device based on the data of the previous steps.
[0456] The LRDT is configured to develop a light recipe design
(LRD) for the entire plant treatment time for the grower's
facility. This means the LRDT is configured to take into account
the size of the facility, the size of the plants in each growth
stage (growth phase), the time the plants remain in each grow
stage, the number of grow stages and the like (see above). Based on
this, the LRDT proposes a setup for the facility, indicating the
space required for each grow stage, where to put light fixtures and
which types of light fixtures including the respective
configuration (spectrum, intensity). It also defines the
appropriate velocity (or stand-still time) of plants that may move
on a track or conveyor belt from one position to another. It also
defines the appropriate horticultural fixture design, layout,
placement of attached or connected optical components (like lenses,
reflectors, light guides), cooling conditions, airflow and the
like, distance to the plant canopy, as well as any inclination of
the light fixture.
[0457] 17.sup.th aspect of "Light Recipes & Workflow": The
method for agricultural management according to the 16.sup.th
aspect of "Light Recipes & Workflow", further comprising the
steps of
Implementing the light recipe design (LRD) in the facility;
Controlling the workflow in the facility by means of the actuator
device and the computing device based on the LRD.
[0458] The LRD may be uploaded to the grower's horticulture
Internet of Things (IoT) platform. The horticulture IoT platform
may be configured to do real-time asset tracking to monitor the
plant movement along the workflow and match it to the LRD and give
feedback to the grower if it matches or if something needs to be
adjusted to the LRD. Adjustment to the workflow could be for
example slowing down/speeding up the process time at a growth
stage. Asset tracking may be done for example by sensors and radio
frequency (RF), RFID or barcode and QR-code scanning of plant trays
or plant pots during the production/workflow.
[0459] 18.sup.th aspect of "Light Recipes & Workflow": The
method for agricultural management according to the 17.sup.th
aspect of "Light Recipes & Workflow", wherein the step of
controlling the workflow further comprises the sub-steps of
Moving the plants along the direction of the workflow and across
the zones (Z1; Z2; Z3) of the plant production line; Controlling
the light fixtures according to the light recipe design (LRD), i.e.
according to a setup of the facility including its equipment (light
fixtures, actuators, sensors, etc.), which setup is adapted to the
fetched light recipe and the workflow.
[0460] 19.sup.th aspect of "Light Recipes & Workflow": The
method for agricultural management according to the 18.sup.th
aspect of "Light Recipes & Workflow", whereby moving of the
plants is conducted in order to cross each zone (Z1; Z2; Z3)
according to a pre-defined schedule.
[0461] 20.sup.th aspect of "Light Recipes & Workflow": The
method for agricultural management according to any one of the
16.sup.th to 19.sup.th aspect of "Light Recipes & Workflow",
further comprising the steps of
Measuring and collecting data by means of the sensor device,
comprising data for detecting the growth status of the plants, and
adapting the timing for moving the plants to the detected status of
the plants.
[0462] 21.sup.th aspect of "Light Recipes & Workflow": A
computer program product, comprising:
[0463] a plurality of program instructions, which when executed by
a computer system of a Controlled Agricultural System according to
any one of the 6.sup.th to 15.sup.th aspect of "Light Recipes &
Workflow", cause the Controlled Agricultural System to execute the
method for Agricultural Management according to any one of the
16.sup.th to 20.sup.th aspect of "Light Recipes &
Workflow".
[0464] The LRDT software program may be configured to improve
itself based on feedback (customer, produces) by executing Deep
Learning or AI methods. The LRDT software program may be licensed
to other parties.
[0465] 22.sup.th aspect of "Light Recipes & Workflow": An
agricultural facility (plant growing facility, (vertical) farm,
greenhouse, etc.) with at least one Controlled Agricultural System
according to any one of the 6.sup.th to 15.sup.th aspect of "Light
Recipes & Workflow".
[0466] Though a horticultural plant facility can have many flow
paths, it is preferred to keep it as simple as possible, e.g.
following a straight line through the horticultural plant facility
(see FIG. 19). Plant factories can have a larger number of plant
rows and paths, probably many hundred. Flow paths can be stacked
upon each other in vertical layers thus providing a 3D path system.
In principle, the flow paths could reverse their direction so that
the plants move again through a previous light setting (but in
opposite direction).
[0467] Plant Health/Growth
[0468] "Prophylaxis"
[0469] According to the element "Prophylaxis" of the disclosure, a
controlled agricultural system and a method for agriculture for
prevention of diseases and pests or for fighting same is
proposed.
[0470] To this end, abiotic and biotic environmental parameters are
monitored and, if need be, appropriate measures are proposed or,
alternatively, introduced automatically.
[0471] 1.sup.st aspect of "Prophylaxis": More specifically, a
controlled agricultural system, comprises a first sensor device for
acquiring data in relation to environmental parameters
(environmental data), a data storage device for storing the data
from the first sensor device and a computing device configured to
analyze the data of the data storage device in order to identify
critical situations and propose suitable countermeasures where
applicable.
[0472] Parts of the controlled agricultural system, for example the
computing device or the data storage device may be based locally or
else on a network or cloud.
[0473] The term environment in this case comprises the greenhouse
per se and the region outside of the greenhouse.
[0474] The environmental parameters, i.e., the effective factors,
include data (environmental data) such as temperature, wind speed,
humidity, light factor, ozone content of the air, UV radiation, but
also season or amount of pollen or number of insects in the air. It
is likewise possible to monitor the temperature at the leaves of
the plant. If the temperature there falls below the dew point,
there is then an increased risk of fungi afflicting the plants. As
to appropriate measures against such risk, see also the element
"Fungi Growth Inhibition" of the group "Plant Health & Growth"
of the disclosure.
[0475] Therefore, the controlled agricultural system is equipped
with sensors that are able to acquire the aforementioned abiotic
and biotic environmental parameters at adjustable time intervals or
else continuously.
[0476] 2.sup.nd aspect of "Prophylaxis": Alternatively, a
controlled agricultural system comprises a first sensor device for
acquiring data in relation to environmental parameters
(environmental data), an actuator device, a data storage device for
storing the data from the first sensor device and a computing
device configured to analyze the data of the data storage device in
order to identify critical situations and introduce suitable
countermeasures with the aid of the actuator device where
applicable.
[0477] Countermeasures could be: [0478] Start automated
illumination with specific light treatment (UV) [0479] Start
automated spraying of pesticides [0480] Inform the operator to have
a check and show the affected or suspicious location [0481] Adjust
watering, ventilation, etc.
[0482] Further countermeasures could be (the controlled
agricultural system may be configured to start them automatically
or inform the grower and leave the choice to him): [0483] Low
acidity.fwdarw.add an acid to the nutrient solution [0484] High
acidity.fwdarw.add a base to the nutrient solution [0485] Low
nutrients.fwdarw.add macro and micro elements or ready to use
fertilizer to nutrient solution [0486] Temperature too
low.fwdarw.tell heat system to adjust it, close or open windows
[0487] Too dark/bright.fwdarw.open screen/close screen, dim up/dim
down light [0488] Aphids found.fwdarw.add imidacloprid (or any
other insecticide) to nutrient solution [0489] Mildew
found.fwdarw.change light to a UV enriched spectrum/add fungicide
to automated sprayer, adjust humidity and temperature to
optimum.
[0490] The controlled agricultural system may also be configured to
just giving notifications/recommendations in the beginning or wait
for confirmation by the operator before executing the recommended
countermeasures. For instance, the system may recommend a
countermeasure like "In the current situation, grower XYZ
implemented this or that countermeasure with the effect of ABC. Do
you want to execute?" Alternatively or in an advanced stage of the
project the system may be configured to decide and implement
countermeasures autonomously.
[0491] The measure using pesticides should be execute as described
in the user manuals. The user manuals of seed-, substrate-,
fertilizer-, pesticide- and equipment companies should be stored
and continuously updated in the system.
[0492] The countermeasures should also take into account the
expected yield/harvesting time (and acceptable reductions or
delays). Afterwards the system can give suggestions how often we
increase the light intensity, or change the spectrum.
[0493] Sometimes it may also makes sense to delay a measure, e.g.
before opening and closing the sunscreen to take account for small
clouds in the sky.
[0494] All countermeasures may be documented by the agricultural
system.
[0495] 3.sup.rd aspect of "Prophylaxis": The controlled
agricultural system according to the 1.sup.st or 2.sup.nd aspect of
"Prophylaxis", comprising a second sensor device for acquiring data
in relation to the state of the plants (plant data), wherein the
data storage device is configured to store the data from the second
sensor device.
[0496] Specifically, the controlled agricultural system is equipped
with sensors that are able to acquire the state of the plants, in
some embodiments/implementations the stress state thereof.
[0497] By way of example, these may be optical, chemical or
electrical sensors, which identify, for example, the growth of the
plants (density of the leaves, height of the plants, plant
morphology, leaf area index), measure the color and reflectivity of
the leaves, the thermo-luminescence thereof or the chlorophyll
fluorescence thereof or the abscisic acid (ABA) luminescence
thereof and hence the health of the plants and in particular the
stress state thereof, and are able to supply these (plant data) to
an evaluation.
[0498] Furthermore, the controlled agricultural system is
configured to measure the recovery state, i.e., the reduction of
stress parameters, of the plants. These information items are
stored, in some embodiments/implementations in a plant-specific
manner, in a data storage device and are analyzed by a computing
device.
[0499] If a disease has been detected, the computing device of the
controlled agricultural system regularly checks the sensors that
detected the disease to monitor the development of the disease. If
no improvement of the situation can be observed after a certain
time period has passed, a warning is issued. If the situation
improves, the countermeasures are modified accordingly, e.g. the
amount of insecticide may be reduced.
[0500] 4.sup.th aspect of "Prophylaxis": The controlled
agricultural system according to the 3.sup.rd aspect of
"Prophylaxis", wherein the computing device is configured to
analyze the data of the data storage device, to identify negative
effects on the plants in the process and reduce or stop the
countermeasures should negative effects on the plants be
identified.
[0501] The analysis can be performed using methods connected to
artificial intelligence (AI), such as deep learning. The goal of
the analysis is to identify and/or predict an environmental
situation that is accompanied by an increased occurrence of
diseases or pest infestation. The analysis may also include the
plant state, for example the degree of maturity. This is because,
as a rule, the risk of pest infestation also increases with
advancing degree of maturity.
[0502] Additionally, situations in which pests such as fungi thrive
may arise (particularly indoors) from the growth recipes with
variable temperatures and degrees of humidity thereof. These
situations may likewise be identified.
[0503] If such a situation is identified, the operator of the
greenhouse can then be informed so as to introduce measures that
prevent or reduce an outbreak of the disease or which prevent pests
from entering the greenhouse.
[0504] However, the system may also be able to take up these
measures in preventative fashion, with care having to be taken that
the plants are not adversely affected, or not adversely affected
too much, by the measures. Thus, there is a trade-off between
potential use and possible damage by the measure. This is weighted
with the probability of the occurrence of the disease or the pests
and the probability of damage by the measure, and hence a decision
is made as to whether or to what extent, the measure is carried
out.
[0505] 5.sup.th aspect of "Prophylaxis": The controlled
agricultural system according to any one of the 1.sup.st to
4.sup.th aspect of "Prophylaxis", wherein the first sensor device
comprises one or more sensors for one of the following
environmental parameters or a combination thereof: air composition,
air temperature, air humidity, wind speed, light intensity, light
spectrum, number of pests, light factor, ozone content of the air,
UV radiation.
[0506] 6.sup.th aspect of "Prophylaxis": The controlled
agricultural system according to any one of the 1.sup.st to
5.sup.th aspect of "Prophylaxis", wherein the second sensor device
comprises one of the following sensors or a combination thereof:
temperature sensor, gas analyzer, photodiode, spectrometer,
camera.
[0507] 7.sup.th aspect of "Prophylaxis": The controlled
agricultural system according to any one of the 1.sup.st to
6.sup.th aspect of "Prophylaxis", wherein the actuator device
comprises one or more of the following actuators or a combination
thereof: plant light fixture with various light sources, UV
radiation source, applicator for pesticides, applicator for
herbicides, applicator for fungicides, applicator for useful
creatures, mobile robot unit, drone, heater or cooler,
ventilator.
[0508] Measures may include the irradiation with UV (or generally a
change in the light recipe), the closing of windows and doors, the
reduction of the humidity or the temperature, or else the automatic
release of useful creatures or the automatic application of
correspondingly licensed pesticides by means of a mobile robot
unit, etc.
[0509] Placing UV-reflecting mats below the plants may be a passive
measure for reducing the infestation of pests. Thus, pests can no
longer distinguish leaves from the ground, and so they settle less
frequently on the plants.
[0510] Effects on the plants can be monitored by controlling the
plant stress (but also by checking the growth with cameras, etc.).
If need be, preventative measures may be terminated if the stress
on the plants becomes too large. At the same time, environmental
parameters are checked regularly to see when the risk of an
outbreak of disease or infestation of pests has abated.
[0511] 8.sup.th aspect of "Prophylaxis": A method for agricultural
management, comprising the following method steps: measuring
relevant environmental parameters in a target area, analyzing the
measurement data and identifying critical situations such as
environmental conditions that are inexpedient for plants, for
example, with an (elevated) risk of the plants being afflicted by
disease or infested by pests or whether the plants are already
afflicted by disease or infested by pests, proposing, or
alternatively automatically introducing, countermeasures.
[0512] 9.sup.th aspect of "Prophylaxis": The method for
agricultural management according to the 8.sup.th aspect of
"Prophylaxis", comprising the following additional steps: a)
acquiring data in relation to the state of the plants and checking
whether the countermeasures have a (negative) effect on the plants,
b) reducing or stopping the countermeasures if the countermeasures
have a (negative) effect on the plants, c) re-measuring relevant
environmental parameters in the target area and checking whether a
critical situation still is present if the countermeasures do not
have a (negative) effect on the plants, d) stopping the
countermeasures if the situation is no longer critical, e)
continuing the countermeasures if the situation still is critical
and continuing with step c).
[0513] 10.sup.th aspect of "Prophylaxis": The method for
agricultural management according to the 8.sup.th or 9.sup.th
aspect of "Prophylaxis", carried out by a controlled agricultural
system according to any one of the 1.sup.st to 7.sup.th aspect of
"Prophylaxis".
[0514] The method enables to identify critical situations such as
environmental conditions that are inexpedient for plants, and
optionally taking countermeasures. Furthermore, reference is made
to the description above, the features described there shall also
be disclosed in terms of the method.
[0515] 11.sup.th aspect of "Prophylaxis": A machine-readable
computer product, comprising a multiplicity of program instructions
which, when executed on the computing device of the controlled
agricultural system according to any one of the 1.sup.st to
7.sup.th aspect of "Prophylaxis", cause the Controlled Agricultural
System to execute the method according to the 8.sup.th or 9.sup.th
aspect of "Prophylaxis".
[0516] "Stress Detection"
[0517] According to the element "Stress Detection" of the
disclosure, pests, diseases and stress of plants are detected based
on leaf characteristics by means of sensors.
[0518] 1.sup.st aspect of "Stress Detection": More specifically, a
controlled agricultural system, comprises a sensor device able to
measure distinctive characteristics of plants (measured data of
plants), a data storage device for storing reference data of
plants, and a computing device, configured to compare the data
measured by the sensor device with the respective reference data
stored on the data storage device and to identify stress, diseases,
pests or any other critical condition of the plants from the result
of the comparison.
[0519] Furthermore, the controlled agricultural system comprises a
computing unit configured to identify stress or disease from the
data measured by the sensors. For instance, if the computing unit
detects morphological changes of the leaves, the controlled
agricultural system delivers a warning to the user (farmer).
[0520] 2.sup.nd aspect of "Stress Detection": The controlled
agricultural system according to the 1.sup.st aspect of "Stress
Detection", further comprising a user interface for delivering the
result of the comparison and/or identification to the user.
[0521] To this end, the controlled agricultural system comprises
sensors, which are able to measure distinctive characteristics of
plants, e.g. color changes of the leaves by means of optical
sensors (e.g. sensors for spectral measurements), plant morphology
by means of a camera, etc.
[0522] In an exemplary embodiment, a camera is configured to take
pictures of the leaves in regular intervals (e.g. minutes, hours,
days). The pictures are then compared to earlier pictures or
pictures of a healthy plant. "Earlier pictures" can mean that one
or a sample of earlier pictures have been taken for the purpose of
later comparison or that an average of the earlier pictures has
been calculated with respect to the respective parameters like
inclination, leaf-size, roll-up, etc.
[0523] A stress situation can be detected, if the picture analysis
shows a difference in certain morphology parameters which are
larger than a certain threshold, for instance: [0524] certain
inclination of the leaf (e.g. the leaf in inclined downwards,
although it shows upwards for healthy plants), [0525] a roll-up of
the leaf (i.e. the tip of the leave moves upwards), [0526] curling
of leaves (i.e. the edges of the leaf move towards each other like
folding the leaf longitudinally), [0527] an unsymmetrical
leaf-size, i.e. one side of the leaf is smaller e.g. by at least 10
percent than the second side, or the size has been reduced by a
certain amount (e.g. 10 percent) compared to earlier pictures,
[0528] deformation due to an infection by aphids or other
insects.
[0529] 3.sup.rd aspect of "Stress Detection": The controlled
agricultural system according to the 1.sup.st or 2.sup.nd aspect of
"Stress Detection", further comprising an actuator device.
[0530] 4.sup.th aspect of "Stress Detection": The controlled
agricultural system according to the 3.sup.rd aspect of "Stress
Detection", wherein the actuator device comprises one or more of
the following actuators or a combination thereof: agricultural
lighting device, radiation source able to emit ultraviolet (UV)
radiation, irrigation system, ventilation system, heating/cooling
system, feeder for dosing fertilizer and/or pesticides.
[0531] If the morphological change is due to a certain root cause
(e.g. not enough water), the system may optionally initiate a
counter-measure (e.g. irrigation). For this purpose, the controlled
agricultural system further comprises respective actuators (e.g.
irrigation system).
[0532] 5.sup.th aspect of "Stress Detection": The controlled
agricultural system according to the 3.sup.rd or 4.sup.th aspect of
"Stress Detection", wherein the computing device is configured to
automatically counteract by means of the actuator device, if
stress, diseases, pests or any other critical condition is
identified.
[0533] For identifying stress or disease, the pictures currently
taken may be compared with existing reference pictures of
corresponding plants in good health and condition retrieved from a
database. The database is stored in a data storage device that may
be based locally, in a network or the cloud. The identification
process may be performed by using picture recognition algorithms,
e.g. deep learning. By using data of other sensors (environmental
sensors, chemical sensors), the different morphological changes can
be linked to other causes (e.g. hanging leafs due to not enough
water or due to other environmental parameters such as a too high
salt concentration). These causes may also depend on the specific
kind of plant, which may also be taken into consideration when
analyzing the pictures. Artificial Intelligence programs may be
used to monitor, collect and interpret such sensor generated data
and calculate forecast or prediction models in order identify and
reduce plant stress.
[0534] 6.sup.th aspect of "Stress Detection": The controlled
agricultural system according to any one of the 1.sup.st to
5.sup.th aspect of "Stress Detection", wherein the sensor device
comprises one or more of the following sensors or a combination
thereof: imaging system, e.g. still or video camera, in some
embodiments/implementations TOF camera or stereo camera, LIDAR
system, environmental sensor, e.g. for measuring temperature,
humidity and/or chemical composition of the air or soil, sensors
for detecting color changes of the plant, particularly of the
leaves, sensors for detecting specific gases exhaled by the plants,
sensors for detecting the fluorescence emitted by the plants after
activation with dedicated radiation.
[0535] In a preferred embodiment, the measurement system is capable
to create a 3D-representation of the leaves (e.g. by using time of
flight (TOF-) cameras, stereo cameras, or LIDAR (light detection
and ranging)). If the picture is only available in two dimensions,
the angle of inclination or the symmetry of the leaf might be
misinterpreted, as the cameras cannot look perpendicularly on each
leaf. A 3D-representation helps to avoid this mistake.
[0536] In a similar way, root morphology (e.g. in hydroponics
systems) can be measured and analyzed with regard to pests or
diseases.
[0537] Furthermore, a method for agricultural management detects
pests, diseases and stress of plants based on leaf characteristics
as described above.
[0538] 7.sup.th aspect of "Stress Detection": A method for
agricultural management, comprising at least one controlled
agricultural system as described above and the following method
steps: measuring distinctive characteristics of plants in a target
area by means of the sensor device and collecting these measured
data of the plants, storing reference data of plants, comparing the
measured data with the reference data by means of the computing
device and identifying stress, diseases, pests or any other
critical condition of the plants from the result of the comparison
by means of the computing device.
[0539] 8.sup.th aspect of "Stress Detection": The method for
agricultural management according to the 7.sup.th aspect of "Stress
Detection", further comprising the step of delivering the result of
the comparison and/or identification to the user by means of the
user interface.
[0540] 9.sup.th aspect of "Stress Detection": The method for
agricultural management according to the 7.sup.th or 8.sup.th
aspect of "Stress Detection", further comprising the step of
counteracting automatically by means of the actuator device, if
stress, diseases, pests or any other critical condition of the
plants is identified.
[0541] 10.sup.th aspect of "Stress Detection": The method for
agricultural management according to any one of the 7.sup.th to
9.sup.th aspect of "Stress Detection", further comprising the step
of establishing reference conditions before measuring distinctive
characteristics of the plants in the target area, in some
embodiments/implementations establishing reference lighting of the
plants in the target area.
[0542] In addition, to gain consistent results the measurement
should be conducted under standardized conditions, as different
illumination (color or intensity) may affect the leaf morphology as
well. In addition, different measurement conditions, e.g. colors of
the luminaires, might lead to different measurement results. On the
other hand, well-defined changes of illumination parameters can be
used to analyze the plant stress, as it might induce changes in the
leaves. This change, especially the reaction time for a respective
change, can be measured and the measurement result may provide an
indication about the stress.
[0543] 11.sup.th aspect of "Stress Detection": A machine-readable
computer product, comprising a multiplicity of program instructions
which, when executed on the computing device of the controlled
agricultural system according to the 1.sup.st to 6.sup.th aspect of
"Stress Detection" causes the controlled agricultural system to
execute the method according to any of the 7.sup.th to 10.sup.th
aspect of "Stress Detection".
[0544] "Discolored Spots Detection"
[0545] According to the element "Discolored Spots Detection" of the
disclosure, diseases and stress of plants are detected based on the
detection of discoloration by means of complementary illumination.
Additionally, complementary illumination may be used to identify
colors or color changes, for example, due to ripening.
[0546] 1.sup.st aspect of "Discolored Spots Detection": A
controlled agricultural system, particularly for detection of plant
diseases and various stages of ripening, comprising a data storage
device comprising data, which are related to spectra of light,
particularly of light with colors complementary to colors of parts
of plants (Complementary Color Spectrum CCS), for example,
complementary to discolored areas or parts of plants, an
illumination device able to emit light with a color spectrum
according to the data stored in the data storage device and
illuminate plants, a sensor device able to detect the light
reflected by the illuminated plants, and a computing device,
configured to control the illumination device based on the data of
the database, and further configured to analyze the data from the
sensor device and detect dark areas on the plants.
[0547] 2.sup.nd aspect of "Discolored Spots Detection": A
controlled agricultural system, particularly for detection of plant
diseases and various stages of ripening, comprising an illumination
device able to emit light, perform a spectral light scan,
comprising Complementary Color Spectra, particularly with regard to
discoloration of plants or plant parts, and illuminate plants a
sensor device able to detect the light reflected by the illuminated
plants, a computing device, configured to control the illumination
device for performing a spectral light scan, and further configured
to analyze the data from the sensor device and detect dark areas on
the plants.
[0548] For instance, various Discolored Spots (DSi) are illuminated
with light with Complementary Color Spectra (CCSi). If all
Discolored Spots (DSi) show the same discoloration, they may be
illuminated with the same Complementary Color Spectra (CCSi). If
the Discolored Spots (DSi) show different discolorations, they may
be illuminated with different Complementary Color Spectra (CCSi),
corresponding to the different discolorations.
[0549] The detection of discoloration may be used for various tasks
of cultivating plants. For instance, it may be used to track
changes in plants or part of the plants, e.g. flowering, changing
colors due to ripening etc. In this case, the complementary color
of the state of the plant is applied (either the previous state to
see if it is still there or the expected state to see if it has
been realized). For example, to verify if the color of the tomatoes
have already changed from green to red, the tomatoes may be
illuminated with light of the color complemental to green (i.e.
reddish light (magenta)). If such illuminated tomatoes appear dark,
their color is still green. Otherwise, they have already changed
their color to red and may be ready for harvesting. Alternatively,
the tomatoes may be illuminated with light of the color
complemental to red (i.e. cyan). If the illuminated tomatoes appear
dark, their color is already red. Otherwise, their color is still
green.
[0550] In the following, the disclosure will be described in more
detail for the example of detecting diseases, where plants show
discolored spots. However, the method steps and features may as
well be used for other tasks of breeding, cultivating and/or
harvesting plants, such as, inter alia, the examples described
above.
[0551] A discolored spot, in the following designated Discolored
Spot DSi, where i is the index of the spot of the plant, comprising
stem, petals, etc. (i=1 to N, wherein N is the total number of
spots of the respective plant) shows, when lit with white light
(e.g. a white light source with a reference light spectrum that
shows a good Color Rendering Index CRI (in some
embodiments/implementations higher than 90), or a standardized
light source with a specific reference light spectrum) a reflection
light (light remission) with a color/spectrum that is different
from the reflection light of a non-discolored plant area or
spot.
[0552] Specifically, any Discolored Spot DSi does not reflect light
with a complementary spectrum (called: Complementary Color Spectrum
CCSi) This means that e.g. a yellow spot on a leaf does not (or
only minimally) reflect blue light. It is preferred that the
spectral Full Width at Half Maximum (FWHM) of the complementary
spectrum is rather narrow, in some embodiments/implementations in
the range between 1 nm, and 50 nm.
[0553] The current (local) color of a discolored spot DSi is termed
Discoloration Color DCi. A plant can have several (local)
Discoloration Colors DC1, DC2 . . . DCN., one Discoloration Color
DCi for each Discolored Spot (DSi).
[0554] The Complementary Color Spectrum CCSi of each of the
respective Discolored Spots DSi are provided by a Complementary
Light Source CLSi. A horticulture light fixture may comprise
several Complementary Light Sources CLSi.
[0555] It may be preferred that the illumination system (e.g.
horticulture light fixture) emits only one Complementary Color
Spectrum CCSi at a given time thus making it easier for sensor
systems to differentiate between various reflected light colors.
However, it may also be preferred to simultaneously apply radiation
(light) with two or more Complementary Color Spectra CCSi to the
plants. Then a detecting camera system needs to comprise color
separation filters or other means of differentiating the various
Complementary Color Spectrum CCSi.
[0556] 3.sup.rd aspect of "Discolored Spots Detection": A
controlled agricultural system, according to the 1.sup.st or
2.sup.nd aspect of "Discolored Spots Detection", wherein the
illumination device comprises light sources, which are able to emit
light of at least three different colors, in some
embodiments/implementations red, green and blue.
[0557] In a preferred embodiment, the illumination unit comprises
at least three light colors, e.g. red, green and blue for the RGB
color-space. Such illumination units are more and more frequently
used in agricultural systems for illumination purposes, but the
illumination unit to detect the discolored spots/disease may also
be added as an independent light source. For example, the
illumination unit may be arranged in the agricultural lighting
system or a separate fixed installation, or in a moveable
installation, e.g. on tracks or in in automated guided vehicle
(AGV) or even inside a flying drone.
[0558] 4.sup.th aspect of "Discolored Spots Detection": A
controlled agricultural system, according to any one of the
1.sup.st to 3.sup.rd aspect of "Discolored Spots Detection",
wherein the sensor device comprises one or more of the following
sensors: camera, CCD sensor with or without filter, photodiode.
[0559] Due to the above explained measures according to the
disclosure, and because the discolored spots DSi do not reflect (or
only very minimally) light with their respective Complementary
Color Spectrum CCi, discolored spots are visualized as dark spots
that can be recognized and measured easily by a camera or other
sensor systems (Photodiode, CCD chips with filters etc.).
[0560] In other words, when a plant has discolored parts/spots due
to a disease or any other cause, illuminating the plant with the
complementary light increases the contrast between the discolored
part and the surrounding part of the plant/stem/leave, making it
easier to identify discolored parts/spots.
[0561] In some embodiments/implementations, the controlled
agricultural system according to the disclosure comprises a
(scientific) database with a mapping of plant diseases,
diseases-typical discolorations of the plants (for every growth
stage), and the respective complementary light (Complementary Color
Spectrum CCSi). The database is part of a computing device.
[0562] The controlled agricultural system further comprises an
illumination unit (lighting fixture), which may be based on LEDs
(with or without phosphor conversion), Super-Luminescent Diodes, or
lasers, and which emits light in the visible range (approx. 380 to
780 nm), and may also include violet and Far-Red radiation. The
illumination unit is suited to apply the complementary light
(Complementary Color Spectrum CCSi). The controlled agricultural
system is configured to control the illumination unit based on the
data of the database.
[0563] The controlled agricultural system further comprises a
sensor system (controlled by its control unit). This may be a
(still or video) camera. For each setting of complementary light,
the camera takes a picture of the plants (probe picture). The
computing device analyses each picture and looks for dark spots.
The computing device may also store a picture taken with
normal/reference illumination, e.g. white light, which shows the
leaves and other parts of the plants (reference picture). The
computing device then compares each probe picture with the
respective reference pictures. If dark spots are detected in an
area, which comprises parts of the plants, this may indicate a
discoloration due to a disease.
[0564] Based on the data of the database, which may be stored on a
data storage device connected to (or integrated within) the
computing device, the controlled agricultural system applies to the
plants complementary light through the illumination unit. For
instance, red discolorations (with an RGB-code of e.g. #FF0000)
will appear dark when illuminated with a cyan color (with the
RGB-code of #00FFFF). Therefore, this measure according to the
disclosure intensifies the contrast between the discolored part and
the normal-colored part and makes it easier to detect a discolored
part/spot (disease).
[0565] In a second embodiment, the controlled agricultural system
applies normal (reference), non-complementary light of the
discoloration to the plant in a first step and then the
complementary light in a second step. This will lead to a very
pronounced color difference between the first (reference) and the
second (probe) picture taken with the camera, making it even easier
to detect discolored parts.
[0566] In another embodiment of the disclosure, the illumination
unit illuminates the plants at different wavelengths (each
wavelength range is emitted consecutively, i.e. only during
separate time intervals), i.e. performs a spectral scan mode for
probing discolored areas, and the computing device analyses the
pictures. This approach can be advantageous to detect possible
diseases if the database, particularly the data for specific
Complementary Color Spectra, is not available or incomplete.
[0567] In yet another embodiment, the computing device is
configured to trigger measurements of discolorations in regular or
irregular time intervals or even stochastically. The measurement
data may be analyzed by means of deep learning algorithms.
Furthermore, the results of the analysis may be represented
graphically. Such procedure may be used to monitor curing of plant
diseases.
[0568] 5.sup.th aspect of "Discolored Spots Detection": A
controlled agricultural system, according to any one of the
1.sup.st to 4.sup.th aspect of "Discolored Spots Detection",
further comprising a user interface.
[0569] The computing device may also comprise a user interface,
which provides feedback of the measurements to the user. Via the
interface the user can also schedule measurements (once a day, once
a week, during the day, at the end of the day, irregular intervals,
stochastically within time intervals, etc.). The computing device
then interrupts the normal illumination mode and switches the
illumination to detect mode.
[0570] In the detect mode, the plants are illuminated with
complementary light, either applying the lights (Complementary
Color Spectra) stored in the database or providing a spectral light
scan, as described above. If the detection is performed in a
greenhouse, the controlled agricultural system may draw down
shutters or blinds prior to starting the detection mode. For this
purpose, the controlled agricultural system may further comprise an
appropriate actuator.
[0571] Due to the enhanced contrast between the dark spots and the
surrounding when taking pictures with complementary light, diseases
can be easily detected. It is not even necessary to have a very
close look at the plants, but the sensor (e.g. the camera) can be
placed at some distance of a plant and cover several plants at the
same time. The plants can be illuminated and sensed from above or
from the side (i.e. focusing on leaves or stems).
[0572] It should be noted that the controlled agricultural system
according to the disclosure that applies to the plants
complementary light by means of the illumination unit can be used
in a greenhouse that is with the presence of natural sun light, as
well as in a completely enclosed farming environment (controlled
agricultural environment). In the first case, illumination with
complementary light will still increase the color difference
between healthy and discolored unhealthy plant parts. Similarly, in
the second case, when the regular illumination light is on
(ON-Lighting-cycle) or OFF (OFF-lighting-cycle). If measurements
are performed in the ON-Lighting-cycle, the regular illumination
can be temporarily switched off during the measurement cycles and
switched on afterwards.
[0573] Agricultural lighting fixtures may comprise artificial light
sources like Light Emitting Diodes (LED) with or without conversion
by using a fluorescent substance, commonly referred to as phosphor,
monochromatic Laser diodes, OLED light emitting material on organic
basis, Quantum Dot light emitters, Fluorescent lamps, Sodium low
and high pressure lamps, Xenon and Mercury Short Arc lamps, Halogen
lamps, and the like.
[0574] All of the plants arranged in an agricultural or
horticultural facility and managed by means of a controlled
agricultural system according to the disclosure need not be
illuminated with the Complementary Color Spectra (CCSi) at the same
time, but can be illuminated sequentially. For example, the light
with a Complementary Color Spectrum (CCSi) may be directed onto a
scanning device, like a moving MEMS-mirror, and then reflected onto
the various parts of an agricultural plant environment (plant
cultivating area) in a time sequential manner.
[0575] 6.sup.th aspect of "Discolored Spots Detection": A
controlled agricultural system, according to any one of the
1.sup.st to 5.sup.th aspect of "Discolored Spots Detection",
further comprising an actuator device able to treat the plants,
e.g. with water, UV-light, IR-light, nutrition, medication,
fungicides, pesticides.
[0576] Furthermore, the computing device may comprise an object
recognition program that determines the location of the affected
plant and can then send command controls to a health sustaining
system. The health sustaining system may comprise appropriate
actuators, e.g. by means of automated guided vehicles (AGV), which
then treat the affected plant(s) (or plant area) with e.g.
UV-light, IR-light, nutrition, medication, pesticides, etc.
[0577] 7.sup.th aspect of "Discolored Spots Detection": A
controlled agricultural system, according to any one of the
1.sup.st to 6.sup.th aspect of "Discolored Spots Detection",
wherein the colors of parts of plants comprise one or more of the
following: discolored spots, particularly due to diseases, colors
of flowers, colors of fruit in various stages of ripening.
[0578] Furthermore, according to "Discolored Spots Detection", a
method for detecting/verifying colors or discoloration of plants,
or discolored spots on plants, or discoloration of plant parts,
like fruits or flowers, is proposed by providing an illumination
system that illuminates the plants or parts of the plants with
light with Complementary Color Spectra (CCSi) with regard to the
anticipated color or discoloration of the plant, plant part or
plant spot. The controlled agricultural system is configured to be
able to execute the method.
[0579] 8.sup.th aspect of "Discolored Spots Detection": More
specifically, the method for agricultural management, comprises at
least one controlled agricultural system and the steps of starting
the detect mode of the controlled agricultural system, illuminating
plants with complementary light by means of the illumination
device, and screening/detecting the plants for dark areas, e.g.
discolored spots that appear as dark spots when illuminated by the
complementary light, by means of the sensor device.
[0580] 9.sup.th aspect of "Discolored Spots Detection": The method
for agricultural management according to the 8.sup.th aspect of
"Discolored Spots Detection", further comprising the step of
analyzing and identifying the cause of a detected dark area, e.g. a
discolored spot, flower, fruit, etc., by means of the computing
device based on data store on the data storage device.
[0581] 10.sup.th aspect of "Discolored Spots Detection": The method
for agricultural management according to the 8.sup.th or 9.sup.th
aspect of "Discolored Spots Detection", further comprising the step
of identifying the disease associated with a detected discolored
spot by means of the computing device.
[0582] 11.sup.th aspect of "Discolored Spots Detection": The method
for agricultural management according to any one of the 8.sup.th to
10.sup.th aspect of "Discolored Spots Detection", wherein screening
the plants for dark areas further comprises the step of taking
pictures of the plants by means of the camera.
[0583] 12.sup.th aspect of "Discolored Spots Detection": The method
for agricultural management according to any one of the 8.sup.th to
11.sup.th aspect of "Discolored Spots Detection", wherein screening
the plants for dark areas further comprises the step of detecting
the color of the light reflected by the plants/plant parts by means
of at least one photodiode or CCD chips with filters.
[0584] 13.sup.th aspect of "Discolored Spots Detection": The method
for agricultural management according to any one of the 8.sup.th to
12.sup.th aspect of "Discolored Spots Detection", further
comprising the step of probing for a specific discoloration by
illuminating the plants with the respective complementary
light.
[0585] 14.sup.th aspect of "Discolored Spots Detection": The method
for agricultural management according to any one of the 8.sup.th to
13.sup.th aspect of "Discolored Spots Detection", further
comprising the step of enhancing the contrast for analyzing and
detecting the dark areas by illuminating the plants with
normal/reference light, particularly white light, and comparing the
measurement data (reference data) from the sensor device with the
respective measurement data (probe data) from the illumination with
complementary light.
[0586] 15.sup.th aspect of "Discolored Spots Detection": The method
for agricultural management according to any one of the 10.sup.th
to 13.sup.th aspect of "Discolored Spots Detection", further
comprising the step of taking countermeasures against the
identified disease, e.g. treating the affected plant(s) with e.g.
UV-light, nutrition, medication, fungicides, pesticides, etc., by
means of the actuator device.
[0587] 16.sup.th aspect of "Discolored Spots Detection": The method
for agricultural management according to any one of the 10.sup.th
to 13.sup.th aspect of "Discolored Spots Detection", further
comprising the step of informing the user by means of the user
interface that discolored spots have been identified and about the
diagnosed disease.
[0588] Furthermore, reference is made to the description above; the
features described there shall also be disclosed in terms of the
method.
[0589] 17.sup.th aspect of "Discolored Spots Detection": A
machine-readable computer product, comprising a multiplicity of
program instructions which, when executed on the computing device
of the controllable agricultural system according to any one of the
1.sup.st to 7.sup.th aspects, cause the Controlled Agricultural
System to execute the method for agricultural management according
to any one of the 8.sup.th to 16.sup.th aspects of "Discolored
Spots Detection".
[0590] 18.sup.th aspect of "Discolored Spots": A method for
investigating a plant grown in an agricultural system,
comprising:
[0591] providing a complementary light source for emitting a first
complementary light with a first complementary color spectrum,
which has a first spectral gap in comparison to a white light
spectrum,
[0592] illuminating the plant with the first complementary
light,
[0593] screening the plant illuminated by the first complementary
light for dark areas, which absorb the first complementary light at
least partly, and/or for bright areas, which reflect the first
complementary light at least partly.
[0594] 19.sup.th aspect of "Discolored Spots": The method of the
18.sup.th aspect of "Discolored Spots", wherein the first spectral
gap of the first complementary color spectrum lies in the green
and/or yellow spectral range, the plant illuminated by the first
complementary light being screened for bright areas.
[0595] Typical leaves having a green color show no absorption in
the green/yellow spectral range. Consequently, they reflect
green/yellow light, which is the reason for their green appearance.
When illuminating the plant with spectral intensities outside the
green/yellow spectral range, the focus is not on the green leaves
themselves but on any discoloration of the leaves, for instance
discolored spots. Those can indicate an insufficient supply or a
disease of the plant. In simple words, since the green colored
leave itself is not illuminated in its spectral range, any
discoloration of the leaves can be detected better. Any
discoloration appears brighter as the green background is
reduced.
[0596] "Blue spectral range" can for instance mean a spectral range
from 400 nm to 490 nm.
[0597] "Green spectral range" can for instance mean a spectral
range from 490 nm to 575 nm.
[0598] "Yellow spectral range" can for instance mean a spectral
range from 575 nm to 600 nm.
[0599] "Orange spectral range" can for instance mean a spectral
range from 600 nm to 650 nm.
[0600] "Red spectral range" can for instance mean a spectral range
from 650 nm to 800 nm.
[0601] The existence of a "spectral gap" does not necessarily mean
that there is no intensity at all in the respective spectral range.
The intensity shall be at least reduced, it can for instance amount
to not more than 30%, 20% or 10% of a maximum intensity of the
complementary color spectrum (comparing for instance the spectral
irradiance). This can apply for an average intensity in the
spectral range with the spectral gap and/or for a maximum intensity
in the spectral range with the spectral gap. Nevertheless, it is
also possible that there is no intensity at all in the spectral
range with the gap.
[0602] 20.sup.th aspect of "Discolored Spots": The method of the
19.sup.th aspect of "Discolored Spots", wherein leaves of the plant
illuminated by the first complementary light are screened for the
bright areas for detecting a plant disease or inappropriate plant
treatment.
[0603] Alternatively, the screening of bright areas can also allow
for a tracking of a growth stage, for instance the flowering or
ripening (e.g. change from green to red color).
[0604] 21.sup.st aspect of "Discolored Spots": The method of the
18.sup.th aspect of "Discolored Spots", wherein the first spectral
gap of the first complementary color spectrum lies outside the
green spectral range, the plant illuminated by the first
complementary light being screened for dark areas.
[0605] In this case, for instance, the green leave itself will
reflect the green light and appear bright, whereas a discolored
area will appear dark when the spectral gap lies outside the
spectral range reflected by the discoloration.
[0606] 22.sup.nd aspect of "Discolored Spots": The method of the
21.sup.st aspect of "Discolored Spots", wherein the first spectral
gap of the first complementary color spectrum lies in the blue
spectral range.
[0607] The first complementary color spectrum can have intensities
in the green and/or yellow and/or orange and/or red spectral
range.
[0608] 23.sup.rd aspect of "Discolored Spots": The method of the
22.sup.nd aspect of "Discolored Spots", wherein leaves of the plant
illuminated by the first complementary light are screened for the
dark areas for detecting a plant disease or inappropriate plant
treatment causing yellow coloring of the leaves.
[0609] 24.sup.th aspect of "Discolored Spots": The method of the
22.sup.nd or 23.sup.rd aspect of "Discolored Spots", wherein the
first complementary light is green light.
[0610] The first complementary color spectrum has a spectral
intensity in the green spectral range only.
[0611] 25.sup.th aspect of "Discolored Spots": The method of any of
18.sup.th to 24.sup.th aspects of "Discolored Spots", wherein a
first image of the plant illuminated by the first complementary
light is captured and screened for dark and/or bright areas by
digital image evaluation.
[0612] 26.sup.th aspect of "Discolored Spots": The method of the
25.sup.th aspect of "Discolored Spots", wherein the number of dark
areas in the first image is counted and/or the number of bright
areas in the first image is counted.
[0613] Apart from a disease detection, the dark and/or bright area
screening can for instance be used for evaluating the number of
flowers or fruits (an approximate value), which can allow for a
yield prediction (see the element "Yield Prediction" in
detail).
[0614] 27.sup.th aspect of "Discolored Spots": The method of any of
the 18.sup.th to 26.sup.th aspects of "Discolored Spots", wherein
the plant is, subsequently to the illumination with the first
complementary light, illuminated by a second complementary light
with a second complementary color spectrum, which has a second
spectral gap in comparison to a white light spectrum, the second
spectral gap lying in another spectral region than the first
spectral gap.
[0615] 28.sup.th aspect of "Discolored Spots": The method of any of
the 18.sup.th to 26.sup.th aspects of "Discolored Spots", wherein
the illumination unit illuminates the plants at different
wavelengths (each wavelength range is emitted consecutively, i.e.
only during separate time intervals), i.e. performs a spectral scan
mode for probing discolored areas.
[0616] In other words, a spectral scan is performed, see the above
remarks on the "spectral scan mode". Further, subsequently to the
illumination with the first/second complementary light, the plant
can be illuminated by a third complementary light with a third
complementary color spectrum, which has a third spectral gap in
comparison to a white light spectrum, the third spectral gap lying
in another spectral region than the first and the second spectral
gap.
[0617] The complementary light source can be adjustable to emit the
different complementary light spectra subsequently, or a plurality
of complementary light sources can be provided.
[0618] 29.sup.th aspect of "Discolored Spots": The method of the
27.sup.th aspect of "Discolored Spots", wherein a first image of
the plant illuminated by the first complementary light is captured
and a second image of the plant illuminated by the second
complementary light is captured, wherein an image comparison of the
first and the second image is performed.
[0619] 30.sup.th aspect of "Discolored Spots": An agricultural
system for a method according to any of the 18.sup.th to 29.sup.th
aspects of "Discolored Spots", the agricultural system
comprising
[0620] a light fixture for emitting light,
[0621] a growth area for growing a plant,
[0622] a sensor device,
[0623] an actuator device,
[0624] a computing device,
[0625] wherein the sensor device comprises an image capture device
for capturing an image of the plant,
[0626] and wherein the computing device is configured to process
the image captured by the image capture device and, based on an
outcome of the image processing, to trigger the actuator device
and/or to output a signal to a user interface.
[0627] The actuator device can for instance perform a pest control
or crop spraying, or a targeted fertilization. It can also unload
the plant to a separate treatment location, see "Horticulture
Processing Line" in detail.
[0628] The agricultural system can in particular be configured to
illuminate the plant with the first complementary light. The image
of the plant is captured when the plant is illuminated by the first
complementary light.
[0629] 31.sup.st aspect of "Discolored Spots": The agricultural
system of the 29.sup.th aspect of "Discolored Spots", wherein the
computing device is configured to screen the image captured by the
image capture device for dark areas and/or for bright areas.
[0630] 32.sup.nd aspect of "Discolored Spots": The agricultural
system of the 29.sup.th or 31.sup.st aspect of "Discolored Spots",
wherein the computing device is configured to access a database,
which comprises data on plant diseases and disease-related
discolorations, wherein the image processing comprises a matching
with the data comprised in the database.
[0631] 33.sup.rd aspect of "Discolored Spots": The agricultural
system of any of the 29.sup.th to 32.sup.nd aspects of "Discolored
Spots", wherein the complementary light source for emitting the
first complementary light is comprised in the light fixture, the
computing device being configured to switch between an
investigation mode, in which the complementary light source emits
the first complementary light, and an agricultural lighting mode,
in which the complementary light source is switched off and another
light source of the light fixture emits light to assist a growth of
the plant.
[0632] The light emitted by the other light source can for instance
be defined in a light recipe.
[0633] 34.sup.rd aspect of "Discolored Spots": The agricultural
system of any of the 29.sup.th to 33.sup.rd aspects of "Discolored
Spots", comprising a light guide coupled to the complementary light
source, wherein the light guide is provided for guiding the first
complementary light to the plant.
[0634] The light guide can for instance be a fiber optic cable, see
the element "Light Guides" in detail.
[0635] "Disease & Pest Control"
[0636] According to the element "Disease & Pest Control" of the
disclosure, diseases and pests are identified based on collecting
data about the plants and, optionally, about the ambient conditions
in the target area as well. Then, a probability for the presence of
a disease or the occurrence of pests is determined by comparing the
collected data with reference data. Depending on the probability,
and if need be, appropriate measures are proposed or introduced
automatically.
[0637] 1.sup.st aspect of "Disease & Pest Control": More
specifically, the controlled agricultural system, comprises a
sensor device for acquiring data in a target area, a computing
device connected to the sensor device, a data storage device
connected to the computing device, wherein the computing device is
configured to compare the data of the sensor device with the data
stored in the data storage device and detect deviations between the
two sets of data, a control unit connected to the computing device,
wherein the computing device is configured to output control
commands to the control unit depending on the detected deviations,
a light fixture connected to the control unit, wherein the control
unit is configured to convert the control commands of the computing
device into control signals for the light fixture.
[0638] The controlled agricultural system is configured to allow
the identification of changes to plants that may be caused by
diseases or pests, the identification of these diseases or
infestation by pests and the introduction of measures, in
particular countermeasures, which contain light recipes, in
particular UV-A and UV-B radiation, but also radiation in the blue
and yellow spectral range. This is because it is known that certain
light recipes are harmful to pests, such as lice, arachnids, acari,
and bacterial pathogens. To this end, the controlled agricultural
system may comprise at least one light fixture (agricultural light
fixture) with corresponding light sources. Furthermore, the
countermeasures may contain light recipes, which reduce the plant
stress (biotic stress). For reducing biotic stress, illumination
parameters may be adapted, for example, the illumination duration
and/or the illuminance may be changed, e.g. reduced, and/or the
light spectrum of the illumination may be changed.
[0639] 2.sup.nd aspect of "Disease & Pest Control": A
controlled agricultural system, comprising a sensor device for
acquiring data in a target area, a computing device connected to
the sensor device, a data storage device connected to the computing
device, wherein the computing device is configured to compare the
data of the sensor device with the data stored in the data storage
device and detect deviations between the two sets of data, an
actuator device connected to the control unit, wherein the control
unit is configured to convert the control commands of the computing
device into control signals for the actuator device.
[0640] By way of example, measures may also comprise a change in
the room temperature, the humidity, ventilation, the addition of
nutrients, fertilizer, pesticides, pheromones, and the addition of
medicine such as systemically acting pesticides to the nutrients.
Further measures may contain a geometric modification of the light
fixture position, the light fixture configuration and the light
fixture emission characteristic. To this end, the controlled
agricultural system may comprise corresponding actuators, which
carry out these measures.
[0641] A further measure in the case of an infestation by pests may
include traps being illuminated in such a way that insects are
attracted thereby, said insects leaving the plants and being locked
in the traps or adhering thereto (sticky traps). This can be
assisted by pheromones, etc. Likewise, it is possible to attract
predators for the pests, such as mesostigmata, which attack spider
mites. To this end, the plants can be illuminated with light in the
UV range (250-380 nm) and/or in the blue-green range (500-550
nm).
[0642] 3.sup.rd aspect of "Disease & Pest Control": The
controlled agricultural system according to the 1.sup.st and
2.sup.nd aspect of "Disease & Pest Control".
[0643] Furthermore, it may be advantageous to combine the
controlled agricultural system according to the 1.sup.st aspect of
"Disease & Pest Control" with the controlled agricultural
system according to the 2.sup.nd aspect of "Disease & Pest
Control".
[0644] 4.sup.th aspect of "Disease & Pest Control": The
controlled agricultural system according to any one of the 1.sup.st
to 3.sup.rd aspect of "Disease & Pest Control", wherein the
sensor device is designed to acquire data of plants growing in the
target area and/or data in relation to the ambient conditions in
the target area.
[0645] Therefore, the controlled agricultural system is equipped
with sensors, for example optical sensors, which identify the
growth of the plants, the reflectivity of the leaves or the stress
of the plants, for example. The growth of the plants may be
detected by the density of the leaves, plant morphology, and leaf
area index.
[0646] However, sensors may also identify the fluorescence
radiation emitted by plants (after irradiation with excitation
radiation). Chlorophyll fluorescence may be a particularly suitable
option since the photosystem or the respiration changes in the case
of disease or environmental conditions. Sensors may also measure a
change in color of the plant (see e.g. the element "Discolored
Spots Detection"), in particular of the leaves. Sensors may also
determine gases released by plants or determine the concentration
of said gases in the ground.
[0647] Sensors may also identify the pests directly or typical
damage to the plants, which indicates infestation by pests (stunted
growth, deformations or other malformations). Here, use can be made
of optical sensors such as cameras with image recognition, LiDAR
systems for acquiring the plant morphology (see e.g. the element
"LiDAR Plant Surveillance"), spectroscopic measurement appliances,
which analyze spectral properties of the irradiation light,
reflected from the infested plants, but also acoustic sensors which
register characteristic noises from the pests.
[0648] Deviations that indicate a disease or negative change in the
plant health or an infestation by pests are determined by the
comparison with a characteristic growth behavior or characteristic
physical or chemical properties. As already explained above, the
type of disease or pest infestation can be determined by exact
analysis of the leaf colors or plant forms, for example.
[0649] The comparison data are stored in a database and can be
evaluated by an evaluation unit, in particular also in statistical
fashion. The comparison with an intended value can be implemented
by direct parameter comparison; however, artificial intelligence
methods (such as deep learning) can also be used for the comparison
of statistical evaluation. A parameter comparison can include an
analysis and comparison of the plant morphology and a prediction,
derived therefrom, for the further growth or the morphological
embodiment of the plants. From the comparison of the measured data
with the characteristic values (intended values), the system
establishes a probability for the occurrence of the disease or the
infestation by pests. Furthermore, such an evaluation unit can be
provided to create predictions of a possible outbreak of disease
and thereupon output a corresponding warning to the operator and/or
customer of an agricultural system controlled in this fashion.
[0650] If the probability lies above a first threshold, then there
probably is an affliction by disease or pests. The system informs
the operator or planter, for example, about the discovery of the
possible disease or infestation by pests and proposes a further
analysis in order to determine the disease or the infestation by
pests more accurately.
[0651] If the probability lies above a second threshold, the system
can propose a specific countermeasure for the disease or the
infestation by pests or (in a further embodiment) autonomously
carry out the countermeasures described above in exemplary
fashion.
[0652] In order to carry out the comparison of the sensor data with
the comparison data (intended data), the controlled agricultural
system comprises a computing device. Here, the sensor data and the
comparison data are supplied to the computing device. Depending on
the result of the comparison, the computing device, via a control
unit, actuates the light sources in the respective light fixture
or, optionally, the actuators as well.
[0653] Part of the controlled agricultural system, for example the
computing device or the data storage device, may be local, but it
may also be network-based or cloud-based.
[0654] Furthermore, according to the aspect "Disease & Pest
Control", a method for identifying and reacting to diseases and
pests is proposed.
[0655] 5.sup.th aspect of "Disease & Pest Control": More
specifically, the method for agricultural management, according to
"Disease & Pest Control", comprises the steps of monitoring the
plants in a target area by collecting data about the plants and/or
the ambient conditions in the target area, comparing the collected
data to corresponding intended data, determining whether deviations
have occurred during the comparison, determining the probability
for the occurrence of a disease or pest infestation on account of
the determined deviations and if the probability lies under a first
threshold then no further measures are introduced, if the
probability lies between a first threshold and a second threshold
then an information item that a disease or a pest infestation may
be present is output and/or further analyses proposed, if the
probability lies over a second threshold then countermeasures are
propose or, alternatively, countermeasures are independently
introduced.
[0656] The probability for the occurrence of a disease or pest
infestation may be determined as follows. First, the difference
values of the relevant parameters that deviate from the respective
intended parameter values are calculated, i.e. in each case the
absolute value of the measured value minus the intended value of a
parameter. Relevant parameters in this context are parameters that
indicate or influence the growth and/or health status of the
plants, for example, the color of the plants, temperature and
humidity of the environment, etc. Then each difference value is
multiplied with a respective weighting factor, and the products
are, finally, accumulated. The resulting sum is a measure of the
probability. The respective weighting factors depend, amongst
others, on the number of measured parameters. For instance, the
partial probabilities have to be normalized to result in a total
sum of the value 1 if the plants are actually infected by a
specific disease. Furthermore, a weighting factor may be the
smaller the less relevant the respective parameter is for
determining a disease. Furthermore, the weighting factors may be
modified with the help of learning algorithm (AI, deep learning)
based on empirical data to improve the reliability of the detection
of a disease or infection with pest.
[0657] 6.sup.th aspect of "Disease & Pest Control": The method
for agricultural management according to the 5.sup.th aspect of
"Disease & Pest Control" carried out using a controlled
agricultural system according to any one of the 1.sup.st to
4.sup.th aspect of "Disease & Pest Control".
[0658] 7.sup.th aspect of "Disease & Pest Control": A
machine-readable computer product, comprising a multiplicity of
program instructions which, when executed on the computing device
of the controllable agricultural system according to any one of the
1.sup.st to 4.sup.th aspect of "Disease & Pest Control", cause
the Controlled Agricultural System to execute the method for
detecting and reacting to diseases or pests of plants according to
the 6.sup.th aspect of "Disease & Pest Control".
[0659] "Yield Prediction"
[0660] According to the element "Yield Prediction" of the
disclosure, an automated yield forecast for flowering plants like
tomatoes or strawberries is proposed. To this end, a controlled
agricultural system is configured to be able to predict the yield
of flowering plants growing in a target area (cultivated area).
[0661] 1.sup.st aspect of "Yield Prediction": A controlled
agricultural system, comprising a sensor device, comprising sensors
able to detect flowers and/or buds of plants, a data storage
device, wherein conversion rates of flower to fruit of plants are
stored, a computing device, configured to identify and count the
flowers/buds from the data of the sensor device, and further
configured to predict the yield based on the number of the
flowers/buds and the respective conversion rate retrieved from the
data storage device.
[0662] 2.sup.nd aspect of "Yield Prediction": Alternatively, a
controlled agricultural system, comprises a sensor device,
comprising sensors able to measure the biomass of plants, and
further comprising sensors able to measure environmental parameters
like light intensity, light spectrum, temperature, air movement,
humidity, chemical composition of soil, air, fluids, a computing
device, configured to predict the yield based on the biomass of the
plants and current and/or future environmental data measured by
means of the sensor device.
[0663] According to the alternative approach, the actual biomass is
measured and current and/or future environmental data (temperature,
humidity, light intensity, light spectrum . . . ) are in some
embodiments/implementations included to estimate the yield. Biomass
in this context refers to the mass of the plants, e.g. deduced from
the number of plants and their size, i.e. the size of their stems
and/or leaves.
[0664] 3.sup.rd aspect of "Yield Prediction": The controlled
agricultural system according to the 1.sup.st or 2.sup.nd aspect of
"Yield Prediction", further comprising a user interface configured
to deliver the result of the prediction.
[0665] 4.sup.th aspect of "Yield Prediction": The controlled
agricultural system according to any one of the 1.sup.st to
3.sup.rd aspect of "Yield Prediction", wherein the sensor device
comprises one or more of the following sensors or a combination
thereof: imaging system, e.g. still or video camera, in some
embodiments/implementations TOF camera or stereo camera, LIDAR
system, color sensor.
[0666] The controlled agricultural system comprises at least one
sensor, which is able to detect the flowers (or buds) at a plant or
to measure the biomass of the plants in the target area. For
instance, the at least one sensor may comprise a camera and an
image recognition system (object recognition and classification) to
detect flowers (or buds) at a plant.
[0667] Furthermore, the controlled agricultural system comprises a
computing device configured to identify the flowers (or buds) from
the data measured by the at least one sensor. The computing device
may host the image recognition system. It may use machine
learning/deep learning algorithms to detect flowers. Alternatively
or in combination, it may also detect the flowers directly based on
the color of the flower (e.g. yellow for tomatoes) and/or the
typical size derived from the picture, either as an absolute value
or relative to the size of other parts of the plant (e.g.
leaves).
[0668] 5.sup.th aspect of "Yield Prediction": The controlled
agricultural system according to any one of the 1.sup.st to
4.sup.th aspect of "Yield Prediction", wherein the sensor device
further comprises sensors able to measure the current status of
growth/ripening of the plants/fruits.
[0669] 6.sup.th aspect of "Yield Prediction": The controlled
agricultural system according to the 5.sup.th aspect of "Yield
Prediction", wherein typical time schedules of ripening of the
fruits are stored in the data storage device, and wherein the
computing device is configured to calculate a prediction for the
harvesting time of the fruits based on the currently detected
status of growth/ripening of the plants/fruits and the typical time
left until ripeness of the fruits according to the time
schedules.
[0670] To cover an extended cultivated area, multiple sensors, e.g.
cameras, may be distributed within the area. For instance, the
sensors/cameras may be attached fixedly in the greenhouse or at
posts in the field. Some or all of the sensors (cameras) may be
attached movably at a drone or robot and move through the
greenhouse or the field, in some embodiments/implementations
autonomously.
[0671] The number of flowers or buds per plants may be assessed
individually for each plant in the cultivated area of the field or
the greenhouse to obtain the overall number of flowers or buds in
the cultivated area. If the number of plants is too large, a
statistical approach can be chosen, i.e. limiting the measurements
to a representative selection of plants (sub group). For instance,
only every nth plant is measured, plants in a certain distance from
the next plant are measured or plants in areas of the field that
are known to be representative for the whole field (cultivated
area) are measured. The number of flowers for the whole field
(cultivated area) is then extrapolated from the measured number of
flowers of this subgroup of plants.
[0672] Furthermore, according to "Yield Prediction", a method for
predicting the yield is proposed.
[0673] 7.sup.th aspect of "Yield Prediction": More specifically, a
method for agricultural management, comprises at least one
controlled agricultural system and the steps of detecting the
flowers or buds of the plants by means of the sensor device and the
computing device assessing the number of flowers/buds by means of
the computing device and based on the data measured by the sensor
device predicting the yield by retrieving the respective conversion
rate of the plant species from the data storage device and weighing
the number of flowers assessed in the previous step with the
conversion rate by means of the computing device.
[0674] 8.sup.th aspect of "Yield Prediction": Alternatively, a
method for agricultural management, comprises at least one
controlled agricultural system and the steps of measuring the
biomass of the plants by means of the sensor device and the
computing device, measuring environmental parameters by means of
the sensor device and the computing device, predicting the yield
based on the biomass and the environmental data by means of the
computing device.
[0675] For predicting the yield, the method for agricultural
management, according to the aspect "Yield Prediction", uses a
typical conversion rate from flowers to fruits available for each
plant species in a database, which is stored in a data storage
device of the computing device. The conversion rate is the rate at
which flowers result in fruits. For instance, a conversion rate of
0.5 means that only half of the flowers eventually result in fruits
(e.g. 10 flowers would result in 5 fruits). The typical conversion
rate may be the average value of conversion rates observed in the
past. The conversion rate may depend on additional parameters like
the temperature, humidity, etc., which may be measured as well, in
order to improve the accuracy of the prediction. For example, the
pollination performance of the bumble-bees is different, depending
on the species, temperature, air movement, day length, humidity,
etc. It also depends on the amount of bumble-bees the grower is
using. All these parameters have to be considered to derive a
correct yield prediction. The calculated conversion rate can also
take into consideration future changes in parameters like
temperature, humidity or illumination. The parameters may be
checked regularly. In case deviations are observed, the conversion
rate and with it the predicted yield may be updated.
[0676] 9.sup.th aspect of "Yield Prediction": The method for
agricultural management according to 8.sup.th aspect of "Yield
Prediction", further comprising the step of delivering the result
of the prediction to the user (e.g. farmer or customer) by means of
the user interface.
[0677] Using the typical conversion rate and the measured or
extrapolated number for flowers in the cultivated area, the
expected number of fruits is calculated by the computing device,
taking into consideration that not all fruits will "survive" until
harvesting, as they may drop, for example, due to low water, bad
nutrition or something else. Using the average weight of the
fruits, the expected total yield can be calculated, e.g. in
kilograms.
[0678] 10.sup.th aspect of "Yield Prediction": The method for
agricultural management according to any one of the 7.sup.th to
9.sup.th aspect of "Yield Prediction", further comprising the steps
of detecting the current state of ripening of the plants/fruits by
means of the sensor device and the computing device, predicting the
harvesting time by retrieving the time schedule of ripening from
the data storage device, comparing it with the current state of the
ripening and calculating the typical time left until ripeness of
the fruits, according to the time schedules and by means of the
computing device, and/or predicting the next stage of ripening by
retrieving the time schedule of ripening from the data storage
device, comparing it with the current state of the ripening and
calculating the typical time left for the next state of ripening,
according to the time schedules and by means of the computing
device.
[0679] Furthermore, the harvesting time may be forecasted as well.
For this purpose, the system recognizes the state of the ripeness,
e.g. the development of the flowers, the withering of the flowers,
the creation of the fruits, and the different state of its
ripeness. It can predict the expected harvesting time for each
fruit based on average times stored in a database.
[0680] The prediction does not only include the final harvesting
time but also the time when the next stage in the ripening process
will be accomplished. The predicted time is compared regularly with
the actual time. The forecast will be adjusted accordingly in case
there should be a difference between actual and predicted time
(e.g. a faster or slower ripening). In this case, the average
ripening time stored in the database will be updated. The average
ripening time for each stage (time schedule of ripening) is in some
embodiments/implementations stored with corresponding environmental
data like humidity, nutrition, illumination, temperature, and
others.
[0681] The computing device may then present the calculated result
(prediction) to a third party like the customer or farmer. The
result may comprise a set of data, including the forecasted yield
and, optionally, harvesting time, images (shot by still or video
camera) or other graphical representation such as virtual or
augmented reality of the plants.
[0682] 11.sup.th aspect of "Yield Prediction": A computer program
product, comprising a plurality of program instructions, which when
executed by a computer system of an Controlled Agricultural System
according to any one of the 1.sup.st to 6.sup.th aspect of "Yield
Prediction", cause the Controlled Agricultural System to execute
the method for Agricultural Management according to any one of the
7.sup.th to 10.sup.th aspect of Yield Prediction".
[0683] "Fungi Growth Inhibition"
[0684] According to the element "Fungi Growth Inhibition" of the
disclosure, a controlled agricultural system with a light fixture
is proposed that is configured to be able to illuminate plants
during the nighttime to inhibit growth of fungi.
[0685] 1.sup.st aspect of "Fungi Growth Inhibition": A Controlled
Agricultural System for growing plants, comprising a lighting
fixture for providing agricultural lighting, a fungi prevention
light source for emitting light with a wavelength in a spectral
range between 380 nm and 800 nm, wherein the Agricultural System is
configured for applying the agricultural lighting to the plants
during a day phase; and illuminating the plants with the fungi
prevention light source at least temporarily during a night
phase.
[0686] In addition to a lighting fixture for agricultural lighting,
the agricultural system comprises a fungi prevention light source
for emitting light with a wavelength in a spectral range between
380 nm and 800 nm. During a day phase, the agricultural lighting is
applied to the plants. During a night phase, which usually is a
dark period without any lighting at all, the plants are illuminated
at least temporarily with the fungi prevention light source. In
general, the duration of the additional illumination may vary from
1 minute to several hours, for instance 8 hours.
[0687] Illuminating the plants during the night phase can inhibit
or prevent the growth of pathogenic fungi that would cause plant
diseases. For the purpose of illustration, reference is made to
downy mildew below, even though the disclosure is not restricted to
it. Downy mildew is one of the most occurring diseases in basil and
can lead to huge losses in production up to a total loss of the
crop.
[0688] By illuminating the plants during the night phase, the
germination or sporulation of a fungi spore can be prevented or
growth can be suppressed. Also sporulation can be slowed down,
depending on temperature and light conditions. The fungi growth or
germination/sporulation is affected by illumination, which means
that a certain dark period duration is usually required to trigger
the germination/sporulation of the spores. In simple words, it
germinates and sporulates generally during the night. With the
fungi prevention light source, the night or night phase is
interrupted, preventing the germination. In other words, day
conditions are simulated for the fungus during the night phase.
[0689] 2.sup.nd aspect of "Fungi Growth Inhibition": The Controlled
Agricultural System according to the 1.sup.st aspect of "Fungi
Growth Inhibition", wherein the wavelength of the light of the
fungi prevention light source lies in a spectral range between 400
nm and 700 nm, in some embodiments/implementations between 600 nm
and 700 nm.
[0690] On the other hand, the plants themselves require a certain
dormant period, namely a night phase without agricultural lighting.
Therefore, it is not beneficial, or can be even outright
detrimental to illuminate the plants for 24 hours with the standard
agricultural lighting. In some embodiments/implementations, the
fungi prevention lighting has a reduced intensity and/or reduced
spectral range. In a preferred embodiment, the wavelength of the
fungi prevention light is at least 400 nm, particularly preferred
at least 600 nm. An advantageous upper limit can for instance be
700 nm. Using red light is presumably advantageous in view the
absorption behavior of the fungi.
[0691] Depending on the plants and fungi in detail, another
advantage using red light can be a certain penetration through the
leaves of the plants. In simple words, even by illuminating the
plants from above, a certain treatment of the lower sides of the
leaves as well as leaves at a lower position can be possible. In
general, the fungi prevention lighting can be applied from any
direction, from above, from the side, and/or from below. The light
can be brought to any location of the plants by using for instance
a light guide or optical fiber (see also "Light Guides").
[0692] With this disclosure, the use of fungicides can be
drastically reduced. In some countries, this option is even not
available, as certain fungicides are not permitted for use.
Treating fungus diseases with light furthermore allows to grow
plants organically and reduces crop loss. The concept of using a
night interrupting light treatment can be used for any plants, in
particular for fungi infecting herbs, medical plants or ornamental
plants.
[0693] 3.sup.rd aspect of "Fungi Growth Inhibition": The Controlled
Agricultural System according to the 1.sup.st or 2.sup.nd aspect of
"Fungi Growth Inhibition", configured for illuminating the plants
with the fungi prevention light source temporarily during the night
phase, namely during at least one interval.
[0694] In a preferred embodiment, the plants are only illuminated
temporarily during the night phase, namely during at least one
interval. This can reduce a negative impact or influence on the
plants themselves, which require the dormant period. The additional
illumination may be provided once during the night (e.g. in the
middle of the night) or at regular intervals (e.g. every hour) or
randomly during the night. In some embodiments/implementations, the
fungi prevention illumination is applied during a plurality of
intervals during the night phase. Therein, the duration of the
intervals themselves and/or the Off-time between the intervals can
be constant or can vary. Any variation can be distributed regularly
or randomly. Constant intervals are possible as well, the fungi
prevention illumination might for instance be applied every 2 hours
for one hour during night time.
[0695] 4.sup.th aspect of "Fungi Growth Inhibition": The Controlled
Agricultural System according to the 3.sup.rd aspect of "Fungi
Growth Inhibition", configured for illuminating the plants with the
fungi prevention light source in a plurality of intervals during
the night phase.
[0696] 5.sup.th aspect of "Fungi Growth Inhibition": The Controlled
Agricultural System according to the 4.sup.th aspect of "Fungi
Growth Inhibition", wherein an intensity of the illumination with
the fungi prevention light source is varied, a different intensity
being applied in different intervals.
[0697] In some embodiments/implementations, the fungi prevention
light source is dimmable, for instance in the range of 3-100
.mu.mol/(m.sup.2s). Likewise, the intensity of the fungi prevention
illumination can be varied, so that a different intensity is
applied in different intervals. A different intensity can be
applied for each interval, or the intensity can vary in groups.
Further, the intensity can also vary within an interval. In
particular, the intensity may be higher in the intervals at the
beginning of the night phase than at the end of the night phase, or
it may be higher at the end of the night phase than at the
beginning of the night phase. The maximum intensity may also be
reached in the middle of the night phase.
[0698] 6.sup.th aspect of "Fungi Growth Inhibition": The Controlled
Agricultural System according to any one of the 1.sup.st to the
5.sup.th aspect of "Fungi Growth Inhibition", configured for
applying a dark period with no illumination at the beginning of the
night phase.
[0699] 7.sup.th aspect of "Fungi Growth Inhibition": The Controlled
Agricultural System according to any one of the 1.sup.st to the
6.sup.th aspect of "Fungi Growth Inhibition", wherein the duration
of the dark period is at least 1 hour and not more than 4
hours.
[0700] 8.sup.th aspect of "Fungi Growth Inhibition": The Controlled
Agricultural System according to any one of the 1.sup.st to the
7.sup.th aspect of "Fungi Growth Inhibition", wherein the duration
of the night phase is at least 2 hours and not more than 10
hours.
[0701] In a preferred embodiment, a dark period with no
illumination is applied at the beginning of the night phase. In
some embodiments/implementations, the duration of the first dark
period is at least 1 hour and not more than 6 hours. In some
embodiments/implementations, the duration of the night phase itself
is at least 2 hours, further preferred at least 4 hours. Possible
upper limits are 10 hours, in some embodiments/implementations 8
hours at maximum. Together, the day and the night phase add up to
24 hours.
[0702] 9.sup.th aspect of "Fungi Growth Inhibition": The Controlled
Agricultural System according to any one of the 1.sup.st to the
8.sup.th aspect of "Fungi Growth Inhibition", wherein a total
illumination time with the fungi prevention light source (200)
during the night phase is not more than 2/3 of the duration of the
night phase.
[0703] In a preferred embodiment, a total fungi prevention
illumination time amounts to not more than 2/3 of the duration of
the night phase. Possible lower limits can for instance be at least
1/100, 1/50, or 1/10 of the duration of the night phase. In case of
an illumination in intervals, the total illumination time is
obtained by summing up the duration of the intervals.
[0704] 10.sup.th aspect of "Fungi Growth Inhibition": The
Controlled Agricultural System according to any one of the 1.sup.st
to the 9.sup.th aspect of "Fungi Growth Inhibition", comprising a
sensor device, the Controlled Agricultural System being configured
for illuminating the plants with the fungi prevention light source
depending on a measurement with the sensor device.
[0705] In a preferred embodiment, the fungi prevention illumination
is applied based on a measurement performed with a sensor device.
Infested plants can for instance be detected using a sensor like a
camera or the like, for instance in combination with a picture
recognition.
[0706] 11.sup.th aspect of "Fungi Growth Inhibition": The
Controlled Agricultural System according to any one of the 1.sup.st
to the 10.sup.th aspect of "Fungi Growth Inhibition", comprising an
additional fungi prevention UV light source for emitting UV light,
wherein the Controlled Agricultural System is configured for
illuminating the plants with the fungi prevention UV light source
at least temporarily during the night phase.
[0707] In a preferred embodiment, an additional fungi prevention UV
light source is provided. In some embodiments/implementations, the
plants are illuminated with UV light at least temporarily during
the night phase. The UV light can for instance be UV-A light
(380-315 nm), UV-B light (280-315 nm) and/or UV-C light (200-280
nm).
[0708] 12.sup.th aspect of "Fungi Growth Inhibition": The
Controlled Agricultural System according to the 11.sup.th aspect of
"Fungi Growth Inhibition", and in combination with the 4.sup.th or
5.sup.th aspect of "Fungi Growth Inhibition", wherein the plants
are not illuminated by the fungi prevention UV light source
in-between the intervals during the night phase.
[0709] 13.sup.th aspect of "Fungi Growth Inhibition": The
Controlled Agricultural System according to the 11.sup.th or
12.sup.th aspect of "Fungi Growth Inhibition", wherein the plants
are not illuminated by the fungi prevention UV light source in at
least one of the intervals.
[0710] In some embodiments/implementations, the plants are not
illuminated with the UV light source between two intervals, in
which the fungi prevention illumination is applied (e.g. red
light). Particularly preferred, no illumination at all is applied
between the intervals of the fungi prevention/UV illumination.
[0711] The fungi prevention illumination (in particular red light)
during the night phase has the goal to disturb the growth cycle of
the fungus, preventing it from growing and spreading. The
additional UV illumination may even destroy already existing
fungi.
[0712] If several illumination intervals are planned during the
night phase, at least one of them might also include UV only. The
fungi prevention time which uses UV-C-light may have a duration of
15 seconds to 1 minutes, whereas illumination with UV-A-light may
last from 5 minutes to 5 hours to inactivate spores. UV-light could
also be applied simultaneously with the red light. In some
embodiments/implementations, the total duration of the fungi
prevention illumination is longer than the duration of the UV
illumination.
[0713] In some embodiments/implementations, the fungi prevention
light source and/or the additional UV light source are integrated
into the lighting fixture for the agricultural lighting. In
general, the light source(s) can be controlled by a control unit,
which controls for instance the intensity, the illumination
duration of the light, and the dark periods between the
illuminations. The intensities and durations can be controlled
independently for the fungi prevention and the UV light source.
[0714] 14.sup.th aspect of "Fungi Growth Inhibition": The
Controlled Agricultural System according to any one of the 1.sup.st
or 13.sup.th aspect of "Fungi Growth Inhibition", configured for
varying an additional environmental parameter during the night
phase, in some embodiments/implementations at least one of
temperature and humidity.
[0715] In a preferred embodiment, an additional environmental
parameter is varied during the night phase, in some
embodiments/implementations temperature and/or humidity. The risk
of infestation of the plants by fungi is usually reduced by
reducing the population density, using a dry cultivation (i.e.
irrigation from below and possibly in the morning or only a few
larger water sprayings), introducing a time interval to a
subsequent crop cycle, preventing dew formation in the greenhouse
(emergency dry heating, use of fans), using hygienic measures, or
supplying balanced nutrients (e.g. avoiding nitrogen stress). If
the fungus has infested the plants, the infested plants are usually
removed immediately or treated with fungicides (if available).
[0716] 15.sup.th aspect of "Fungi Growth Inhibition": A Method for
Controlling an Agricultural System according to any one of the
1.sup.st to 14.sup.th aspect of "Fungi Growth Inhibition",
comprising the steps of applying agricultural lighting to the
plants during a day phase; and illuminating the plants with the
fungi prevention light source (200) at least temporarily during a
night phase.
[0717] Regarding further possible embodiments, reference is made to
the description above and also to the aspect relating to the system
of "Fungi Growth Inhibition".
[0718] It is also possible to adjust the nightly irradiation
composition (spectrum (blue, red, green, UV, IR), intensity) and
cycles (can be different for different light spectral/colors) for
plants into which a symbiotic fungus has been implanted (e.g. to
produce chanoclavine in the plant).
[0719] 16.sup.th aspect of "Fungi Growth Inhibition": Computer
program product, comprising a plurality of program instructions,
which when executed by a computing device of a Controlled
Agricultural System according to any one of the 1st to 14.sup.th
aspect of "Fungi Growth Inhibition", cause the Controlled
Agricultural System to execute the Method for Controlling a
Controlled Agricultural System according to the 15.sup.th aspect of
"Fungi Growth Inhibition".
[0720] The light treatment will be triggered by a control unit. The
command for the control unit can be given by a computing device
which either receives the command from the grower, or which
triggers the treatment automatically based on the detection of the
fungi by a sensor device. However, the treatment can also be
initiated prophylactically to avoid the growth of fungi on the
plants (e.g. every night, once a week or once a month). The
respective illumination durations, dark periods and illumination
intensities are stored in a database connected to or integrated
into the computing device. The treatment method described here
might be part of the overall control program of the light
source.
[0721] "Sensor Retrofit"
[0722] According to the element "Sensor Retrofit" of the
disclosure, a moveable irrigation device is equipped with a sensor
device for measuring plant parameters, particularly parameters
indicating health and growth stage of the plants.
[0723] 1.sup.st aspect of "Sensor Retrofit": An Agricultural
System, comprising a growth area for growing plants, an irrigation
device for irrigating plants grown on the growth area and a sensor
device, wherein the irrigation device is mounted moveable with
respect to the growth area, and wherein the sensor device is
mounted at the irrigation device and moveable with respect to the
growth area, thus.
[0724] The Agricultural System according to "Sensor Retrofit"
comprises an irrigation device moveable with respect to a growth
area (or cultivated area) and a sensor device mounted at the
irrigation device. When the irrigation device is moved over the
growth area for irrigating the plants grown there, the sensor
device is moved along with the irrigation device. Therefore, plants
grown at different locations or regions of the growth area can be
measured with the same sensor device.
[0725] Furthermore, most Agricultural Systems are equipped with an
irrigation device anyway. Thus, the movement unit, which moves the
nozzles over the growth area, is available already. The sensor
device can be attached or retrofitted to this existing setup, which
can be advantageous from an economical point of view as well. The
"irrigation device" may not only be used for watering purposes but
also for a treatment with fertilizers/pesticides or the like.
[0726] 2.sup.nd aspect of "Sensor Retrofit": The Agricultural
System according to the 1.sup.st aspect of "Sensor Retrofit",
wherein the sensor device is an optical sensor, in particular a
camera.
[0727] Many greenhouse growers are using an automated trolley as
irrigation device. The trolley usually includes a bar or rail or
arrangement of levers, which contains nozzles for irrigation or
spraying of fertilizers/pesticides. The sensor device can for
instance be a camera mounted to such a trolley, taking pictures of
the plant surface while the trolley is turning back and forth over
growth area, or other optical devices like a LiDAR (light detection
and ranging) Time-of-Flight measuring and sensor device (see also
"LiDAR Plant Surveillance", below). These pictures can help the
grower to find regularities and irregularities in the plant
population (growth, morphology, fruition, health condition). The
irrigation device can also be an irrigation robot, which can be
used indoors or outside in open fields or vineyards, or a vehicle
driving autonomously.
[0728] 3.sup.rd aspect of "Sensor Retrofit": The Agricultural
System according to the 1.sup.st or 2.sup.nd aspect of "Sensor
Retrofit", which is an indoor farm, the irrigation device being
mounted below a ceiling above the growth area.
[0729] Plant growth can be influenced by several parameters like
light intensity (photon flux), light spectrum, nutrients or
temperature. Especially when experimenting with new settings of
those parameters, a fast feedback about the plant growth, i.e. the
morphological parameters, is necessary. Plant growth can mean the
height of the plant, the size and number and orientation of the
leaves, the diameter of the plant, the plant morphology, etc.
[0730] However, even when the parameters to grow plants in an
agriculture system are set, a regular control if the plants are
growing as expected is necessary, as undetected changes in the
parameters, diseases or pests can affect the plant growth. It would
also be beneficial to track plant growth data or growth indicators
continuously, by day and night, and correlate the data to other
external parameters like temperature, nutrients, photon flux,
applied spectra, illumination ON and OFF cycles, etc.
[0731] 4.sup.th aspect of "Sensor Retrofit": The Agricultural
System according to any one of the 1.sup.st to 3.sup.rd aspect of
"Sensor Retrofit", wherein the irrigation device comprises a
horizontal rail with a plurality of nozzles provided along the
rail.
[0732] Usually, an irrigation device or trolley is made of metal
profiles, in particular aluminum profiles. In a preferred
embodiment of an in-house farm, the irrigation device is mounted
below a ceiling above the growth area. It can for instance hang on
a rod from the roof top. The sensor can be mounted to the
irrigation device with clips or clamps (by a form-fit or with
screws or the like). In some embodiments/implementations, the
irrigation device comprises a horizontal rail with a plurality of
nozzles provided along the rail.
[0733] In a preferred embodiment, the sensor device is an optical
sensor, in particular a camera. In general, other sensors are
possible, for example temperature sensors (creating for instance a
heat map) or ultrasound or LiDAR sensors to measure distances.
[0734] 5.sup.th aspect of "Sensor Retrofit": The Agricultural
System according to any one of the 1.sup.st to 4.sup.th aspect of
"Sensor Retrofit", comprising a plurality of sensor devices mounted
removably to the irrigation device.
[0735] 6.sup.th aspect of "Sensor Retrofit": The Agricultural
System according to the 5.sup.th aspect of "Sensor Retrofit",
wherein a distance between neighboring sensor devices amounts to
0.1 m at minimum and 1 m at maximum.
[0736] In a preferred embodiment, a plurality of sensor devices are
mounted at the irrigation device. A distance between neighboring
sensor along the trolley bar devices can for instance be at least
0.1 m and in some embodiments/implementations not more than 1 m. In
detail, the spacing between the sensor devices or cameras will for
instance depend on the mounting height and the angle of the lens of
the camera.
[0737] 7.sup.th aspect of "Sensor Retrofit": The Agricultural
System according to the 5.sup.th or 6.sup.th aspect of "Sensor
Retrofit", wherein at least one sensor device differs from another
sensor device in the parameter measured respectively.
[0738] 8.sup.th aspect of "Sensor Retrofit": The Agricultural
System according to the 7.sup.th aspect of "Sensor Retrofit",
wherein the sensor devices, which differ in the parameter measured,
are cameras with a different spectral sensitivity.
[0739] In some embodiments/implementations, at least some of the
sensor devices differ in the parameter measured respectively, for
instance cameras in their spectral sensitivity. The cameras can be
equipped with same or different lens systems in order to cover
various field-of-view settings and therefore different sensed or
surveilled plant areas. The lens systems can be adjustable, in some
embodiments/implementations by remote control. The cameras can be
equipped for daylight picture taking and/or for nighttime picture
taking using infrared-sensitive sensors. They can also be equipped
with an UV-protective cover that is transparent for visual and/or
infrared radiation. The cameras can also be equipped with cleaning
devices or with removable optically transparent protective covers
that can be cleaned, refurbished and so on.
[0740] In general, simple RGB cameras can be provided to create a
general overview of the entire plant canopy. However, also
multispectral or hyperspectral cameras can be used to measure e.g.
the chlorophyll fluorescence or the fertilization status. With each
passing of the irrigation device, pictures can be taken in
different wavelength ranges, e.g. in the IR, visible range (whole
spectrum or monochromatic) or UV. It is also possible that
neighboring cameras take pictures at different wavelengths during
one passing, e.g. the 1st, 4th, 7th, . . . camera takes pictures in
the visible range, the 2nd, 5th, 8th, . . . camera takes pictures
in the IR and the 3rd, 6th, 9th, . . . camera takes pictures at a
certain wavelength (monochromatic). Pictures can be taken at
regular time intervals or as a function of trolley speed that can
for example be in the range between 5 and 25 km/h. Of course, a
camera can also take videos for continuous surveillance and plant
tracking.
[0741] 9.sup.th aspect of "Sensor Retrofit": The Agricultural
System according to any one of the 5.sup.th to 8.sup.th aspect of
"Sensor Retrofit", wherein the sensor devices are provided along a
rail.
[0742] 10.sup.th aspect of "Sensor Retrofit": The Agricultural
System according to any one of the 4.sup.th to 9.sup.th aspect of
"Sensor Retrofit", wherein the rail with the sensor devices is
mounted at the horizontal rail with the nozzles, the rails
extending basically in parallel to each other.
[0743] In a preferred embodiment, the sensor devices are provided
along a rail. This inventive rail equipped with the sensor
devices/cameras, can be mounted to the existing structure (e.g. in
parallel to the existing rail with nozzles) in different ways. For
example, depending on the system, simple clips or clamps can be
used. If necessary, a crossbar (or a steel rope) can be used to
stabilize the structure.
[0744] 11.sup.th aspect of "Sensor Retrofit": The Agricultural
System according to any one of the 5.sup.th to 10.sup.th aspect of
"Sensor Retrofit", comprising a computing device configured for
collecting and merging the parameters measured by the sensor
devices, a parameter map of the growth area being generated by
merging the parameters.
[0745] A preferred Agricultural System comprises a computing device
configured for collecting and in some embodiments/implementations
merging the parameters measured by the sensor devices. Likewise, a
parameter map of the growth area can be generated.
[0746] 12.sup.th aspect of "Sensor Retrofit": The Agricultural
System according to any one of the 1.sup.st to 11.sup.th aspect of
"Sensor Retrofit", configured for measuring a respective position
of the irrigation device with respect to the growth area.
[0747] 13.sup.th aspect of "Sensor Retrofit": The Agricultural
System according to the 11.sup.th and 12.sup.th aspect of "Sensor
Retrofit", wherein the computing device is configured for
generating a 2-D or 3-D model from the position information and the
parameters measured by sensor device.
[0748] In general, each of the sensor devices/cameras can be
controlled individually. With this setup it is possible to create a
general overview of the entire surface, which can be analyzed by a
software. In addition, a 3-D picture can be generated by evaluating
or merging pictures from two or more cameras next to each other.
Due to the different angles, a simple 3-D model of the surface can
be calculated.
[0749] By calculating a 3-D model of the plants, data can be
collected about: [0750] i. Height [0751] ii. Shape [0752] iii.
Angle of leaves
[0753] On the other hand, by calculating a 2-D model, data can be
collected about: [0754] i. Coloration, which also can be
down-calculated to necrosis, virus or fungi disease [0755] ii.
Malformation of leaves [0756] iii. Number of flowers [0757] iv.
Missing plants [0758] v. Plant size [0759] vi. Plant height [0760]
vii. Plant diameter [0761] viii. Nutrition status of the plants
[0762] ix. Disease detection [0763] x. Water content
[0764] In some embodiments/implementations, the position of the
trolley will be measured to provide coordinates for the measured
values, in particular for the pictures taken. The calculation of
the position can be done using an (indoor) positioning system e.g.
based on Bluetooth beacons, or knowing a start-point of the trolley
and calculating the actual position based on the speed of the
trolley and the time passed and/or using marks (like an QR-code)
along the rail for positional checking and information input.
[0765] The measured parameters, in particular the picture data,
will be sent to a general control unit. The data transfer can be
wire-based (LAN, 5-core cable, or other existing cables for data
transfer) or wire-less. The data can be transferred to the
computing device via a control box or control unit. The latter can
be equipped with a Wi-Fi module, which transfers the data to the
computing device. A wire-based connection to the computing device
is possible as well. The computing device can be linked to or
comprise a climate control computer.
[0766] The computing device can be local (edge computing) or in the
cloud. The data will be processed and alerts, growth status, etc.
can be provided for instance on a dashboard to the grower. In case
of deviation from the predicted or expected growth, an alert will
be given. The alert can contain the kind of abnormality and where
the abnormality was detected, for example with positional
coordinates.
[0767] Data distribution and analysis can be performed using
Artificial Intelligence and Deep Learning methods. Data
distribution, analysis and data handling can use a blockchain
technology in order to generate a tamper-proof distributed
ledger-system. It is also possible to provide a low-resolution
picture, with the software marking the area in a specific color
where something is out of a normal behavioral condition or
biological setting. Depending on the intelligence of the system, it
can also give a recommendation to the user how to treat the
plants.
[0768] 14.sup.th aspect of "Sensor Retrofit": The Agricultural
System according to any one of the 1.sup.st to 13.sup.th aspect of
"Sensor Retrofit", configured for moving the irrigation device
forth and back over the growth area, wherein a measurement with the
sensor device is only performed during one pass of the irrigation
device.
[0769] 15.sup.th aspect of "Sensor Retrofit": The Agricultural
System according to the 14.sup.th aspect of "Sensor Retrofit",
wherein the irrigation device is moved forth in a first pass and
back in a second pass, and wherein the sensor device is moved ahead
the irrigation device during the first pass and the measurement is
performed during the first pass.
[0770] In a preferred embodiment, the irrigation device is moved
forth and back over the growth area. Therein, a measurement with
the sensor device is only performed during one pass of the
irrigation device, either during a first pass forth or during a
second pass back. In some embodiments/implementations, the
measurement (picture taking) is done when the sensor device(s)
is/are moving in front of the rail with the nozzles. The trolley is
usually moving twice across the field (back and forth), i.e. the
data can be collected either only during one pass of the trolley,
or during both passages.
[0771] 16.sup.th aspect of "Sensor Retrofit": The Agricultural
System according to any one of the 1.sup.st to 15.sup.th aspect of
"Sensor Retrofit", comprising a light source mounted at the
irrigation device and being moveable with respect to the growth
area, thus.
[0772] In a preferred embodiment, a light source is mounted at the
irrigation device. This can for instance be a high-power UV LED for
disinfection or a red/far-red source for night interruption. In
some embodiments/implementations, the light source is mounted to
the rail as well. Along the rail, a plurality of sensor devices can
be provided. For instance, each camera can be equipped with a
respective light source. The light sources can emit light at the
wavelength measured by the respective camera to improve the
brilliance. They can also emit light with a complementary color of
an expected disease reflectance as described in DE102018214676.
Furthermore, the light sources can also emit infrared light for
nighttime inspection with infrared-sensitive cameras.
[0773] 17.sup.th aspect of "Sensor Retrofit": The Agricultural
System according to any one of the 1.sup.st to 16.sup.th aspect of
"Sensor Retrofit", wherein the irrigation device and the sensor
device share a common power supply.
[0774] In a preferred embodiment, the irrigation device and the
sensor device share a common power supply. Alternatively, the power
supply of the sensor device can be realized via a small solar panel
with a battery on the top of the sleigh if no power supply is
available. In some embodiments/implementations, the common power
supply is implemented based on the existing infrastructure with an
electric control box above each irrigation trolley. The power
supply lines can go next to the irrigation pipes.
[0775] 18.sup.th aspect of "Sensor Retrofit": A Method for
Controlling an Agricultural System according to any one of the
1.sup.st to 17.sup.th aspect of "Sensor Retrofit", wherein the
irrigation device and the sensor device are moved over the growth
area, and a parameter is measured by the sensor device.
[0776] For instance, morphological or other parameters measured can
be analyzed by the computing device. The parameters and the result
of the analysis can be provided to the farmer or a customer. In
case of deviations, the system can automatically change a growth
parameter (e.g. illumination or temperature) or it can inform the
farmer or a customer (e.g. on a display about for instance the
actual growth, simulated growth, growth prognosis, AR (augmented
reality) or VR (virtual reality) representation, 2D and 3D plant
configuration, and so on).
[0777] 19.sup.th aspect of "Sensor Retrofit": A Computer program
product, comprising a plurality of program instructions, which when
executed by a computing device of an Agricultural System according
to any one of the 1.sup.st to 17.sup.th aspect of "Sensor
Retrofit", cause the Agricultural System to execute the Method for
Controlling according to the 18.sup.th aspect of "Sensor
Retrofit".
[0778] "LIDAR Plant Surveillance"
[0779] According to the element "LiDAR Plant Surveillance" of the
disclosure, the growth of plants is monitored by measuring the
decreasing distance between a distance-measuring device and the
growing plants.
[0780] 1.sup.st aspect of "LiDAR Plant Surveillance": More
specifically, a controlled agricultural system, comprises a growth
area for growing plants and a distance measuring device for
measuring a distance to an object in a detection field, the
distance measuring device being arranged in a relative position to
the growth area such that the detection field and the growth area
have at least an overlap.
[0781] The distance measuring device is oriented towards the growth
area of the agricultural system, for measuring the distance to the
plants grown there. For instance, it can be arranged above the
growth area, "looking" downward onto the latter. Then, the distance
measured will decrease the larger the plants become. In particular,
the distance measurement can enable a profile measurement giving
information on morphological parameters of the plants.
[0782] 2.sup.nd aspect of "LiDAR Plant Surveillance": The
controlled agricultural system according to the 1.sup.st aspect of
"LiDAR Plant Surveillance", the distance measuring device being
adapted for a time-of-flight distance measurement.
[0783] In a preferred embodiment, the distance measurement is a
time-of-flight distance measurement. In general, an ultrasonic
measurement is possible, even though a light-based measurement is
preferred, in particular with a LiDAR system. Therein, the term
"light" is not restricted to the visible part of the
electromagnetic spectrum, it also relates to UV and IR light, the
latter can even be preferred.
[0784] 3.sup.rd aspect of "LiDAR Plant Surveillance": The
controlled agricultural system according to the 1.sup.st or
2.sup.nd aspect of "LiDAR Plant Surveillance", the distance
measuring device comprising a light source for emitting light
pulses, in some embodiments/implementations laser pulses, and a
sensor device for detecting echo pulses returning from the
detection field after a reflection at the object.
[0785] A light source is provided for emitting the light pulses, in
particular a laser source, which in some
embodiments/implementations comprise one or more laser diodes. The
light/laser pulses are emitted into the detection field and are
reflected at the surface of the object(s) located there, for
instance at the leaves in case of the plants. The measuring device
further comprises a sensor for detecting the reflected pulses
returning from the detection field, namely for detecting the echo
pulses. From the time delay between the emission of the pulse and
the detection of the echo pulse, namely from the time of flight
.delta.t, the distance can be calculated (d=.delta.tc/2).
[0786] In the following some further characteristics of a preferred
LiDAR system are summarized:
[0787] The light source, in particular a laser, emits short light
pulses (typically with a pulse half-width between 0.1 ns and 100
ns, here preferred between 0.1 and 10 ns). The sensor, which can
also be sensor array, can for instance be a Photo-Diode, an
Avalanche Photo Diode (APD), a Single Photon Avalanche Diode
(SPAD), a PIN-Diode, or a Photo-Multiplier, it detects the echo
pulse. In some embodiments/implementations, infrared light is used
(wave length between 850 nm and 1600 nm, or larger), but visible or
UV-light can be used as well. The light source can emit the light
pulses with repeat frequencies between 1 kHz and 1 MHz, in some
embodiments/implementations between 1 kHz and 100 kHz (this gives a
pulse enough time to return back to the sensor; 2 .mu.s delay time
corresponds to a distance of 300 m, 1 .mu.s to 150 m, and 100 ns to
15 m). The light can be pulsed stochastically to filter out the
background illumination, which could be sunlight but also heat
radiation. This will improve the signal-to-noise ratio of the
signal.
[0788] 4.sup.th aspect of "LiDAR Plant Surveillance": The
controlled agricultural system according to the 3.sup.rd aspect of
"LiDAR Plant Surveillance", the distance measuring device being
adapted for a spatially resolved distance measurement.
[0789] In some embodiments/implementations, the distance measuring
device is adapted for a spatially resolved distance measurement
(referred to as "enhanced" system below). The detection field is
segmented into a plurality of segments, for each segment a distance
value is measured. This gives a distance image with a spatial
resolution, namely a three-dimensional picture of the environment,
in particular of the growth field.
[0790] 5.sup.th aspect of "LiDAR Plant Surveillance": The
controlled agricultural system according to the 4.sup.th aspect of
"LiDAR Plant Surveillance", the distance measuring device being
adapted for assigning the echo pulses received with the sensor
device to different solid angles of the detection field.
[0791] 6.sup.th aspect of "LiDAR Plant Surveillance": The
controlled agricultural system according to the 4.sup.th or
5.sup.th aspect of "LiDAR Plant Surveillance", the distance
measuring device being adapted for emitting the light pulses into
different solid angles of the detection field.
[0792] 7.sup.th aspect of "LiDAR Plant Surveillance": The
controlled agricultural system according to any one of the 4.sup.th
to 6.sup.th aspect of "LiDAR Plant Surveillance", the distance
measuring device being adapted for adapting the size of the
detection field to the growth area and/or a growth state of the
plants.
[0793] On the one hand, the spatial resolution can be achieved with
the sensor device. Therein, the sensor assigns the echo pulses
returning from the detection field to different solid angles. The
sensor or sensor array comprises several pixels, each detecting the
reflected light in a certain solid angle. This can for instance be
achieved with CCD or CMOS sensor combined with an optical system,
for instance a lens. The optical system guides the echo pulses from
the different solid angles onto different pixels, for instance
different areas of the CCD or CMOS array. Likewise, each pixel is
linked to a respective solid angle, and the echo pulse can be
assigned accordingly. In such a setup, the light/laser source can
for instance illuminate the whole detection field (area of
interest) in a flash mode.
[0794] On the other hand, the spatial resolution can also be
achieved by scanning the light/laser pulses across the detection
field, for instance by moving mirrors like MEMS-mirrors.
Accordingly, at a certain point in time, the light/laser pulse is
emitted in a certain solid angle (depending on the current tilt of
the mirror). Thereafter, the next pulse is emitted in another solid
angle, and so on. In this setup, the sensor can even consist of
just one sensor element with an optic which covers the whole
detection field (the sensor has no spatial resolution). However, as
the pulse is emitted in a certain solid angle, the measuring device
(or control/computing device connected thereto) knows from which
solid angle the detected echo pulse returned.
[0795] It is also possible to combine a sensor with a spatial
resolution and the scanning emission in a hybrid approach.
[0796] 8.sup.th aspect of "LiDAR Plant Surveillance": The
controlled agricultural system according to any one of the 4.sup.th
to 7.sup.th aspect of "LiDAR Plant Surveillance", the distance
measuring device being adapted for a spectrally resolved distance
measurement, namely for emitting and detecting light pulses having
a different wavelength.
[0797] In some embodiments/implementations, the distance measuring
device is adapted for a spectrally resolved distance measurement,
namely for emitting and detecting light pulses having a different
wavelength (referred to as "enhanced" system below). An enhanced
system can employ various wavelengths at the same time, then a
(segmented or multi-) sensor needs to have respective filters, or
apply the filters sequentially. Each wavelength could also use
another pulse-pattern, so that it can be differentiated from other
wavelengths. Using different wavelengths can provide additional
information, like leaf reflectivity, fluorescence radiation, e.g.
chlorophyll fluorescence. In the latter case, any subsequent pulse
needs to wait until a typical fluorescence or phosphorescence decay
time is over. Using light pulses having different infrared
wavelengths will help increase the Signal-to-Noise Ratio (SNR) or
the measured Lidar Pulses, since more measurement data can be used
for data measurement and processing, object recognition and
classification.
[0798] It is also possible to use laser radiation in the visible or
ultraviolet wavelength range for the described scanning
application. Therefore, the term LIDAR includes laser radiation in
the entire wavelength range from Ultraviolet to Infrared.
[0799] Using visible laser radiation in the visible wavelength
range can be used to detect and measure not just plant morphology
but also biological or chemical plant features and health
conditions.
[0800] Early disease detection for plants is important, especially
in a closed environment like a vertical farm, where diseases can
spread easily. Different kinds of diseases or stress can cause
different symptoms at a plant, for example on plant leaves, petals,
stem or roots. Some can lead to a reduced growth of the plant,
others, like the Tobacco mosaic virus, which can infect tobacco,
pepper, tomato and cucumber, mainly cause "mosaic"-like mottling
and discoloration on the leaves. Causes of discolorations,
depending on plant type, can for example be caused by lack of
nutrients or lack of chemical elements like Nitrogen (N), Phosphor
(P), Potassium (K), Sulfur (S), Manganese (Mn), over-supply of
nutrients, too much light, too rapid temperature changes, lack of
air circulation, too dry air, too much irrigation, bacterial and
virus infestation causing for example bacterial blight and
bacterial wilt, soil contamination, soil temperature and many
others. In addition to discoloration effects, plant leaves can
develop holes.
[0801] It is known to use cameras to observe plants and detect
color changes that could be associated with diseases, i.e. the
discolored parts have changed from their naturally provided colors
(according to their actual growth stage) to a changed color
impression, therefore they have become discolored. Discolorations
can affect only parts or small segments of a plant body (stem,
petals, leaves) or greater areas. However, some of these color
changes, particularly in an early stage of a disease, only affect
small parts of the leaves, or the contrast between the discolored
part and the normal colored part is small, thus making it easy to
overlook the discolored areas. The aspect "Plant Surveillance"
targets to intensify the contrast between discolored and normal
colored parts of a plant.
[0802] Furthermore, some color changes (discoloration) signal a
next stage of ripening, e.g. the change of color in fruits. For
instance, tomatoes discolor from green to red while ripening,
eventually triggering harvesting.
[0803] It is therefore possible to use such a LIDAR scanning system
(as described above) in a Controlled Agricultural System for plant
breeding and cultivating, particularly for detection of plant
diseases and various stages of ripening, comprising by using a data
storage device comprising data, which are related to spectra of
light, particularly of light with colors complementary to colors of
parts of plants (Complementary Color Spectrum CCS), for example,
complementary to discolored areas or parts of plants, an LIDAR
illumination device able to emit light with a color spectrum
according to the data stored in the data storage device and
illuminate plants, a sensor device able to detect the light
reflected by the illuminated plants, a computing device configured
to control the illumination device based on the data of the
database, and further configured to analyze the data from the
sensor device and detect dark areas on the plants.
[0804] 9.sup.th aspect of "LiDAR Plant Surveillance": The
controlled agricultural system according to any one of the 1.sup.st
to 8.sup.th aspects of "LiDAR Plant Surveillance", wherein the
distance measuring device (200) is arranged in a distance from the
growth area of 30 m at maximum.
[0805] In a preferred embodiment, the distance measuring device is
arranged in a distance of 30 m maximum from the growth area, in
some embodiments/implementations 25 m, 20 m, 15 m or 10 m at
maximum (possible lower limits are for instance at least 2 m, 4 m
or 5 m). A LiDAR system can reach a resolution of a few millimeters
at a distance of about 10 meters. This resolution is sufficient to
detect morphological parameters of plants like biomass, size, leave
size, flowers (number and size), etc., future systems will even
provide a better resolution.
[0806] 10.sup.th aspect of "LiDAR Plant Surveillance": The
controlled agricultural system according to any one of the 1.sup.st
to 9.sup.th aspects of "LiDAR Plant Surveillance", which is an
indoor farm, the distance measuring device being mounted below a
ceiling above the growth area.
[0807] 11.sup.th aspect of "LiDAR Plant Surveillance": The
controlled agricultural system according to any one of the 1.sup.st
to 10.sup.th aspects of "LiDAR Plant Surveillance", comprising a
light fixture for illuminating at least a part of the growth area,
wherein the distance measuring device is a part of the light
fixture.
[0808] In a preferred embodiment, the Controlled Agricultural
System is an indoor farm, for instance a greenhouse or vertical
farm. To detect morphological (and other) parameters, the
LiDAR-system (or enhanced-LiDAR system with spectral/spatial
resolution) can be attached at an elevated place in the greenhouse
or vertical farm, it can be mounted below a ceiling above the
growth area, either at the ceiling itself or at a scaffold. The
LiDAR-system can also be integrated into a light fixture which is
provides artificial lighting to the growth area; the LiDAR-system
can for instance be arranged in the housing of the light
fixture.
[0809] In a simple approach, one (enhanced) LiDAR-system attached
in the center of the greenhouse could be sufficient to get a rough
overview. However, installations in the greenhouse like lighting
fixtures might block the laser pulses and the (enhanced) LiDAR
system will only measure a plant from one direction.
[0810] In general, the distance measuring device (LiDAR-system) can
be mounted movably for capturing the growth area from different
sides. It can for instance move along a track in a vertical farm.
In a vertical farm, the plants grow on shelves in racks, the
LiDAR-system could then move along the rack to measure the plants
on each shelf.
[0811] 12.sup.th aspect of "LiDAR Plant Surveillance": The
controlled agricultural system according to any one of the 1.sup.st
to 11.sup.th aspects of "LiDAR Plant Surveillance", the distance
measuring device being immovably mounted in its relative position
with respect to the growth area.
[0812] In some embodiments/implementations, the distance measuring
device (LiDAR-system) is mounted immovably (in an immobile manner)
with respect to the growth area. In comparison to the prior art
mentioned above, this mounting is far less complex. With a
LiDAR-system, the light can be flashed or scanned over the entire
detection field/growth area, whereas in the prior art the whole
sensor system has to be moved across the growth area. A
LiDAR-system does not need a movable, mechanical support and can
continuously measure a much wider area.
[0813] 13.sup.th aspect of "LiDAR Plant Surveillance": The
controlled agricultural system according to any one of the 1.sup.st
to 12.sup.th aspects of "LiDAR Plant Surveillance", comprising an
additional distance measuring device for measuring a distance to an
object in a detection field, in some embodiments/implementations by
a light pulse time-of-flight distance measurement, the distance
measuring devices being arranged to capture different regions of
the growth area and/or to capture the growth area from different
points of view.
[0814] In a preferred embodiment, the Controlled Agricultural
System comprises an additional distance measuring device for
measuring a distance to an object in a detection field, in some
embodiments/implementations an additional LiDAR-system. The
LiDAR-systems are arranged to capture different regions of the
growth area and/or to capture the growth area from different points
of view. Using several LiDAR-systems in a vertical farm or
greenhouse can enable the creation of a full view of the plants. In
a simple approach, an (enhanced) LiDAR-system is attached close to
one of the four corners of a greenhouse. From this perspective, the
whole area of interest can be covered. If the line of sight of one
(enhanced) LiDAR is constrained, an (enhanced) LiDAR from another
angle can cover this area. In addition, the plants can be measured
from all angles, creating a 360.degree.-view of the plant
morphology.
[0815] When a plurality of LiDAR-systems are provided, each can
scan the whole growth area (e.g. the full view the system is able
to scan). The detection field can even be larger than the growth
area. A computing device, either a local or a central device, can
distinguish the growth area from other parts of the greenhouse/farm
(e.g. walls). The computing device can then reduce or adapt the
scanned area for each LiDAR-system so that it only covers the area
of interest ("commissioning").
[0816] In a preferred embodiment, the Controlled Agricultural
System is configured for a time-synchronized measurement with the
different distance measuring devices/LiDAR-systems. The control
unit or computing device of the Agricultural system activates the
LiDAR-systems at a specific point in time or at specific points in
time--for example during illumination with light emitted by the
regular horticulture lighting fixtures with a specific color, or
with a specific spectral intensity or other photometric values,
like photosynthetically active radiation (PAR) or Photon Flux, or
only during a dark time period (no lighting), or after the plants
have been treated with UV-radiation--in the greenhouse or
horticultural indoor farm in an interleaved mode (i.e. one after
the other) to avoid that one LiDAR-system interferes with a second
LiDAR-system, leading to a "false" signal.
[0817] 14.sup.th aspect of "LiDAR Plant Surveillance": The
controlled agricultural system according to the 13.sup.th aspects
of "LiDAR Plant Surveillance", wherein the additional distance
measuring device is adapted for emitting and detecting light pulses
having another wavelength than the light pulses emitted and
detected by the first distance measuring device.
[0818] In a preferred embodiment, the distance measuring
devices/LiDAR-systems are equipped for operating in different
spectral regions. Each sensor (IR, UV, visible) is connected to a
computing device (via its control unit). Since different
wavelengths are used, the signals from another (wrong) LiDAR light
source can be ignored by the sensor (e.g. by using a
wavelength-filter).
[0819] 15.sup.th aspect of "LiDAR Plant Surveillance": The
controlled agricultural system according to the 13.sup.th or
14.sup.th aspect of "LiDAR Plant Surveillance", being configured
for a clocked and/or time-synchronized measurement with the
distance measuring devices, one after the other.
[0820] In a preferred embodiment, the Controlled Agricultural
System is configured for a clocked measurement with the different
distance measuring devices/LiDAR-systems. The control unit or
computing device of the Agricultural system activates the
LiDAR-systems in the greenhouse in an interleaved mode (i.e. one
after the other) to avoid that one LiDAR-system interferes with a
second LiDAR-system, leading to a "false" signal.
[0821] 16.sup.th aspect of "LiDAR Plant Surveillance": The
controlled agricultural system according to the 13.sup.th to
15.sup.th aspect of "LiDAR Plant Surveillance", comprising a
computing device configured for merging distance images taken by
the distance measuring devices.
[0822] 17.sup.th aspect of "LiDAR Plant Surveillance": The
controlled agricultural system according to the 16.sup.th aspect of
"LiDAR Plant Surveillance", comprising a reference point in a
defined relative position with respect to the growth area, the
computing device being configured for merging the distance images
by means of the reference point.
[0823] Each LiDAR-system will provide a three-dimensional set of
(time-sequential) pictures, from its point of view. Different
wavelength ranges are possible, but not mandatory. To create a
three-dimensional picture of each plant, the pictures of the
LiDAR-systems need to be mapped over each other. To map them, the
system in some embodiments/implementations uses a reference point.
This reference point can be an object in the greenhouse and the
respective distances are calculated from this object.
Alternatively, the reference point can be the walls of the
greenhouse. The computing device receives the information from the
LiDAR-system how far a plant is away from the opposite wall, and it
knows the distance between the walls of the greenhouse.
[0824] The height of a plant is measured with respect to the upper
surface of the soil. Usually, the plants do not cover the whole
soil, so that this information should be available any time.
However, the system can make a reference measurement before the
first plant is planted, so that the correct height of the plant can
be calculated even if the plants cover the soil completely.
[0825] The detected morphological parameters will be analyzed by
the computing device. The parameters and the result of the analysis
can be provided to the farmer or a customer. In case of deviations,
the system can automatically change a growth parameter (e.g.
illumination or temperature) or it can inform the farmer or a
customer (e.g. on a display about for instance about the actual
growth, simulated growth, growth prognosis, yield forecast, AR or
AV representation, and so on). Such a system is able to measure
even at night as to detect night behavior (e.g. also after a
nightly UV-exposure).
[0826] It is also possible for a LiDAR system to recognize other
objects inside a greenhouse or vertical farm, like humans,
agribots, animals, and so on and provide a movement pattern of the
other object. It is also possible for a LiDAR system to measure the
movement and/or location of a plant or product along a moving belt
or tray, allowing correct identification of the product.
[0827] Furthermore, according to "LiDAR Plant Surveillance", a
method for agricultural management is proposed, which is intended
for controlling a controlled agricultural system as described
above.
[0828] 18.sup.th aspect of "LiDAR Plant Surveillance": More
specifically, the method for agricultural management, comprises at
least one controlled agricultural system, wherein plants are grown
at the growth area, and wherein the plants are captured by a
distance measurement performed with the distance measuring
device.
[0829] 19.sup.th aspect of "LiDAR Plant Surveillance": The method
according to the 18.sup.th aspect of "LiDAR Plant Surveillance",
wherein a reference measurement of the growth area (203) is
performed before the plants are grown at the growth area.
[0830] 20.sup.th aspect of "LiDAR Plant Surveillance": Computer
program product, comprising a plurality of program instructions,
which when executed by a computing device of a Controlled
Agricultural System according to any one of the 1.sup.st to
17.sup.th aspects of "LiDAR Plant Surveillance", cause the
Controlled Agricultural System to execute the Method for
Controlling an Agricultural System according to the 18.sup.th or
19.sup.th aspect of "LiDAR Plant Surveillance".
[0831] The growth and health of plants can be monitored according
to any of the aspects of the disclosure described above or a
combination of various aspects. For example, growth and health of
plants may be monitored by combining any or all of the aspects of
"Stress Detection", "Discolored Spots Detection", "Sensor Retrofit"
and "LiDAR Plant Surveillance". Additionally, potentially critical
situations may be detected according to the aspects of
"Prophylaxis". The results of the monitoring, i.e. the probability
that something detrimental may have happened to the plants, based
on the aforementioned aspects may be further analyzed according to
the aspects of "Disease & Pest Control". Finally,
countermeasures may be taken according to the aspects of "Fungi
Growth Inhibition".
[0832] Light/Growth Recipes
[0833] "Temperature Dependent Illumination"
[0834] It is an object to provide an advantageous Agricultural
System. This problem is solved by an Agricultural System comprising
at least two light fixtures at different locations and being
configured for applying a different illumination with these light
fixtures at the different locations based on a temperature value
measured. In detail:
[0835] 1.sup.st aspect of "Temperature dependent illumination": A
Controlled Agricultural System comprising:
[0836] at least two light fixtures for providing agricultural
lighting,
[0837] a sensor device for measuring a temperature value,
[0838] wherein the light fixtures are arranged at different
locations in the Agricultural System,
[0839] and wherein the Agricultural System is configured for
applying a different illumination with the light fixtures at the
different locations based on a temperature value measured.
[0840] The "temperature value" can be the actual temperature,
measured for instance in K, .degree. C. or .degree. F. The
temperature can be measured by any kind of a thermal sensor
(Electric, Resistance, Pyrometer, Piezo, etc.). In this respect,
the "temperature value" can be any type of output signal of a
thermal sensor, which relates to the temperature, for instance an
electrical current or voltage. At the "different locations" for
instance trays or bowls can be provided, in which the plants are
grown. The different locations can in some
embodiments/implementations lie on a different height respectively,
for instance on different shelves. In some
embodiments/implementations, the different locations are arranged
in the same building, particularly preferred in the same room.
[0841] Accordingly, the light fixtures and locations can be spaced
vertically, for instance in a vertical farm. Vertical farm
buildings can have heights of 10, 20, 30 or more meters and contain
dozens of shelves from the ground to the top in which the plants
(includes Food Crops, Floriculture, Cannabis) are growing. Each
shelf usually contains its own lighting fixture. Efforts to
construct especially designed vertical farms are sometimes
summarized under the term Agritecture.
[0842] The inventors observed that horticultural light fixtures can
produce a certain amount of heat, even in case of LED light
sources. The control systems of vertical farms may try to keep a
constant (vertical) temperature in the building. However, due to
the large number of light fixtures and other electrical equipment
producing heat and due to the large dimensions of typical vertical
farms, it is unavoidable, that the temperature under the ceiling is
higher than on the ground (as warm air is lighter and moves up).
Therefore, the temperature conditions in soil and air (and possibly
also the water irrigation temperature) is different at different
height levels.
[0843] Temperature, however, has an influence on the growth of
plants. Some plants like petunia or verbena for instance need less
time to flowering the higher the temperature is. However, petunia
grow faster the higher the temperature is, whereas verbena grow
faster the lower the temperature is. Other plants like salvia have
a maximum growth rate at about 22.degree. C., whereas they grow
slower for higher and lower temperatures.
[0844] An approach here is to influence the growth by applying a
different illumination depending on the temperature. In particular,
the growth at different locations can be synchronized by applying
for instance a higher DLI value where the temperature is lower, and
vice versa. However, in general, the methodology also allows
application of certain lighting conditions at given local
temperatures in order to reach other growth targets, like
super-fast growth, or super-slow growth for instance (see also
"Customer Request").
[0845] 2.sup.nd aspect of "Temperature dependent illumination": The
Controlled Agricultural System according to the 1.sup.st aspect of
"Temperature dependent illumination", wherein the illumination
applied with the light fixtures at the different locations differs
in at least one of a DLI value and a spectral composition.
[0846] The "Daily light integral" (DLI) describes the number of
photosynthetically active photons (individual particles of light in
the 400-700 nm range) that are delivered to a specific area over a
24-hour period.
[0847] Further, in terms of the different illumination, different
light spectra may be applied at different temperatures. For
instance, red light can be of interest at a specific temperature
(e.g. 12-19.degree. C.) and blue light at another specific
temperature (e.g. 20-25.degree. C.). The red light can affect the
activation of phytochrome, the blue light can affect the activation
of phototropin and cryptochrome. Additional effects may be
generated when applying red or blue light at different humidity
levels, e.g. red light irradiation at a cultivation atmosphere
humidity level of 40% to 90% and blue light irradiation at a
humidity level of 40% to 90%.
[0848] Plant growth during various growth cycles can be strongly
influenced by the applied light spectra, for example, cucumber and
lettuce plants reach greater length and/or mass when illuminated
with the inventive horticultural light that includes far red light
(700-800 nm).
[0849] So, one solution is to adjust the spectral ratios of a
horticulture lamp (LED) as a function of ambient temperature. For
example, the Far-Red radiation content (better: the Far-Red related
Photosynthetically Active Photon Flux Density, PPFD or PFD measured
in .mu.mol/(m.sup.2s), or the Far-Red related Applied Daily Light
Integral (DLI) or the Far-Red related Daily Light Applied Spectrum
Integral (DLASI), can be properly adjusted, e.g. for every
3.degree. C. temperature increase a reduction of 5-30% compared to
the lower temperature level. Of course, as described above, also
the DLI values can be additionally adjusted.
[0850] 3.sup.rd aspect of "Temperature dependent illumination": A
Controlled Agricultural System according to the 1.sup.st or
2.sup.nd aspect of "Temperature dependent illumination", configured
for applying a higher DLI value with the lighting fixture at that
location at which the temperature is lower.
[0851] 4.sup.th aspect of "Temperature dependent illumination": The
Controlled Agricultural System according to any of the 1.sup.st to
3.sup.rd aspect of "Temperature dependent illumination", wherein
the locations are spaced vertically, namely are arranged on a
different height respectively.
[0852] 5.sup.th aspect of "Temperature dependent illumination": The
Controlled Agricultural System according to the 4.sup.th aspect of
"Temperature dependent illumination", configured for applying a
higher DLI value at that location, which is arranged at a lower
height.
[0853] Due to the temperature difference in a vertical farm, the
growing behavior of plants at higher height levels (especially
underneath the ceiling) will differ from the growing behavior on
the middle levels or on the ground (at lower temperatures), which
will lead to different plant growth morphologies, different
harvesting times and possibly also to different plant ingredients
(vitamins, THC, enzymes, glucose, etc.) for the same plant.
Temperature distribution is of course also influenced by the
applied cooling conditions and the day/night illumination cycles
(ON/OFF).
[0854] A sensor device is provided for measuring the (local)
temperature settings, in particular inside a vertical farm building
or the like, in order to apply favorable growth influencing
conditions (as explained above). Basically, even a single sensor
device could be sufficient, for instance an infrared camera
allowing a temperature measurement at different locations at the
same time. In some embodiments/implementations, a plurality of
local sensor devices are provided.
[0855] 6.sup.th aspect of "Temperature dependent illumination": The
Controlled Agricultural System according to the 4.sup.th or
5.sup.th aspect of "Temperature dependent illumination", comprising
a plurality of light fixtures on a different height respectively,
wherein the Controlled Agricultural System is configured for
measuring a temperature value at least at an uppermost and a
lowermost location.
[0856] Accordingly, all or at least some of the locations can be
equipped with a respective sensor device. In particular, the sensor
device can be integrated into the lighting fixture. Lighting
controllers can be placed locally at the lighting fixture or
remotely.
[0857] As mentioned, in a vertical farm, a plurality of light
fixtures (locations) are provided on a different height
respectively, for instance at least 3, 5, 8, 10, 12, 14, 16, 18 or
20 light fixtures (locations). Possible upper limits can for
instance be 1.000, 500, 200 or 100 different vertical locations.
The vertical locations can be provided on a shelf respectively,
each shelf comprising a plurality of horizontal locations on the
same height level, equipped with an own lighting fixture
respectively.
[0858] 7.sup.th aspect of "Temperature dependent illumination": The
Controlled Agricultural System according to the 6.sup.th aspect of
"Temperature dependent illumination", configured for applying, with
at least one lighting fixture arranged vertically in between the
uppermost and the lowermost location, an illumination based on an
interpolation of the temperature values measured at the uppermost
and the lowermost location.
[0859] It is possible to use a linear (or non-linear) temperature
profile by just measuring the temperatures at the bottom and at the
top of a building and interpolating in between. Of course,
depending on the number of temperature measuring points, any kind
of reasonable mathematical interpolation can be used.
[0860] Such a desired temperature profile may be dependent on
external weather conditions (adjustment time), but this is then
already reflected in the actual local temperature measurement. Of
course, it is necessary to apply a certain (characteristic)
illumination for heat generation, either in a standard setting
(DLI, spectrum) or otherwise properly selected. Once measured, such
temperature data can be fed into a computer system and proper
lighting conditions can be calculated and applied for each
plant.
[0861] In a basic approach, the temperature profile may only be
measured after quite long time intervals like hours, or only once
per day.
[0862] In a more sophisticated approach, the actual local
temperatures (LTik) (I=height index, k=positional index at that
height, like position on a shelf) at different elevations (height
levels) are regularly measured by various kinds of thermal sensors
(Electric Resistance, Pyrometer, Piezo, etc.) and a vertical
temperature profile (TPik) can be generated. It is preferred that
such temperature sensors are built into the light fixtures.
[0863] As mentioned above, measured local data (LTik) can be stored
into a Data Bank (DB). Likewise the actually applied lighting
conditions (CLik) (either measured or per lighting
program/sequence). The measurement of the applied lighting
conditions can contain a variety of parameters (DLI, spectral
ratios, and so on, as explained above). Measurements can be done
e.g. at preselected time intervals (like seconds, minutes, hours),
or irregularly. Once measured, such data can be fed into a computer
system and proper lighting conditions can be calculated and applied
(intermediate approach).
[0864] In an even more sophisticated approach, also the actual
local plant growth parameters can be measured, like plant height,
plant morphology, plant chemistry, plant leaf density index, plant
color and other growth and ripening indicative parameters with
various measurement techniques (destructive and non-destructive,
see for instance "LiDAR for plant measurement" or also "Measuring
patterns"). These data will then be stored as well into a data bank
(Growth Parameters GPik). The Growth Parameters are compared to
target growth values and the proper lighting conditions are chosen
to reach the harvesting goal with respect to the actual growth
parameters and the actual temperature profile. (high-level
approach).
[0865] 8.sup.th aspect of "Temperature dependent illumination": The
Controlled Agricultural System according to any of the 4.sup.th to
7.sup.th aspect of "Temperature dependent illumination", comprising
a plurality of light fixtures on a different height respectively,
wherein the Controlled Agricultural System is configured for
measuring temperature values at all vertical locations to obtain a
vertical temperature profile.
[0866] 9.sup.th aspect of "Temperature dependent illumination": The
Controlled Agricultural System according to the 8.sup.th aspect of
"Temperature dependent illumination", wherein, on each height
respectively, a plurality of light fixtures are provided at
different horizontal locations, wherein the Controlled Agricultural
System is configured for measuring a temperature value at the
horizontal locations respectively to obtain a horizontal
temperature profile.
[0867] 10.sup.th aspect of "Temperature dependent illumination":
The Controlled Agricultural System according to one of the
preceding aspects, wherein at least one of the light fixtures
comprises a sensor device for measuring a temperature value at the
location of that lighting fixture.
[0868] 11.sup.th aspect of "Temperature dependent illumination":
The Controlled Agricultural System according to one of the
preceding aspects, comprising a computing device, configured to
compare the data measured by the sensor device with a reference
data set and to apply an illumination based on the result of the
comparison.
[0869] 12.sup.th aspect of "Temperature dependent illumination": A
Method for Controlling an Agricultural System which comprises at
least two light fixtures arranged at different locations at which
the same plants are grown, the method comprising the steps of
[0870] measuring a temperature value at at least one of the
locations; [0871] applying a different illumination at the
different locations based on the temperature value measured.
[0872] 13.sup.th aspect of "Temperature dependent illumination":
The Method according to the 12.sup.th aspect of "Temperature
dependent illumination" for controlling a Controlled Agricultural
System according to any of the 1.sup.st to 11.sup.th aspect of
"Temperature dependent illumination".
[0873] 14.sup.th aspect of "Temperature dependent illumination": A
Computer program product, comprising:
[0874] a plurality of program instructions, which when executed by
a computing device of a Controlled Agricultural System according to
any one of the 1.sup.st to 12.sup.th aspect of "Temperature
dependent illumination", cause the Controlled Agricultural System
to execute the Method for Controlling according to the 12.sup.th or
13.sup.th aspect of "Temperature dependent illumination"
[0875] 15.sup.th aspect of "Temperature dependent illumination": A
Method for Generating a Data Set for a Controlled Agricultural
System according to one of the 1.sup.st to 11.sup.th aspect of
"Temperature dependent illumination" or for a Method according to
the 12.sup.th or 13.sup.th aspect of "Temperature dependent
illumination" or for a Computer program product according to the
14.sup.th aspect of "Temperature dependent illumination", the
Method comprising the steps of [0876] growing a plurality of plants
and applying a defined temperature and illumination to the plants,
wherein, in groups respectively, the temperature and the
illumination differs; [0877] measuring a growth parameter of the
plants respectively.
[0878] "Temperature dependent illumination" also relates to a
method for generating a data set for controlling an Agricultural
System. For generating this data set, a plurality of plants are
grown, wherein a defined temperature and illumination is applied.
Therein, the temperature and illumination differs in groups. In
particular, several different temperatures are defined and several
different illumination setups are defined. With each temperature
and illumination combination, one or in some
embodiments/implementations more plants are investigated by
monitoring a growth parameter. In some embodiments/implementations,
for generating the data set, conspecific plants are grown and
divided into groups with different temperature/illumination.
[0879] Such an evaluation can measure and assess for instance the
necessary DLI levels (illumination setup) in order to reach the
same Time to Flower Rate (growth parameter) at various temperature
settings within a given (defined) temperature range, see Table 1
for illustration (for Petunia Coral Pink). Such relationships can
be done with all plants and stored into a database. The database
then allows producers to adjust the DLI levels (increase, keep,
decrease) appropriately in order to synchronize (or at least
minimize the time difference) the temperature and DLI-dependent
Time to Flower. By the same methodology, however more complicated,
also other factors can be taken into account, like Spectral
Distribution and its adaptive adjustment, spectral ratios (like
UV-B to Far-Red), humidity and others.
[0880] 16.sup.th aspect of "Temperature dependent illumination":
The Method according to the 15.sup.th aspect of "Temperature
dependent illumination", wherein a correlation function between the
temperature and the illumination is obtained from the growth
parameters measured.
[0881] Apart from the Time to Flower, the "plant growth" measured
can for instance also be the plant height, plant morphology, plant
chemistry, plant leaf density index, plant color and other growth
and ripening indicative parameters with various measurement
techniques (destructive and non-destructive). These data will then
be stored as well into a data bank (Growth Parameters GP).
[0882] Of course, plant growth can depend on many factors that can
be evaluated by the method described, like the [0883] i. applied
light spectrum, [0884] ii. applied Photosynthetically Active
radiation (PAR) [0885] iii. Photosynthetically Active Photon Flux
Density, PPFD or PFD measured in .mu.mol/(m.sup.2s), [0886] iv.
applied Daily Light Integral (DLI) or the Daily Light Applied
Spectrum Integral (DLASI). [0887] v. the change of light spectra,
[0888] vi. the ratios of spectra e.g. the ratio of blue to Far-Red;
or the ratio between UV-A and Far-Red [0889] vii. the illumination
times with specific light spectra, [0890] viii. duration and change
between simultaneous or sequential illumination with different
spectral distributions, [0891] ix. amount and timing of UV-B
irradiation, [0892] x. day-night-cycles
[0893] By the same methodology, however more complicated, also
other factors can be considered, like applied temperature periods,
i.e. temperature profiles, duration, change and so on. Though
complicated, growth influencing relationship can be found. Of
course, a variety of mathematical methods and computer simulation
including neuronal learning and other artificial intelligence
techniques can be used to find proper relations. A skilled person
can find out many more of these influencing parameters by proper
research.
[0894] Of course, it is understood, that the actual local
temperatures (LT) are dependent on cooling conditions, air
circulation, air humidity, actual light illuminating recipes at
each shelf, and so on, generating complex interactive temperature
interdependencies with complex feedback loops.
[0895] A Data Bank (DB) can for instance hold: [0896] i.
Temperature Profiles (LTik, TPik) [0897] ii. Lighting conditions
CLik [0898] iii. Growth Parameters GPik
[0899] All these data can be used by a suited computer program
(software) to calculate the best Lighting Conditions for the actual
local temperature conditions in order to minimize deviation of
growth parameters at different local temperatures and/or to
influence plant growth otherwise.
[0900] The compute unit can also calculate (or extrapolate) time to
harvest based on any applied temperature, e.g. a temperature on the
ground level of a vertical farm, or on the top level. The compute
unit can also communicate this information to third parties: user,
provider, etc.
[0901] "Adaptive Spectrum"
[0902] It is an object of this element of the disclosure to provide
an agricultural system or method, which, on the one hand, enables
an illumination of the plants with a specific light customized to
the respective plant type. On the other hand, it is an object to
optimize the energy consumption of the system or facility.
[0903] 1.sup.st aspect of "Adaptive Spectrum": A controlled
agricultural system, comprising
[0904] a growth area for growing plants,
[0905] a sensor device for a measurement of an ambient spectrum of
an ambient light (second light) incident on the growth area,
and
[0906] a light fixture,
[0907] wherein the agricultural system is configured [0908] to
establish a difference spectrum between the ambient spectrum of the
ambient light and a target spectrum (third light) on the basis of
the measurement of the sensor device, and [0909] to trigger the
light fixture to emit an additional light (first light) with an
additional spectrum,
[0910] wherein a superposition (superimposed light) of the first
light and the second light is spectrally closer to the target
spectrum (third light) than the ambient spectrum.
[0911] A respective "spectrum" can for instance cover the entire
spectrum or only a spectral range of the respective light. A
spectral range can for instance extend over at least 20 nm, 50 nm,
or 80 nm (possible upper limits being for instance 1000 nm, 800 nm,
600 nm, 400 nm, or 200 nm). A "spectrum" can be continuous or
quasi-continuous, or it can consist of discrete values at discrete
wavelengths (e.g. at least one value per nm). For comparing
spectra, for instance a radiant flux related value, e.g. the
radiant flux itself (in Watt) or the irradiance (W/m.sup.2) or
radiant intensity (W/sr) or radiance (W/m.sup.2/sr), plotted over
the wavelength (e.g. in nanometer) can be evaluated (plotted in a
linear coordinate system). The spectrum resulting from the
superposition of the additional and the ambient spectrum, namely
the superimposed spectrum, shall be closer to the target spectrum
(third light) than the ambient spectrum. In other words, a
difference between the target spectrum and the superimposed
spectrum shall be smaller than a difference between the target
spectrum and the ambient light. Therein, at a respective
wavelength, the absolute value (modulus) of the respective
difference value is taken.
[0912] In some embodiments/implementations, the ambient light is
natural light, in particular sunlight. In general, the natural
light can be the light available at day or also during the night.
In case that sunlight is available, e.g. in terms of daytime and
weather, it is incident on the growth area. For this purpose, the
growth area of the agricultural system or facility can for instance
be a arranged in a glasshouse. However, the sunlight could be also
guided to the plants via light tubes or the like.
[0913] The sensor device allows for a spectral measurement, namely
for measuring a radiant flux related value at different
wavelengths. Such a spectral measurement is important, because the
growth or thrive of the plants can depend on the flux or intensity
in specific spectral ranges, see the "Examples of Light Recipes"
below. Measuring for instance only a color of the ambient light
would not be sufficient, because different spectral compositions
can result in the same color.
[0914] 2.sup.nd aspect of "Adaptive Spectrum": The controlled
agricultural system of the 1.sup.st aspect of "Adaptive Spectrum",
wherein the superimposed light corresponds to the third light.
[0915] As far as possible in terms of technical accuracy, the
resulting light (ambient+first light) has the same spectral
composition as the target light. In other words, the first spectrum
of the first light is basically identical to the difference
spectrum.
[0916] 3.sup.rd aspect of "Adaptive Spectrum": The controlled
agricultural system of the 1.sup.st or 2.sup.nd aspect of "Adaptive
Spectrum", configured for an operation in which the first light
has, at least temporarily, a share of at least 10% at the
superimposed light.
[0917] Further lower limits can for instance be at least 20%, 30%,
or 40%. Therein, for instance the irradiance of the first light and
the superimposed light are compared. Even though a complete
substitution (100%) is possible, preferred upper limits can for
instance be 90% or 80% at maximum (at least temporarily, in the
supplementation mode). The ambient light (second light) having a
certain share at the superimposed light can be advantageous in
terms of the energy consumption.
[0918] The goal of "Adaptive Spectrum" is to obtain the spectrum of
the target light, at least approximately and in some
embodiments/implementations to the best possible extent. Only
setting the correctly perceived color of the light (given by the
color coordinate in a CIE diagram, for example) with the aid of the
additional light is insufficient in the agricultural sector; this
is because a color can be represented in different ways, i.e., by
different spectra (for example, yellow light can be represented by
a spectrum of yellow light or by a spectrum containing red and blue
components). However, the accurate spectrum is important for the
growth of the plants in the agricultural sector.
[0919] 4.sup.th aspect of "Adaptive Spectrum": The controlled
agricultural system of any of the 1.sup.st to 3.sup.rd aspect of
"Adaptive Spectrum", wherein the light fixture comprises at least
two different light sources adapted for emitting light with
different spectral properties.
[0920] These light sources differ in their spectral properties.
Their peak intensities can for instance lie at different
wavelengths and/or the spectral distribution can differ (narrowband
or broadband). In some embodiments/implementations, the different
light sources can be light-emitting diodes, see in detail
below.
[0921] 5.sup.th aspect of "Adaptive Spectrum": The controlled
agricultural system of the 4.sup.th aspect of "Adaptive Spectrum",
the agricultural system being configured for adjusting the
intensity of the at least two different light sources individually,
namely independently of each other.
[0922] Likewise, a very flexible supplementation of the ambient
light is possible. In other words, the target spectrum can be
reached under various ambient light conditions.
[0923] As mentioned, the ambient light can for instance be
sunlight. However, it can also be artificial light or a
superposition of sunlight an artificial light. Possible fields of
application of "Adaptive Spectrum" may for instance be: greenhouses
(in particular glasshouses), indoor farming or portable growing
units, in which the plants (agricultural plants) are irradiated by
a second light which, for example, may be the sunlight and/or
artificial illumination (e.g., from adjacent or the surrounding
regions, too).
[0924] Typically, the second light is not constant. For instance,
the sunlight has a certain daily cycle and a yearly cycle,
depending on geographic position. Moreover, further influencing
variables can influence or change the characteristics of the
available sunlight, such as, e.g., the formation of clouds, fine
dust, rain, snow, etc. Depending on longitude and latitude, the
sunlight has a daily color temperature response. In the morning and
in the evening, it has a color temperature of approximately 1800 to
2200 K, it has a color temperature of approximately 5500-6500 K at
noon, it has a color temperature of approximately 5500 K at 3.00 pm
and it has a color temperature of approximately 4300 K in the
evening. The color temperatures lie approximately on or near the
Planck curve. The intensity and also the spectrum may change in the
case of cloud cover, fog, etc.
[0925] The spectral range from 400 to 800 nm is most important for
the growth of plants. Said range comprises blue (b) radiation
(400-500 nm), green (g) radiation (500-600 nm), red (r) radiation
(600-700 nm) and dark red (dr) radiation (700-800 nm). The photon
flux (PF) of the photosynthetically active radiation (PAR) emerges
from the sum of the individual photon fluxes PFb, PFg, PFr, PFdr.
Daylight may have a ratio of PFb:PFg:PFdr=0.27:0.35:0.38.
[0926] With the developments of light-emitting diodes (LEDs),
radiation sources that emit substantially in monochromatic fashion
and radiation sources with a wavelength conversion element
(phosphor) have become available. Depending on the embodiment, LED
light sources can emit in the ultraviolet, visible or infrared
spectrum. The wavelengths of the emission radiation can be
accurately set by means of quantum dot LEDs. Organic LEDs (OLEDs),
electroluminescence light sources, electrodeless induction lamps
and mercury-free dielectric barrier discharge lamps can also be
used as a light module. The light sources can have a compact or
areal embodiment and can be equipped with primary and secondary
optics, such as lenses, light guides, stationary and movable
reflectors or radiation-reflective optical devices, holographic
elements, partly transparent or completely light-opaque films,
heat-reflecting films, luminescent films. Furthermore, use can be
made of laser light sources, in particular those that produce white
or colored light by means of LARP (laser-activated remote phosphor)
technology. Consequently, a multiplicity of light sources are
available for illuminating the plants and the entire radiation
spectrum (UV, visible, IR) can be covered.
[0927] In particular, the agricultural system may comprise a
computing device connected to the sensor device. The computing
device may be configured to establish the difference spectrum
between the spectrum of the ambient light and the target spectrum
on the basis of the measurement values of the sensor device.
Further, the agricultural system may comprise a control unit, the
light fixture being connected to the control unit and the control
unit being connected to the computing device. The control unit may
be configured to convert the previously established difference
spectrum into control signals for the light fixture. Likewise, the
light fixture can be triggered to emit the additional light (first
light) to supplement the ambient light.
[0928] 6.sup.th aspect of "Adaptive Spectrum": The controlled
agricultural system of any of the 1.sup.st to 5.sup.th aspect of
"Adaptive Spectrum", configured to restrict an evaluation of the
ambient light to wavelengths at which an intensity is designated in
the target spectrum.
[0929] This can be achieved by a software or a hardware solution.
For instance, even the sensor device itself can be configured to
restrict the measurement of the ambient spectrum of the ambient
light to the different wavelengths.
[0930] 7.sup.th aspect of "Adaptive Spectrum": The controlled
agricultural system of any of the 1.sup.st to 6.sup.th aspect of
"Adaptive Spectrum", wherein the light fixture comprises LEDs and
the agricultural system is configured to restrict an evaluation of
the spectrum of the ambient light to intensity maxima of the LEDs
of the light fixture.
[0931] In some embodiments/implementations, the sensor device is
configured to restrict the measurement of the spectrum of the
ambient light to these intensity maxima.
[0932] It is not the entire spectrum of the available illumination
that is measured; instead, the measurement is restricted to the
intensity maximums of the LEDs installed in the light fixture. The
width of the wavelength range in the measurement may be fixed
around the maximum in this case (e.g., +/-25 nm); however, it may
also be determined by the curve of the peak, and so the boundaries
lie where the intensity has fallen to a certain value (1/10 or 1/e)
of the maximum.
[0933] Now, the actual intensity of the second light is measured in
these regions, said intensity is compared to the desired intensity
and the intensity of the LEDs can be determined by simply forming
the difference.
[0934] It is possible to also apply this concept to other reference
variables, for example to artificial light sources, the light
properties of which change over time and which can be filled
accordingly by means of the adaptive additional illumination. Thus,
the "ambient light" (second light) can be natural light (direct or
indirect sunlight) but also artificial light or a mixture of
artificial and natural light.
[0935] If the missing parts of the target spectrum (spectrum, light
intensity, etc.) are identified in the target area, then it is
possible to provide the missing/supplemental parts of the spectrum
in a targeted and energy saving manner, said missing/supplemental
parts of the spectrum filling the second light spectrally with the
desired intensity or further characteristics in order to obtain the
target spectrum.
[0936] 8.sup.th aspect of "Adaptive Spectrum": The controlled
agricultural system as described in any of the preceding aspects of
"Adaptive Spectrum", wherein the sensor device comprises one sensor
or a plurality of sensors.
[0937] The controlled agricultural system therefore comprises at
least one light fixture (agricultural light fixture) with at least
one light source and a sensor or an arrangement of sensors (sensor
device), by means of which the locally available second light
spectrum (in the target area) can be analyzed in respect of
composition and intensity, etc. Here, the spectrum means a region
from UV to infrared or far infrared, i.e., approximately 100 nm to
100 000 nm (i.e., also including thermal radiation). The spectrum
of the available illumination can be analyzed, for example in
region increments of 1 nm, of 10 nm or of 50 nm (i.e., it is not
the continuous intensity that is recorded; instead, the intensity
of the spectrum is digitized in certain ranges).
[0938] 9.sup.th aspect of "Adaptive Spectrum": The controlled
agricultural system as described in any one of the preceding
aspects of "Adaptive Spectrum", wherein the target spectrum
corresponds to a light recipe for irradiating produce, in
particular a plant.
[0939] Then, the measurement data are compared to the stored
reference variables and supplied to a program. The program runs on
a computing device, which may be part of the controlled
agricultural system or which may else be cloud-based. Moreover, the
controlled agricultural system comprises a control unit (light
control unit), which actuates the light sources of the at least one
light fixture on the basis of the data of the computing device and
optionally modifies these appropriately. Here, different light
fixtures may also receive different actuation data.
[0940] 10.sup.th aspect of "Adaptive Spectrum": The controlled
agricultural system as described in any one of the preceding
aspects of "Adaptive Spectrum", comprising an interface for weather
forecast data for a predictive adaptation of the additional light
to the weather-dependent change in the sunlight (ambient
light).
[0941] A "prediction" or "predictive adaption" can for instance be
based on or implemented by Artificial Intelligence.
[0942] 11.sup.th aspect of "Adaptive Spectrum": A method for
agriculture, including the following method steps:
[0943] measuring the spectrum of an ambient light (second light)
incident on a target area, in particular a growth area for growing
plants,
[0944] establishing a difference spectrum between the spectrum of
the ambient light and a target spectrum (third light),
[0945] triggering an emission of an additional light (first light),
which has an additional spectrum,
[0946] wherein a superposition (superimposed light) of the first
light and the second light is spectrally closer to the target
spectrum (third light) than the ambient spectrum.
[0947] For establishing the difference spectrum, the spectrum of
the ambient light is compared with the target spectrum (spectrum of
the third light). The first light emitted then has, at least
approximately, the spectral composition of the difference spectrum
to fill this gap. In particular, this can be achieved by way of a
suitable actuation of a light fixture. Then, the growth area
(target area) is irradiated with the produced additional light, in
addition to the ambient light.
[0948] The spectrum of the second light (ambient light) is compared
to the spectrum of the target light that should be used to
illuminate the plants. Ideally, the spectrum is available using the
same type of description as the measured spectrum, in this example
as intensities in a wavelength range (if the spectrum is available
as a continuous spectrum, the corresponding value can easily be
calculated by way of the area of the intensity present in this
wavelength range). Thus, the differences in the intensity can be
determined for the individual ranges (e.g., using the method of
least squares) and the control unit can actuate the light fixture
accordingly so that the plants are irradiated by the required
intensity in the determined wavelength ranges. Thus, the light
fixture provides an additional light (=first light), which
complements the second light (the already available ambient light)
to form the target light. Moreover, provision can be made for the
additional light to be adapted to the spectral changes of the
ambient light (e.g., path of the sun, seasons, etc.) and/or of the
predeterminable target light.
[0949] Apart from the spectral properties, also other light
parameters can be measured, for instance the polarization and/or
irradiation angle.
[0950] 12.sup.th aspect of "Adaptive Spectrum": The method as
described in the 11.sup.th aspect of "Adaptive Spectrum", including
the additional method step of:
[0951] measuring the spectrum of the additional light,
[0952] comparing the spectrum of the additional light to the
established difference spectrum,
[0953] adapting the spectrum of the additional light if the
deviation between the measured spectrum of the additional light and
the difference spectrum exceeds a tolerance range.
[0954] The spectrum of the second light can be measured with
spatial resolution over the irradiation surface and the respective
differences to the respective local target light can be calculated,
for example using the method of least squares. Local differences
can likewise be averaged in order to establish an overall
difference for the entire illuminated region and in order thus to
set the first light accordingly. In addition to local averaging,
provision can also be made for an averaging of the individual
differences and of the overall difference over time.
[0955] The sensor or sensors can also measure the light of the
light fixtures. To this end, the light fixture radiation can be
briefly modulated, for example, and so a measuring device can
distinguish the artificial light from the natural light. This can
ensure that the light output by the light fixture corresponds to
the desired difference between the second light and the target
light. If this is not the case, there is a corresponding correction
(i.e., the intensity of the corresponding LED of the light fixture
is adapted).
[0956] 13.sup.th aspect of "Adaptive Spectrum": The method as
described in the 7.sup.th aspect of "Adaptive Spectrum", wherein
the additional light is modulated during the measurement of the
spectra for the purposes of distinguishing it from the ambient
light.
[0957] The measurement of the spectrum of the second light and
thesssss calculation of the additional light can be implemented
after certain time intervals, for example every second, every
minute, etc. The time interval can be designed differently
depending on, e.g., the color temperature or other influencing
variables (light intensity, polarization, weather).
[0958] The spectrum of the additional light (first light) can be
adapted as soon as the spectrum of the target light and the
spectrum of the second light differ or the measured spectrum of the
additional light and the difference spectrum differ, or else only
once the difference exceeds a tolerance range.
[0959] In a further configuration, it is possible to take account
of not only the current spectrum of the second light (i.e., the
ambient light) but also a prediction in the light change when
creating the first light (i.e., the additional light/light fixture
light). For the good growth of the plant, also receiving the
necessary daily light integral (DLI) in addition to the correct
spectrum over the day is important. To this end, the controlled
agricultural system can obtain information about a weather forecast
(data provided by a weather station), and so the further change in
the second light can be predicted (i.e., the system has an
interface to a weather forecast provider). For example, should the
forecast suggest that it will be cloudy during the day, irradiation
of the plants can already be started at an earlier time, for
example already at 4 o'clock with primarily red light.
[0960] "Flexible Growth"
[0961] In automated plant production (e.g. in a greenhouse or in a
vertical farm), one or more control units can regulate or control
the plant production, for example the production process (planting,
fertilizing, watering, illuminating, quality monitoring, etc.).
[0962] Further examples of processes that can be controlled by
control units are the ordering process for precursor materials
(seeds, fertilizer, etc.), the supply-demand requirements (customer
wishes, customer orders, delivery dates and on-time delivery,
cancellations, complaints), and taking account of economical and
ecological points of views (e.g. energy consumption, goods storage
and delivery). Respective control units may also be combined in a
superordinate control unit, which then consists of a plurality of
such sub-system units, such as, e.g., an interface to the customers
(order and delivery platform, complaints, cancellations), an
interface to the energy producers (cost control, energy
availability), an interface to the actuation unit for the light
fixtures or the applied light programs (growth-dependent
illumination recipes), an interface to the precursor material
suppliers, an interface to the transport and storage logistic
companies, an interface to a data acquisition and evaluation unit
(computing center, software), and more.
[0963] The growth behavior of the products, the yield (mass,
number) and for example a target time, e.g. the harvest or delivery
time can be predicted. Such a prediction can be possible based on
growth recipes defining growth parameters, as for instance the
growth cycle as a fixed parameter.
[0964] However, as discussed in "Flexible Growth", it could be
interesting to adapt the target time, e.g. harvesting time, in line
with external requirements arising for instance in the supply
chain. It can be an interesting approach to consider for example
the workload in downstream facilities (food producers) but also in
upstream facilities (precursor materials).
[0965] 1.sup.st aspect of "Flexible Growth": A Method for operating
a controlled agricultural system, wherein
[0966] plants are grown,
[0967] a growth recipe is applied to the plants,
[0968] wherein the growth recipe delivers a growth cycle, namely a
target time for the growth of the plants,
[0969] and wherein further
[0970] the growth recipe is amended prior to reaching the target
time;
[0971] wherein, due to the amendment of the growth recipe,
[0972] i) the growth cycle is shortened or extended, and
[0973] ii) a quality value of the plants is altered, and/or
[0974] iii) a production value of the agricultural system is
altered.
[0975] In a sense, the measures or results of the items i) to iii)
are conflicting targets. For instance, assuming that iii) remains
unchanged, an improvement of item i), namely a shortening of the
growth cycle, will result in a deterioration of a quality value,
for instance in terms of the plant's color or morphology. The
approach of "Flexible Growth" is to consider or take into account
these interdependencies of the different measures and to amend the
recipe, e.g. depending on external requirements. Such requirements
can for instance be the workload in a subsequent facility
processing the crop or the crop quality required currently in such
a facility (which can vary and depend e.g. from the crop quality of
other farms).
[0976] 2.sup.nd aspect of "Flexible Growth": The Method of the
1.sup.st aspect of "Flexible Growth", wherein a quality value of
the plants is altered, namely a vitamin content, a color parameter,
or a morphology parameter.
[0977] For instance, the vitamin content can be increased to
compensate a poor crop quality of another farm. On the other hand,
a reduced vitamin content could be found to be acceptable in case
that the growth cycle shall be shortened, e.g. to optimize the
workload in the supply chain. In general, shifting the target time,
in particular the harvest time, can for instance help avoiding
overcapacities and undercapacities in the supply chain. A product
(fruits, vegetables, cut flowers, medical plants) may be required
earlier, or else later. Although, alternatively, a delay could be
offset by storage, a disadvantage arising in the process could be
that contents are degraded, i.e. the quality suffers.
[0978] 3.sup.rd aspect of "Flexible Growth": The Method of the
1.sup.st or 2.sup.nd aspect of "Flexible Growth", wherein a
production value of the agricultural system is altered, namely an
energy consumption of the agricultural system.
[0979] 4.sup.th aspect of "Flexible Growth": The Method of the
3.sup.rd aspect of "Flexible Growth", wherein the growth cycle is
shortened and a production value of the agricultural system is
impaired.
[0980] 5.sup.th aspect of "Flexible Growth": The Method of any of
the preceding aspects of "Flexible Growth", wherein the growth
cycle is shortened and a quality value of the plants is
impaired.
[0981] Impairing a color parameter can for instance mean that a
leaf or fruit color pales, for example from green or red to a pale
color tone. Impairing the vitamin content means that less vitamins
are contained in the plants, and impairing a morphology parameter
can for instance mean that the stem diameter is reduced or the
branching is negatively affected.
[0982] 6.sup.th aspect of "Flexible Growth": The Method of any of
the 1.sup.st to 3.sup.rd aspect of "Flexible Growth", wherein the
growth cycle is extended.
[0983] Usually, keeping the growth cycle as short as possible is a
superordinate target in agriculture. In this case, it is
intentionally extended, for example to avoid overcapacities and
undercapacities in the supply chain, see above.
[0984] 7.sup.th aspect of "Flexible Growth": A controlled
agricultural system for making plant growth flexible,
comprising
[0985] an acquisition unit for acquiring the change of the delivery
date for a product of a plant,
[0986] actuators configured to act on the plant growth,
[0987] a control unit connected to the actuators and configured to
identify the plants affected by the change in delivery date,
[0988] a computing device connected to the acquisition unit and the
control unit and configured to establish modified control
parameters for the actuators on the basis of the determined current
growth status in such a way that the desired state (degree of
maturity) of the product is obtained at the time of the amended
delivery date.
[0989] 8.sup.th aspect of "Flexible Growth": The controlled
agricultural system of the 7.sup.th aspect of "Measuring Patterns",
the computing device being configured for executing a method
according to any of the 1.sup.st to 6.sup.th aspect of "Flexible
Growth".
[0990] The embodiment facilitates monitoring and control of the
growth of the plants. To this end, the controlled agricultural
system comprises a control unit, which monitors and controls the
growth of the plants. As a result, it becomes easier to flexibly
react to changes in customer queries and to adapt the harvest time
or delivery date. A digital supply chain (software platform) can be
filled depending on the customer queries and dates, and plants are
planted so that they are mature in timely fashion. Here, the
supply-demand interface can serve as a marketplace, in which supply
and demand are matched to one another and the market prices are
established. The platform closes contracts and ensures transparency
along the supply chain.
[0991] The change in target time can be triggered by an amended
customer query. Depending on the notice for the change in delivery
date, it is possible to delay or accelerate germination, growth or
maturing of the product. This is implemented by way of suitable
changes of, for example, parameters such as light spectra, light
intensity, CO.sub.2 content, water/nutrient supply or temperature
(air, water, ground, plant root, plant blossom, plant leaves, etc.)
by way of suitable actuators (such as light fixtures, watering
facilities, heaters, cooling devices, fertilizer applicants). In
the case of a change in the customer-related delivery date, the
plants affected thereby are identified by the control unit. To this
end, whole growing units (in the case of a large order, for
example) can be provided with an ID, for example a QR code, but
also the smallest individual sale units, such as plant pots,
planting bowls, etc.
[0992] 9.sup.th aspect of "Flexible Growth": The controlled
agricultural system of the 7.sup.th or 8.sup.th aspect of "Flexible
Growth", comprising
[0993] sensors connected to the control unit and configured to
determine the growth phase of the plants.
[0994] Moreover, the growth phase of these customer-related plants
or the amount of, e.g., light and/or temperature that they have
already taken up, for example also temperature without light, i.e.,
in darkness, are determined. The individual values, the number of
individual values or else the sum of individual values (time
integral, power integral) are acquired in the process. Here, the
acquired information items can be very multilayered since
growth-related parameters are a function of a plurality of
influencing factors, such as for example: applied light spectrum,
applied photosynthetically active radiation (PAR), applied
photosynthetically active photon flux density (PPFD or PFD,
measured in .mu.mol/(m.sup.2s)), applied daily light integral (DLI)
or daily light applied spectrum integral (DLASI), or the ratios of
the spectral intensities of blue to dark red, or of UV-A to dark
red, the number and duration of the changes between two different
illumination states, the radiation dose of UV-A and UV-B radiation,
and many more.
[0995] These information items can be kept in a growth log for each
growing unit. In order to determine the current growth phase,
provision may also be made of optical sensors, for example cameras,
or else other sensors such as chemical sensors, spectrally
sensitive sensors or thermal sensors. Here, the phrase growth phase
comprises all stages of the plant growth, including the maturing of
possible fruits (e.g., fruit, vegetable, fungi, plants, etc.) of
the plant.
[0996] Moreover, the amounts still required by the plants or grown
products, for example in respect of the irradiation (spectral
photon fluxes) and/or temperature and dark times (see above in
respect of further influencing factors), until they have reached
the state provided for delivery (e.g., customer-specified degree of
maturity) are determined.
[0997] 10.sup.th aspect of "Flexible Growth": The controlled
agricultural system of any of the 7.sup.th to 9.sup.th aspect of
"Flexible Growth", wherein the computing device is connected to a
database which, for a respective plant, stores what change of a
control parameter can bring about a certain delay or acceleration
or standstill of the growth.
[0998] The running control program is interrupted and replaced by a
delay or acceleration program, or holding program, which use
parameters (spectrum, temperature, CO.sub.2 and more) that have
been modified on the basis of the values established above in order
to correspondingly delay or hold the growth of the plants (later
delivery date) or accelerate this (earlier delivery date). Here,
the computing device of the controlled agricultural system in some
embodiments/implementations accesses a database that has available
appropriate plant-specific information items (e.g., a change in the
parameter x leads to delay of the growth by y hours). From these
information items, the computing device calculates a suitable
modification of the parameters in order to produce the desired
acceleration or delay, or the desired holding state, of the plant
growth. In this calculation, it is possible to take account of
which plant parameters (color, size, content, etc.) were
particularly important to the customer such that the newly
calculated parameters do not change these plant parameters where
possible (keeping customer-critical plant parameters).
[0999] Acceleration programs can be accompanied by a higher light
dose (e.g., a higher DLI, see above) and/or a higher proportion of
red and dark-red radiation. Acceleration programs may also use
other dark periods, e.g., shorter dark periods, and also set or
change brief irradiation during dark periods. Acceleration programs
can increase the nutrient supply and the fertilizer supply, and
also appropriately adapt watering, ventilation, room temperature,
etc.
[1000] Delay programs can be accompanied by a lower light dose
(e.g., a lower DLI, see above) and/or a lower proportion of red and
dark-red radiation. Delay programs may also use other dark periods,
e.g. longer dark periods, and also prompt or modify the brief
irradiation during dark periods. Delay programs may reduce the
nutrient supply and the fertilizer supply, and also appropriately
adapt watering, ventilation, room temperature, etc.
[1001] Holding (standstill) programs modify the parameters in such
a way that the current state of the plants is largely
maintained.
[1002] Depending on the shift in date, a calculation is carried out
as to how long the modified control program should be used until
the standard control program can be used again. Optionally, the
modified control program is also used until harvest.
[1003] 11.sup.th aspect of "Flexible Growth": A method for
agriculture, comprising:
[1004] a controlled agricultural system as described in any one of
the preceding aspects and the following method steps:
[1005] acquiring the change in the delivery date for a product of a
plant with the aid of the acquisition unit,
[1006] identifying the affected plants with the aid of the control
unit, and
[1007] determining the current growth status of the affected plants
with the aid of the sensors or by way of the growth log,
[1008] calculating the modified control parameters by the computing
device on the basis of the determined current growth status and the
state of the product to be obtained at the time of the modified
delivery date,
[1009] actuating the actuators with the modified control parameters
by the control unit (acceleration or holding or delay program).
[1010] 12.sup.th aspect of "Flexible Growth": The method for
agriculture as described in the 11.sup.th aspect of "Flexible
Growth", wherein
[1011] the modified control parameters are calculated in such a way
that they delay or accelerate the germination, the growth or the
maturing of the affected plants or of the product (fruit) of the
plants.
[1012] The market prices (supply-demand) can be noted at regular
intervals and the control program may be updated accordingly under
certain circumstances. Conceivable scenarios include: [1013] If an
order is canceled and another customer whose order data can be met
with a modified growth program (control program) is found, the
modified growth program (control program) is applied. [1014] If
another customer is found and there still is sufficient time for a
new seed in respect of the modified customer order, there is no
delay, but the new customer is served. In particular, this may be
the case if the new customer does not require mature plants at all
but only cuttings. Then, a new production is carried out for the
modified customer order. [1015] If need be, the first production
can be accelerated for the other customer and the original customer
can be served with a likewise accelerated, subsequent
production.
[1016] 13.sup.th aspect of "Flexible Growth": The method for
agriculture as described in the 11.sup.th or 12.sup.th aspect of
"Flexible Growth", including the additional method steps of:
observing the market conditions, adapting the delivery date to the
current market conditions.
[1017] 14.sup.th aspect of "Flexible Growth": A method for
agriculture if the original purchase date for a product is delayed
by the customer, including the following method step: calculating
whether a slowdown of the production or storage of the finished
products would be more cost-effective.
[1018] It is also possible to calculate whether a delay of the
production or storage would be more cost-effective. Possibly, the
production is then carried out as planned and stored since a delay
additionally occupies the production area (opportunity costs).
[1019] It is also possible to calculate whether a production can be
influenced in corresponding fashion at another automated plant
production and can be assigned to the customer order.
[1020] "Plant Movement"
[1021] 1.sup.st aspect of "Plant Movement": An Agricultural Light
Fixture, particularly for use in a Controlled Agricultural,
comprising:
[1022] multiple light modules, each light module comprises at least
one light source and at least one driver connected to the at least
one light source;
[1023] wherein the light modules are controllable individually or
in groups.
[1024] Plants need nutrients and light to grow. However, to grow
strong, they also need to move to strengthen their stems or shoots,
in particular the stem fibers. One possibility to induce a movement
is to create a certain airflow or wind gusts in a greenhouse or a
vertical farm, which simulates the airflow that plants would
experience in an open field.
[1025] Phototropism is the influence of light on the growth of
plants. It can be positive, like for sprouts, or negative, like for
roots, i.e. the plants (stem, leafs, blossom) can move and/or bend
towards the light or away from the light respectively. Plant
growth, growth direction and morphology can also be influenced by
irradiation the plant with polarized light.
[1026] It is not only that the light fixture or fixtures can
illuminate the plants alternatively from opposite directions or be
moved linearly across a plant growth area, but that also the
intensity and/or of the illumination spectrum can be changed, in
particular both together. This can be done with the whole lighting
fixture arrangement or also a single light fixture, in order to
maximize a phototropic effect in combination with or as a function
of plant growth, plant morphology and plant ripeness.
[1027] 2.sup.nd aspect of "Plant Movement": The Agricultural Light
Fixture according to the 1.sup.st aspect of "Plant Movement",
wherein at least one light module is configured to be able to emit
light with various intensities and/or spectra.
[1028] The maximum intensity values at both sides of the
agricultural light fixture or a fixture arrangement can be adjusted
to the needs of the plants; the intensity values do not need to be
equal at both sides but can vary over time
[1029] Furthermore, the agricultural light fixture may be
configured to have two different intensities: One maximum intensity
and one "standard" intensity (which is lower than the maximum
intensity). The agricultural light fixture may as well be
configured that its intensities can change gradually between a
maximum and a minimum value. The difference between maximum and
minimum needs to be sufficient to activate the phototropism of the
plants. Furthermore, the values for maximum and minimum intensity
and their respective durations may be adapted to the required DLI
(day light integral) for each plant.
[1030] Furthermore, the agricultural light fixture may comprise
multiple areal sections that are configured to emit light with
different intensities and/or spectra. There could be a left section
of the light fixture with a first lighting setting, for example to
irradiate plants in the morning cycle with light having a reddish
color temperature at about 4000 to 2000 K, a middle section that
emits light with a midday daylight having a color temperature of
5000 to 10000 K, and a right section that emits light with a color
temperature of about 4000 to 2000 K (sunset condition), depending
on the geolocation.
[1031] Furthermore, the left and right sections of the agricultural
light fixture may be configured to be able to incline or adaptively
incline in order to emit light to the plants at a certain (varying)
irradiation angle thus mimicking the position of the natural
sunlight (circadian condition). Of course, similar cycles may be
applied during the night, mimicking moon and starlight.
[1032] Furthermore, the agricultural light fixture may be
configured to enable changing the form or inclination of the light
fixture or of moveable parts of the light fixture in order to
change the incoming beam inclination angles and/or distance to the
plant within a given lighting period.
[1033] 3.sup.rd aspect of "Plant Movement": The Agricultural Light
Fixture according to the 1.sup.st or 2.sup.nd aspect of "Plant
Movement", wherein at least one light module comprises an LED or
LED-module.
[1034] In a preferred embodiment, the agricultural light fixture
comprises LEDs or groups of LEDs, which can be controlled
independently in order to enable the local intensity change over
time. If the agricultural light fixture is configured such that
single LEDs can be controlled, a gradual change of intensity is
possible, if only groups of LEDs can be controlled, only a stepwise
(specific lighting emitting areas) change of the intensity is
possible. The groups of LEDs may be LED modules arranged in the
agricultural light fixture. It is also possible to use several
agricultural light fixture near each other (arrangement of
agricultural light fixture) to realize this local intensity change
over time.
[1035] 4.sup.th aspect of "Plant Movement": A Controlled
Agricultural System, comprising
[1036] at least one agricultural light fixture according to one or
more of the preceding aspects,
[1037] wherein the Controlled Agricultural System is configured for
controlling the light modules individually or in groups.
[1038] 5.sup.th aspect of "Plant Movement": The Controlled
Agricultural System (200) according to the 4.sup.th aspect of
"Plant Movement", wherein controlling the light modules (110)
comprises controlling the intensities and/or the spectrum of the
light emitted by respective light modules (110).
[1039] 6.sup.th aspect of "Plant Movement": The Controlled
Agricultural System according to the 4.sup.th aspect of "Plant
Movement", wherein the controlling of the light modules is
coordinated such that the at least one agricultural light fixture
is able to emit light with an intensity distribution comprising a
maximum light intensity.
[1040] Therein, the intensity in distributed locally across the
light fixture(s), giving a spatial intensity distribution. To
induce a (bending) movement of plants using light, the intensity
and/or the spectrum of the illumination is changed locally, i.e.
across a part of an illuminated cultivated area (target area), over
time, thus irradiating a plant from different, in some
embodiments/implementations opposite, directions and/or
illumination angles.
[1041] 7.sup.th aspect of "Plant Movement": The Controlled
Agricultural System according to any of the 4.sup.th to 6.sup.th
aspect of "Plant Movement", wherein the controlling of the light
modules is further coordinated such that the at least one
agricultural light fixture is able to move the maximum light
intensity with respect to the light emitting surface of the
agricultural light fixture.
[1042] As an example: Luminaires used in indoor farms usually have
an elongated rectangular form, with one side being longer than the
other side. In an exemplary embodiment of an agricultural light
fixture or an arrangement of agricultural light fixtures according
to "Plant Movement", the intensity of the light on the right side
may be stronger than on the left side (for instance) at the
beginning of the daily illumination period. Then the maximum of the
intensity moves towards the left side during the day so that the
intensity is stronger at the left side than on the right side at
the end of the daily illumination period. Of course, any other
rhythm can be chosen, i.e. once per hour, every 6 hours, every 10
hours, every 14 hours. In some embodiments/implementations, the
rhythm is an integer factor of the daily illumination period.
Alternatively, the agricultural light fixture may be configured
that the maximum intensity moves from right to left and back from
left to right during one period (although the light patterns can be
different).
[1043] 8.sup.th aspect of "Plant Movement": The Controlled
Agricultural System according to any one of the 4.sup.th to
7.sup.th aspect of "Plant Movement", wherein the controlling of the
light modules is further coordinated such that the at least one
agricultural light fixture is able to move the maximum light
intensity from one light module (M3) to another light module
(M4).
[1044] 9.sup.th aspect of "Plant Movement": The Controlled
Agricultural System according to any one of the 4.sup.th to
8.sup.th aspect of "Plant Movement", further comprising a control
unit configured for controlling the light modules of the at least
one agricultural light fixture.
[1045] In general, the controlled agricultural system may also
comprise light guides and/or light reflecting plates, which may be
activated or deactivated at certain times and moved in certain
positions (height, inclination) with respect to the plant canopy
and to provide plant central and/or side illumination (including
root lighting). This way, light can be directed to irradiate the
plants from different sides or angles and therefore contributes to
the described inventive aspect. Activation means to allow light to
pass into or onto these guides/plates and/or to activate special
light sources that illuminate these light guiding elements.
[1046] Furthermore, the agricultural light fixture may be
configured to enable changing the spectral composition of light,
particularly as a function of the moving location of the maximum
value of the light intensity with respect to the light emitting
surface. The spectrum may be changed as a function of the intensity
or the intensity can be changed as a function of the spectrum
during a period. It is also possible that different relation of
spectrum and intensity are applied in different periods, e.g. if a
period has a length of 4 hours and the daily illumination is 12
hours, then each of the 3 periods could have a different relation
of spectrum and intensity.
[1047] In a further refinement of "Plant Movement", that comprises
a changing spectral composition of light, a cycle that resembles
the circadian cycle for sun light and/or a cycle for moon light is
applied to the movement of the maximum value of the light
intensity.
[1048] Furthermore, the light sources that are used for a
time-specific maximum light intensity may be operated (at least for
certain time intervals) in a pulse mode fashion. The cycles may be
determined by the geolocation.
[1049] Furthermore, the intensity change of the LEDs or LED modules
arranged in the agricultural light fixture may be non-periodic or
stochastic.
[1050] 10.sup.th aspect of "Plant Movement": The Controlled
Agricultural System according to the 9.sup.th aspect of "Plant
Movement", further comprising
[1051] a computing device, coupled to the control unit,
[1052] data storage device, coupled to the computing device, for
storing the controlling schemes for the light modules,
[1053] wherein the computing device is configured to control the
light modules of the at least one agricultural light fixture via
the control unit, based on the data of the controlling schemes
stored in the data storage device.
[1054] The computing unit may also be configured to take into
consideration the applied light or growth recipes.
[1055] Another approach would be to rotate the plants and keep the
luminaire static. Rotating could mean to move the plants around the
vertically arranged luminaire (e.g. on a circle with the
circumferentially illuminating luminaire at its center) or the
plants could turn around a central axis thus exposing all sides to
the luminaire in a given timeframe. Alternatively, the luminaire
may be horizontally arranged and the plants may rotate such that
alternately the upper side and the lower side of the plants are
illuminated.
[1056] 11.sup.th aspect of "Plant Movement": A method for
agricultural management, particularly for breeding, growing,
cultivating and harvesting in an agricultural facility, e.g. a
plant growing facility, comprising the steps of:
[1057] Providing multiple light modules, which can be controlled
individually or in groups,
[1058] Arranging the multiple light modules above the plants
arranged in a target area and illuminating the target area,
[1059] Controlling the light modules to emit light on the target
area having an light intensity distribution that comprises a
maximum light intensity,
[1060] Moving the maximum light intensity within the target
area.
[1061] 12.sup.th aspect of "Plant Movement": The method for
agricultural management according to the 11.sup.th aspect of "Plant
Movement", whereby the multiple light modules are arranged in a row
and are controlled such that the maximum light intensity moves from
one light module in the row to another light module in the row.
[1062] 13.sup.th aspect of "Plant Movement": The method for
agricultural management according to the 11.sup.th or 12.sup.th
aspect of "Plant Movement", whereby the maximum light intensity of
the light intensity distribution is implemented by controlling at
least one light module or at most a subset of the multiple light
modules of the light fixture such that its light intensity is
higher than the light intensity of at least one other light module
illuminating the target area.
[1063] 14.sup.th aspect of "Plant Movement": The method for
agricultural management according to any one of the 11.sup.th to
13.sup.th aspect of "Plant Movement", for controlling a Controlled
Agricultural System according to any one of the 4.sup.th to
10.sup.th aspect of "Plant Movement".
[1064] 15.sup.th aspect of "Plant Movement": A method for
agricultural management, particularly for breeding, growing,
cultivating and harvesting in an agricultural facility, e.g. a
plant growing facility, comprising the step of: Moving the plants
with respect to a horticulture light fixture such that all
circumferential sides of the respective plant is illuminated by the
horticulture light fixture during a specified timeframe (cycle
time).
[1065] 16.sup.th aspect of "Plant Movement": The method for
agricultural management according to the 15.sup.th aspect of "Plant
Movement", further comprising the step of rotating the plants
around a central axis.
[1066] 17.sup.th aspect of "Plant Movement": A computer program
product, comprising:
[1067] a plurality of program instructions, which when executed by
a computing device of a Controlled Agricultural System according to
any one of the 4.sup.th to 10.sup.th aspect of "Plant Movement",
cause the Controlled Agricultural System to execute the method for
Agricultural Management according to any one of the 11.sup.th to
13.sup.th aspect of "Plant Movement".
[1068] "Spectrum Calculation"
[1069] A light recipe can define the photon fluxes in all defined
spectral ranges of a light source arrangement of a light fixture
((agricultural) light fixture) at a given time. It can contain a
temporal sequence of photon fluxes in all defined spectral ranges,
a sequence of ON or OFF illumination states and a program for the
dynamic creation of light recipes. Furthermore, a light recipe can
set modes of operation of an illumination device, for example
constant power operation, pulsed operation, DC operation or AC
operation. Furthermore, a light recipe can be generated from a
calculation method with the aid of artificial intelligence (AI),
for example by virtue of a plant-related assessment scheme of
operation and sensor data being created and a light recipe then
being generated therefrom and being applied to the illumination
devices. Furthermore, a light recipe can not only set the spectral
intensities of the light module but can also define the emission
characteristics (e.g., beam width, emission angle, polarization) in
cooperation with optical elements (e.g., lenses, mirrors,
polarizers). Light recipes can also be created in customer-specific
fashion. Thus, the light recipes define the optimal spectrum or a
(non-ideal) spectrum that approximates an optimal spectrum for an
envisaged application. This spectrum can be present as a continuous
intensity distribution over the wavelength (or wavenumber), or else
as a discrete intensity distribution over certain spectral ranges,
wherein the spectrum or spectrums is/are able to be set in a
variable, i.e., changeable, manner. Light recipes can also be
created under inclusion of local light conditions, for example in
the case of a greenhouse illumination (greenhouse lighting).
[1070] By way of example, the intensity in the blue range from
400-450 nm should have a certain value, a further value in the
range from 450-500 nm and a third value in the range from 600 to
720 nm. A value can have a respective overall radiant flux or a
respective PPF (photosynthetic photon flux, i.e., photon flux in
the photosynthetically active region (PAR)) value or a respective
PPFD (photosynthetically active photon flux density
(.mu.mol/(m.sup.2s))) value.
[1071] Additionally, the photon flux ratio of spectral range 1
(e.g., blue) to spectral range 2 (e.g., red) and to further
spectral ranges can be defined by a light recipe (constant in time
or changeable). Naturally, this also applies to any other formation
of ratios of spectral ranges (UV, VIS, IR, dark red).
[1072] Now, a light recipe can be created for a defined selection
(number, arrangement) of light sources. It then controls the
activation and deactivation of the light sources.
[1073] Now, plant illumination devices can have a different number
and arrangement of light sources. Then, there is the need to
convert a light recipe, or adapt it to the best possible extent,
for other plant illumination devices (light fixtures) with a
different number and arrangement of light sources.
[1074] The illumination used to illuminate the plants in some
embodiments/implementations has LEDs. Here, use can be made of LEDs
with different colors, and also in the UV and infrared. The LEDs
can be directly emitting or phosphor converted (phosphor converted
LEDs: pc-LEDs). Directly emitting LEDs have narrowband spectra with
discrete maxima, in which their light intensity is highest.
Phosphor converted LEDs have broader spectral ranges with an
intensity maximum. The width of a maximum can be defined by way of
the FWHM (full width at half maximum) or else by way of the
reduction of the intensity at the maximum to (1/e).sup.2. Then, the
maximum can be known or determinable as a single value, for example
525 nm.
[1075] Consequently, both the spectrum and the spectral ranges in
which the spectral maxima lie, and also the maximum values
themselves, are known for each LED type. The overall spectrum of
the light fixture emerges from the superposition of the spectra of
the individual LEDs. A superposition of the spectra can be
implemented both in real space and in angle space.
[1076] Consequently, the corresponding data are also known for a
plant illumination device, and also (where necessary) the data of
the geometric arrangement of the light sources and the light
fixtures.
[1077] 1.sup.st aspect of "Spectrum Calculation": A controlled
agricultural system facilitating the use of a light recipe with
different light fixtures, comprising
[1078] a light fixture with a plurality of light sources,
[1079] an acquisition unit for capturing parameters of the light
fixture and of a light recipe,
[1080] a computing device connected to the acquisition unit,
[1081] a control unit connected to the computing device and the
light fixture, said control unit configured to convert the data of
the computing unit into control signals for the light sources of
the light fixture such that the light fixture produces
radiation,
[1082] wherein the computing device is configured to select the
suitable light sources from the light sources present in the light
fixture and calculate the actuation thereof on the basis of the
parameters of the light fixture in such a way that the radiation of
the actuated light fixture at least approximates the light
recipe.
[1083] An object here is to allow a light recipe to be used or
adapted in a controlled agricultural system in the case of light
fixtures (agricultural light fixtures) of different design. Thus,
inter alia, a solution is proposed of how a light recipe can be
used, for example, both in the case of a light fixture which only
has three different LED colors (e.g., blue, red, dark red) and in
the case of a light fixture that has seven different LED colors
(e.g., dark blue, light blue, yellow, orange, red, dark red,
green). However, the approach is also applicable to nonvisible
spectral ranges, such as ultraviolet and infrared, to be precise in
combination with visible colors and independently.
[1084] 2.sup.nd aspect of "Spectrum Calculation": The controlled
agricultural system as described in the 1.sup.st aspect of
"Spectrum Calculation", comprising two or more light fixtures,
[1085] wherein the light sources in the at least two light fixtures
differ in one or more of the following criteria: number, maximum
intensity, wavelength at the maximum of the emission radiation,
spectral width of the emission radiation, spatial distribution of
the radiation, angle distribution of the radiation, type of light
source.
[1086] Thus, the light recipe may be available for a light fixture
with a certain combination of LEDs and it should now be used for a
light fixture containing the same type of (structurally equivalent)
LEDs, albeit in a greater respective number. Thus, for example, a
light recipe is designed for maximum emissions of 3 blue and 4 red
LEDs of a first light fixture and it should be used in a second
light fixture with 4 blue and 5 red LEDs which are structurally
equivalent in each case (excess number of in each case structurally
identical light sources), then [1087] only 3 of the 4 blue LEDs and
only 4 of the 5 red LEDs of the second light fixture can be used
when applying a respective maximum power or [1088] the light power
of the 4 blue LEDs of the second light fixture is reduced overall
by a factor of (i.e., by 25%), wherein the individual LEDs of the 4
blue LEDs may be actuated differently and the reduction factor of
must only arise in the sum; and the 5 red LEDs must be impinged by
the overall factor of 4/5 (i.e., a reduction by 20%). Thus, the
light power is reduced by the ratio of the original number of LEDs
and to the new number of LEDs. A change in the light power,
suitable to this end, by way of the current (increase, decrease) or
a modulation of the operational data is known.
[1089] If a fewer number of light sources (e.g., LEDs) of the same
design in each case are present in the second light fixture, the
fewer number must have a stronger electrical impingement by a
factor; i.e., in the case of X blue LEDs of the first arrangement
and Y (less than X) blue LEDs of the second arrangement, the Y blue
LEDs must be impinged more strongly by a factor of X/Y. A change in
the light power, suitable to this end, by way of the current
(increase, decrease) or a modulation of the operational data is
known.
[1090] Should a higher impingement prove impossible (operational
safety, service life of the LEDs), then, optionally, the light
recipe may be modified and/or the associated irradiation may be
applied for longer. An analogous statement also applies in the
first case, if a reduction in the operational values is not
possible (then, where applicable, the light recipe would have to be
applied for a shorter time (provided this is beneficial to the
product)).
[1091] Naturally, this method also applies to other configurations
of structurally equivalent LEDs.
[1092] 3.sup.rd aspect of "Spectrum Calculation": The controlled
agricultural system as described in the 2.sup.nd aspect of
"Spectrum Calculation",
[1093] wherein the computer device is configured to respectively
calculate a selection of the light sources for the light fixtures
with various light sources and the actuation thereof in such a way
that the radiation of the various light fixtures at least
approximates the light recipe.
[1094] An approximation method is used should a situation arise in
which the second light fixture does not comprise structurally
equivalent light sources, e.g., LEDs, i.e., in which said second
light fixture cannot exactly reproduce the predetermined light
spectrum. To this end, the light sources used in the respective
light fixture, the number of said light sources, operational data,
spectral data and maximum values being known to a control unit of
the light fixture, are transmitted to a computing device (software
program), which then is able to simulate a variation space of all
(or most) possible spectral combinations (simulation points). These
simulation points are then compared to the target spectrum or
target data of the light recipe, for example using the method of
the least squares between calculated simulation points and target
data, or of the smallest distance from the overall CIE value of the
target light recipe, or of the spectral-range-specific photon
fluxes. Then, the configuration (operation of those light sources
of the second light fixture) which is closest to the target
spectrum or the target data is selected. This setting can be
adapted during the scope of the irradiation duration to the
requirements of the products (growth, morphology, maturing).
[1095] These methods described in 1. to 3. can be applied both to
light recipes that are not changeable in time and to light recipes
that are changeable in time. Furthermore, the methods described in
1. to 3. can also be used for different types of light sources, for
example the combination of organic LEDs (OLEDs) with inorganic
LEDs, or with inclusion of LARP (laser-activated remote phosphor)
light sources, and with inclusion of conventional light sources
such as discharge and incandescent lamps.
[1096] Furthermore, it is possible to prescribe limits for the
allowed deviations in the respective spectral ranges. This is due
to the fact that some ranges of the spectrum (e.g., in the blue and
in the red and also in the green when producing plant-based
content) are particularly critical for the quality of a plant, for
example when forming enzymes, vitamins, etc. Here, for example,
even a small deviation of the light power can lead to relatively
large changes (morphology, nutritional value) in the plant.
[1097] Consequently, a method is provided, by means of which a
light recipe, which has been defined for a light fixture, can be
transferred to a second light fixture of a different design. To
this end, the respective light fixture parameters (number and type
of the light sources, possibly also the arrangement thereof and the
type and arrangement of optical elements) are made available to a
control unit (light control unit) or a computing device of the
light fixtures or of the controlled agricultural system. Here, the
computing device may also be referred to as a "transformation
unit", since it transforms a light recipe into another light recipe
that is as equivalent as possible, i.e., it makes a light recipe
applicable to a second light fixture of a different design. To this
end, the method according to this element of the disclosure
includes a transformation prescription, which, based on the light
fixture parameters, undertakes the transformation of a light recipe
for a first light fixture to a light recipe for a second light
fixture that differs from the first light fixture. A transformation
matrix can be stored and distributed in a data network. Here, a
first light fixture and a second light fixture can be spatially
separated, for example at different locations in irradiation
devices in plant breeding and/or growing facilities.
[1098] In a further configuration, this method renders it possible
to apply a generic light recipe, which emerges, for example, from
the ideal conditions of growing and/or breeding plants, to a light
fixture, the properties of which (type and number of light sources)
are not known in advance. Here, the generic light recipe may be
present only in the form of intensity over wavelength (or
wavenumber), either continuously or as discrete values for certain
wavelength ranges. This would correspond to a light recipe for a
light fixture, in which the number of different LED colors
corresponds to the number of wavelength ranges in which the
spectrum was stored. Thus, method 3 would be applied here.
[1099] 4.sup.th aspect of "Spectrum Calculation": The controlled
agricultural system as described in any one of the preceding
aspects,
[1100] wherein the light sources of the light fixtures comprise
LEDs.
[1101] 5.sup.th aspect of "Spectrum Calculation": An agricultural
method, comprising:
[1102] a light recipe for a first light fixture (first
light-fixture-specific light recipe),
[1103] a controlled agricultural system comprising a second light
fixture that differs from the first light fixture, and the
following method step:
[1104] transforming the light recipe for the first light fixture
into a light recipe for the second light fixture (second
light-fixture-specific light recipe).
[1105] 6.sup.th aspect of "Spectrum Calculation": The agricultural
method as described in the 5.sup.th aspect of "Spectrum
Calculation", wherein the transformation includes one or more of
the following method steps:
[1106] selecting suitable light sources from the light sources
available in the second light fixture,
[1107] establishing the required spectral-range-specific light
intensities of the respective light sources,
[1108] establishing the required control signals for the respective
light sources, applying the control signals to the respective light
sources.
[1109] The above-described methods are also applicable to an
arrangement of a plurality of light fixtures.
[1110] Finally, provision can also be made for the computer device
to notify the user if a light recipe cannot be reproduced within a
tolerance range by way of a light fixture. Additionally, there
beyond, provision can also be made for the computing device to
provide the user with propositions for a suitable modification of
the existing light fixture, for example by complementing it with
further light sources, or for a suitable new light fixture.
[1111] "Extended Recipes"
[1112] The present disclosure relates to a Controlled Agricultural
System, an Agricultural Light Fixture for use in a Controlled
Agricultural System and a Method for Agricultural Management.
[1113] Light recipes specify the spectrum, the light intensity
(i.e. photon flux) and how long and at what times a specific light
recipe is to be applied to a plant species. Usually, all relevant
parameters are converted into respective currents or current
modifying settings like PWM modulation, On/Off cycles and the like,
which drive the light sources of a horticultural light fixture such
that the light emitted by the horticultural light fixture
reproduces the specific, desired, light recipe as good as
possible.
[1114] High light intensities of light fixtures
(brightness/luminance) typically require high driver currents
causing high energy consumption. This may raise economical issues
due to ever increasing energy costs as well as ecological
concerns.
[1115] However, providing the intensity of the illumination
(illuminance; or more plant specific: photosynthetic photon flux
density [PPFD]) currently required by the light recipe may also be
achieved in another manner, especially by bringing the
horticultural light fixtures closer to the plants and/or by
adjusting or modifying optical devices of the light fixtures, for
example so that the illumination is more focused on parts of the
cultivated area, on the plants or even on parts of the plants.
[1116] 1.sup.st aspect of "Extended Recipes": A Controlled
Agricultural System, particularly for breeding, growing,
cultivating and harvesting in an agricultural facility,
particularly a plant growing facility and/or an aquaponics
facility, comprising:
[1117] An agricultural light fixture arranged above an area
cultivated with plants for illuminating the plants,
[1118] An actuator device configured to be able to control the
position/alignment of the agricultural light fixture,
[1119] A computing device configured to control the brightness of
the agricultural light fixture and to control the actuator device
in order to effectuate an intensity of the illumination
(illuminance) on the plants or parts of the plants according to a
light recipe for the plants.
[1120] It is an advantage of "Extended Recipes" to safe energy by
reducing the standard current setting (i.e. brightness) of a
horticultural light fixture normally required according to the
light recipe, and still keeping the illumination on the plants
compliant to the light recipe. This is achieved by adjusting and/or
modifying a horticultural light fixture, for example, by bringing
the light fixture closer to the plants, according to the light
recipe.
[1121] Therefore, "Extended Recipes" proposes a controlled
agricultural system, comprising an agricultural light fixture,
which agricultural system is configured to be able to control the
position and/or orientation and/or shape of the agricultural light
fixture with respect to the plants and/or adapt an optical device,
arranged downstream of the light sources of the agricultural light
fixture, according to the light recipe.
[1122] For this purpose, the controlled agricultural system further
comprises a computing device and a data storage device. The data
storage device comprises the respective light recipe for the plant
species. The computing device is configured to be able to access
the data of the light recipe (i.e. current light spectrum,
intensity and duration of exposure to light irradiation) from a
data storage device.
[1123] 2.sup.nd aspect of "Extended Recipes": The Controlled
Agricultural System according to the 1.sup.st aspect of "Extended
Recipes", wherein the actuator device comprises means for lowering
or raising or aligning or moving or bending the agricultural light
fixture with respect to the cultivated area.
[1124] Furthermore, the computing device is configured to be able
to compute a position/alignment of the agricultural light fixture
that results in a higher light intensity as originally prescribed
according to the light recipe. Particularly, the agricultural light
fixture may be moved closer to the plants. Moving closer may be
accomplished by moving the agricultural light fixture vertically
closer, i.e. reducing the distance above the plants, and/or
laterally closer, i.e. reducing the distance at the side of a
respective plant. Concurrently, the current for the light sources,
e.g. LEDs, may be reduced, compared to the current setting
originally necessary, such that the resulting light intensity
illuminating the plants in the target area matches with the light
intensity according to the light recipe, while at the same time
using less energy to realize the intended illumination target
value.
[1125] 3.sup.rd aspect of "Extended Recipes": A Controlled
Agricultural System, particularly for breeding, growing,
cultivating and harvesting in an agricultural facility,
particularly a plant growing facility and/or an aquaponics
facility, comprising:
[1126] An agricultural lighting fixture arranged above an area
cultivated with plants for illuminating the plants, comprising an
optical device for adjusting the intensity of the light emitted by
the agricultural lighting fixture during illumination,
[1127] An actuator device configured to be able to control the
optical device of the agricultural light fixture,
[1128] A computing device configured to control the brightness of
the agricultural light fixture and to control the actuator device
in order to achieve an intensity of the illumination (illuminance)
on the plants or parts of the plants according to a light recipe
for the plants.
[1129] The optical device of the agricultural light fixture may be
adjusted to focus the illumination more on the plants, for example
by narrowing or widening the beam angle/spread. Furthermore,
depending on the size of the plants, it may be necessary to adjust
the optical device such that after moving the agricultural light
fixture closer to the plants the illuminated area is still
sufficiently large. The computed new position and/or shape of the
agricultural light fixture and--as the case may be of the optical
device--is sent by the computing device to a control unit, which
controls the agricultural light fixture and/or optical device
correspondingly.
[1130] The optical device may be adjusted by moving lenses of a
lens system or by using an adaptable lens, the focal length of
which can be adjusted by changing the curvature of the surface of
the lens. Alternatively, reflective optical means may be used to
adjust the focusing properties of the optical device.
[1131] 4.sup.th aspect of "Extended Recipes": The Controlled
Agricultural System according to the 3.sup.rd aspect of "Extended
Recipes", wherein
[1132] the optical device comprises one or more of the
following:
[1133] A lens with adaptable focal length (e.g. by adjusting the
curvature of the lens), a lens system, comprising two lenses, which
are movable with respect to one another, a reflector.
[1134] 5.sup.th aspect of "Extended Recipes": The Controlled
Agricultural System according to any one of the preceding aspects,
further comprising
[1135] a data storage device connected to the computing device, the
data storage device comprising a light recipe for the plant to be
illuminated.
[1136] The data storage device may furthermore contain information
on how mechanical changes of the position/alignment of the
agricultural light fixture or the optical device of the
agricultural light fixture influence the illumination, i.e. the
photon flux at the plants. Thus, it is possible to calculate the
feasible reduction of brightness of the light sources and,
therefore, of the current setting for the light sources achieving a
lower power consumption, due to mechanical changes of the
position/alignment/shape of the agricultural light fixture and/or
its optical device (or vice versa), and still being compliant with
the light recipe.
[1137] 6.sup.th aspect of "Extended Recipes": The Controlled
Agricultural System according to the 5.sup.th aspect of "Extended
Recipes", wherein the light recipe further comprises parameters
that control supplemental functions in an agricultural facility
(extended light recipe).
[1138] Thus, besides changing the mechanical or optical properties
of the agricultural light fixture, further parameters of the
agricultural facility (e.g. greenhouse, vertical farm) may be
adjusted in order to meet the requirements of the light recipe. For
instance, the temperature inside the agricultural facility may be
adjusted, because the temperature influences the growth rate at a
predefined light intensity
[1139] Furthermore, the light recipes may comprise parameters that
control supplemental functions in the agricultural facility
(extended light recipe). For instance, the extended light recipes
may comprise parameters that specify the proper adjustment of the
position of the agricultural light fixture or of its optical device
without the need of computing such parameters from the light
intensity data.
[1140] 7.sup.th aspect of "Extended Recipes": The Controlled
Agricultural System according to the 6.sup.th aspect of "Extended
Recipes", wherein the extended light recipe comprises parameters
that specify the proper adjustment of the position/alignment of the
agricultural light fixture or of its optical device.
[1141] 8.sup.th aspect of "Extended Recipes": The Controlled
Agricultural System according to the 6.sup.th or 7.sup.th aspect of
"Extended Recipes", wherein the extended light recipe further
comprises parameters that control any one of the following:
polarization, collimation or coherence of the light emitted by the
agricultural light fixture, environmental temperature,
humidity.
[1142] To summarize, the light recipes may comprise parameters that
control any one of the following: polarization, collimation or
coherence of light, environmental temperature, humidity. A light
recipe may further comprise adaptive irradiation settings as a
function of plant growth, shape and fruition. Therefore, distance,
inclination, adjustment of optical part can be regulated depending
on irradiation time or measured plant growth/shape and the
like.
[1143] 9.sup.th aspect of "Extended Recipes": The Controlled
Agricultural System according to any one of the 6.sup.th to
8.sup.th aspect of "Extended Recipes", wherein the actuator device
is further configured to be able to control the supplemental
functions.
[1144] 10.sup.th aspect of "Extended Recipes": A method for
agricultural management, particularly for breeding, growing,
cultivating and harvesting plants arranged in a cultivated area in
an agricultural facility, e.g. a plant growing facility,
comprising:
[1145] A light recipe and an agricultural light fixture for
illuminating plants, and the steps of:
[1146] Illuminating plants with the agricultural light fixture
according to the light recipe;
[1147] Decreasing the distance between the agricultural light
fixture and the plants by lowering the horticultural light fixture
down closer to the plants, while reducing the brightness of the
agricultural light fixture to keep the illumination on the plants
specified by the light recipe constant.
[1148] 11.sup.th aspect of "Extended Recipes": A method for
agricultural management, particularly for breeding, growing,
cultivating and harvesting plants arranged in a cultivated area in
an agricultural facility, e.g. a plant growing facility,
comprising:
[1149] A light recipe and an agricultural light fixture for
illuminating plants, whereby the agricultural light fixture
comprises an optical device configured to be able to focus the
illumination on parts of the cultivated area and/or on parts of the
plants, and the steps of:
[1150] Illuminating plants with the agricultural light fixture
according to the light recipe;
[1151] Adjusting the optical device to focus the illumination more,
e.g. on parts of the cultivated area, on the plants and/or on parts
of the plants, while reducing the brightness of the agricultural
light fixture to keep the illumination on the plants specified by
the light recipe constant.
[1152] 12.sup.th aspect of "Extended Recipes": The method for
agricultural management according to the 10.sup.th and/or 11.sup.th
aspect of "Extended Recipes", for controlling a Controlled
Agricultural System according to any one of aspects 1-9.
[1153] 13.sup.th aspect of "Extended Recipes": A computer program
product, comprising:
[1154] a plurality of program instructions, which when executed by
a computer system of a Controlled Agricultural System according to
any one of the 1.sup.st to 9.sup.th aspect of "Extended Recipes",
cause the Controlled Agricultural System to execute the method for
Agricultural Management according to any one of the 10.sup.th to
12.sup.th aspect of "Extended Recipes".
[1155] "Light Recipe & VLC"
[1156] 1.sup.st aspect of "Light Recipe & VLC": A Controlled
Agricultural System comprising
[1157] a first light fixture with a light source for agricultural
lighting,
[1158] wherein the Controlled Agricultural System is configured for
modulating an emission of the light source to transmit data via
this modulated signal.
[1159] The modulation can for instance be achieved by modulating
the intensity, for instance by superimposing an intensity change or
by switching off the light source for short intervals. The
modulation can also be achieved by a pulse modulation, for example
a Pulse Width Modulation (PWM), a Pulse Frequency Modulation, a
Pulse Code Modulation or a Pulse Phase Modulation. The modulated
signal can be received by a photodiode, and the data contained in
the signal is available after a demodulation.
[1160] Accordingly, the lighting appliance of the agricultural
system or farm can be used for transmitting data to other
appliances, for instance control data to trigger actuators, for
example for irrigation, manuring, heating/ventilation or the like,
or to trigger a transportation of plant boxes from one lighting
station to the next, or to trigger bendable or moveable fixtures to
change their form, position or inclination. Using the light source
intended for the agricultural lighting also for the data
transmission can reduce the overall number of components and the
complexity of the system, too. For instance, the wiring effort can
be reduced.
[1161] 2.sup.nd aspect of "Light Recipe & VLC": The Controlled
Agricultural System of the 1.sup.st aspect of "Light Recipe &
VLC", comprising a second light fixture configured for receiving
the modulated signal and thus the data from the first light
source.
[1162] In some embodiments/implementations, the controlled
agricultural system is configured for transmitting lighting
parameters via the modulated signal from the first light fixture as
a master to the second light fixture as a slave, but a mesh
configuration can also be possible. A computing device can be
connected to the first light fixture, for instance directly or via
a light control unit. The connection between these components can
be wireless or wire based, combinations are possible as well. Upon
receiving the lighting parameters from the computing device or the
light control unit, the first light fixture can emit the modulated
signal for transmitting these lighting parameters to the other
light fixtures. The computing device or the light control unit can
be an integral part of a lighting fixture. This transmission can
happen immediately upon receiving the lighting parameters from the
computing device, but also after a predefined or stochastic time
interval. Such a data set can contain a fixture identifier so that
just the related (second) fixture responds to that data set,
supposed second fixture has such an (electronic, software code)
identifier and respective detection units.
[1163] 3.sup.rd aspect of "Light Recipe & VLC": The Controlled
Agricultural System according to the 1.sup.st or 2.sup.nd aspect of
"Light Recipe & VLC", comprising a computing device connected
to the first light fixture, the Controlled Agricultural System
being configured for transmitting lighting parameters via the
modulated signal from the first light fixture as a master to the
second light fixture as a slave.
[1164] Upon receiving the lighting parameters from the first light
fixture, the emission of the second light fixture can be adapted
respectively. In particular, a light control unit of the second
light fixture can amend the emission as required. This light
control unit is connected to the second light fixture, and is
connected to a sensor device (e.g. a photodiode) for receiving the
modulated signal or comprises such a sensor device as an integral
part.
[1165] The master/slave architecture can be advantageous in terms
of a flexible setup of the agricultural system or farm. For
instance, in case that additional lighting fixtures are required
for an extension of the farm, those can be installed as slaves.
Likewise, the lighting of a large number of light fixtures can be
aligned and/or synchronized rather automatically. Advantageously,
if required, an additional light fixture can be put in place and
receives the lighting parameters to be applied, a connection to the
power supply being the only installation necessary. Agricultural
lighting fixtures can build up a network that may comprise
sub-networks, that is, grouped fixtures that can be addressed with
the same data set command.
[1166] 4.sup.th aspect of "Light Recipe & VLC": The Controlled
Agricultural System according to the 3.sup.rd aspect of "Light
Recipe & VLC", comprising a further light fixture, wherein the
Controlled Agricultural System is configured for modulating an
emission of a light source of the second light fixture for
transmitting the lighting parameters from the second light fixture
to the further light fixture as a slave.
[1167] In general, but also in the master/slave setup, also the
second light fixture can be adapted for a modulated emission and
for transmitting data via this modulated signal to a third fixture
and/or back to the first fixture and/or to any other agricultural
device (as described above). This also enables a feedback loop. The
second light fixture can for instance transmit growth data of the
plants illuminated or other local parameters to the first light
fixture (and the computing device thus). On the other hand, the
second light fixture can be used as an amplifier or distributor,
namely for transmitting the lighting parameters to further light
fixtures arranged at a larger distance from the first light
fixture. In particular, this enables a transmission of the lighting
parameters from the first light fixture (master) to light fixtures
provided as slaves, even when the latter are not illuminated by the
first light fixture directly, thus enabling a data distribution
network.
[1168] In general, the spectral composition of the emitted light
could be adaptively adjusted or fixed. Then, the lighting
parameters can for instance be intensity values. Preferably, the
light fixtures are adapted for an illumination with different
spectral properties (with different light source types, see below)
so that the lighting parameters are also spectral parameters (in
addition to intensities). Spectral parameters can include other
optical data, for example the polarization of the emitted
spectrum.
[1169] Basically, the light emitted by a light fixture for
agricultural lighting can be monochromatic light (FWHM<25 nm, or
case of a laser light source<5 nm) or narrow band radiation
(FWHM<50 nm) or broadband radiation (FWHM>100 nm) or a
mixture thereof. The term "light" shall comprise spectral ranges
outside the visible light spectrum. Respective non-visible spectral
ranges can be infrared and/or UV.
[1170] 5.sup.th aspect of "Light Recipe & VLC": The Controlled
Agricultural System according to one of the preceding aspects,
comprising an actuator device for providing at least one of
irrigation, manuring, heating, ventilation and air conditioning to
plants grown in the Controlled Agricultural System, the Controlled
Agricultural System being configured to trigger the actuator device
by the modulated signal emitted by the first light source.
[1171] This can be an alternative or a supplementation to the
communication amongst the light fixtures. The actuator device can
be a robot or vehicle, in particular a self-driving vehicle, but
also a stationary appliance. The actuator device can comprise a
sensor device, in some embodiments/implementations a
photoelectrical sensor, for receiving the modulated signal. The
modulated signal can be received by the actuator device directly or
by an external receiving unit connected to the actuator device via
an interface.
[1172] In some embodiments/implementations, the actuator device is
adapted for providing irrigation, manuring, heating, ventilation
and/or air conditioning to the plants grown in the farm or to
trigger a transportation of plant boxes from one lighting station
to the next, or to trigger bendable or moveable fixtures to change
their form, position or inclination. Via the modulated signal, the
actuator device can be triggered to adjust at least one of the
respective conditions, for instance based on a light recipe
applied.
[1173] 6.sup.th aspect of "Light Recipe & VLC": The Controlled
Agricultural System according to the 5.sup.th aspect of "Light
Recipe & VLC" in combination with the 3.sup.rd or 4.sup.th
aspect of "Light Recipe & VLC", the Controlled Agricultural
System being configured for transmitting based on a growth status
of plants grown in the Controlled Agricultural System a light
recipe, namely various lighting parameters via the first light
fixture to the second light fixture or fixtures and various
actuation parameters to the actuator device.
[1174] A "light recipe" can define lighting conditions. It can
contain information and executable commands that control the light
intensity and/or wavelength/spectral composition. A light recipe
can be adaptive, namely depend on external trigger signals or
feedback loops, particularly depending on the growth status of the
plants. In other words, a light recipe contains a data set that
provides for every point in time operational data to enable a
lighting fixture to emit the required spectral composition and
spectral intensities.
[1175] In some embodiments/implementations, the modulation of the
signal is used for transmitting a light recipe via the modulated
signal. In particular, the first light fixture can be used for
transmitting lighting parameters to second light fixtures and
actuation parameters to the actuator device, both based on the
growth status of the plants.
[1176] 7.sup.th aspect of "Light Recipe & VLC": The Controlled
Agricultural System according to one of the preceding aspects of
"Light Recipe & VLC", wherein the first light fixture comprises
light sources of different types with different spectral
properties, a control unit for modulating the emission being
configured to modulate the emission of the different light source
types in at least in one mode of operation simultaneously.
[1177] Thus, the light fixture(s) comprise(s) light sources of
different types. The different types differ in their spectral
properties (e.g. green, red, far red and so on).
[1178] In some embodiments/implementations, a control unit for
modulating the emission is configured to modulate the different
light source types simultaneously, at least in one mode of
operation. For instance, the green, red and far red light sources
can be modulated simultaneously. In some
embodiments/implementations, in this mode of operation, all light
source types are modulated. In other words, the whole
electromagnetic spectrum of the first light fixture is modulated,
the data being contained at every wavelength of the spectrum. The
control unit for modulating the emission can be a separate device
provided between a computing device and the light fixture. However,
it can also be an integral part or function, for instance of the
computing device or the light control unit.
[1179] 8.sup.th aspect of "Light Recipe & VLC": The Controlled
Agricultural System according to one of the preceding aspects of
"Light Recipe & VLC", wherein the first light fixture comprises
light sources of different types with different spectral
properties, a control unit for modulating the emission being
configured to leave the emission of at least one light source type
unmodulated in at least in one mode of operation while the emission
of at least one other light source type is modulated.
[1180] The modulation is applied selectively in an interval of the
light fixture's spectrum. For instance, only one light source type
(e.g. green) can be modulated while the other light source types
are not modulated. A modulation in groups is also possible, so that
for instance green and yellow are modulated while red is not
modulated, or vice versa. It is also possible to switch the
modulation from one colour to another in a predetermined way but
also in a freely selectable manner including a stochastic switch
between various colours.
[1181] 9.sup.th aspect of "Light Recipe & VLC": The Controlled
Agricultural System according to one of the preceding aspects of
"Light Recipe & VLC", wherein the first light fixture comprises
light sources of different types with different spectral
properties, the Controlled Agricultural System being configured for
applying a light recipe, namely various lighting parameters
depending on a growth status of plants grown in the Controlled
Agricultural System, and wherein a control unit for modulating the
emission is configured to modulate different light source types
based on the light recipe.
[1182] In a preferred embodiment, the control unit for modulating
the emission is configured to modulate different light source types
based on the light recipe. Thus, the modulation and communication
depend on the light selected for the illumination. When the latter
changes according to the light recipe, another light source type or
other types are chosen for the modulation. The communication
switches to a different colour. In case that more than one light
source type is used for the lighting, the one having the highest
intensity can be chosen for instance.
[1183] 10.sup.th aspect of "Light Recipe & VLC": The Controlled
Agricultural System according to one of the preceding aspects of
"Light Recipe & VLC", wherein the first light fixture comprises
light sources of different types with different spectral
properties, a control unit for modulating the emission being
configured to modulate the light source types differently in a last
one mode of operation, different data being transmitted via the
different light source types.
[1184] Accordingly, having different light source types at hand is
used for a multichannel communication. For instance, one light
source type and spectral range can be used for transmitting
lighting parameters to the other light fixtures. Another light
source type and spectral range can be used for transmitting
actuation parameters to an actuator device. Accordingly, the
respective data transmitted via the respective light source type
can contain only the information necessary for the devices of the
respective channel. This allows reducing the losses resulting from
the modulation in terms of the lighting of the plants.
[1185] 11.sup.th aspect of "Light Recipe & VLC": The Controlled
Agricultural System according to one of the preceding aspects of
"Light Recipe & VLC", configured for monitoring a reduced
lighting of plants grown in the Controlled Agricultural System,
which results from the modulated emission.
[1186] For instance, the total or a wavelength-specific photon flux
can be measured. In some embodiments/implementations, the off-time
or reduced emission time is derived directly from the control unit
for modulating the emission.
[1187] In some embodiments/implementations, a countermeasure for
compensating the reduced emission is taken, depending on a
threshold value for instance, the light recipe can be modified,
particularly the intensity can be increased. Alternatively or in
addition, the overall duration of the lighting can be increased,
and/or the distance between a lighting fixture and the irradiated
plant can be reduced and/or the orientation of a fixture can be
adjusted.
[1188] 12.sup.th aspect of "Light Recipe & VLC": The Controlled
Agricultural System according to the 11.sup.th aspect of "Light
Recipe & VLC", configured for compensating the reduced lighting
by adjusting at least one of a light recipe, an overall intensity
and an overall duration of the lighting.
[1189] 13.sup.th aspect of "Light Recipe & VLC": The Controlled
Agricultural System according to one of the preceding aspects of
"Light Recipe & VLC", the first light fixture comprising light
sources of different types, wherein the emission of at least one
light source type lies outside the visible spectral range, and
wherein a control unit for modulating the emission is configured to
modulate at least in one mode of operation the at least one light
source type outside the visible spectral range.
[1190] The light source type having an emission outside the visible
spectral range, for instance an UV or IR light source. In some
embodiments/implementations, the emission of this light source type
is modulated in at least one mode of operation so that the
non-visible light is used for transmitting data.
[1191] 14.sup.th aspect of "Light Recipe & VLC": The Controlled
Agricultural System according to the 11.sup.th and 13.sup.th aspect
of "Light Recipe & VLC", optionally in combination with the
12.sup.th aspect of "Light Recipe & VLC", configured for
compensating the reduced lighting by switching into the at least
one mode of operation in which the at least one light source type
outside the visible spectral range is modulated.
[1192] Thus, the non-visible spectral region is modulated when the
aforementioned losses in the visible spectral range become too
large.
[1193] 15.sup.th aspect of "Light Recipe & VLC": A Method for
Controlling a Controlled Agricultural System according to one of
the preceding aspects, wherein an emission of the light source is
modulated to transmit data via this modulated signal.
[1194] 16.sup.th aspect of "Light Recipe & VLC": A Computer
program product, comprising:
[1195] a plurality of program instructions, which when executed by
a computing device of a Controlled Agricultural System according to
any one of the 1.sup.st to 14.sup.th aspect of "Light Recipe &
VLC", cause the Controlled Agricultural System to execute the
Method of the 15.sup.th aspect of "Light Recipe & VLC".
[1196] "Temperature Control"
[1197] "Temperature Control" proposes a method of how temperature
conditions can be changed or adjusted to counter-influence
(negative), keep or enhance (positive) Plant Growth or plant
Time-to-Harvest conditions affected by the local temperature (or
integral local temperature) settings at the location of a
plant.
[1198] Temperature control units for agricultural facilities like
horticulture farms, vertical farms or greenhouses usually try to
keep the temperature at a certain, constant level. If the
temperature rises above the level (e.g. in greenhouses on a very
sunny day), measures are taken to reduce the temperature (e.g. open
the windows to create air ventilation, or start a cold liquid
irrigation system). If the temperature rises below a certain level,
a heating device is switched on to restore the target temperature
in the agricultural facility.
[1199] Horticultural lighting fixtures produce an enormous amount
of heat. For example, the control systems of vertical farms may try
to keep a constant (vertical) temperature in the building. However,
due to the large number of illuminations units and other electrical
equipment, which produce heat, and the large dimensions of typical
vertical farms, it is unavoidable, that the temperature under the
ceiling is higher than on the ground (as warm air is lighter and
moves up [natural heat convection]). Therefore, the temperature
conditions in soil and air (and possibly also the water irrigation
temperature) is different at different height levels.
[1200] Temperature, however, has an influence on the growth of
plants. Some plants like petunia or verbena need less time to
flowering the higher the temperature is. However, petunia grow
faster the higher the temperature is, whereas verbena grow faster
the lower the temperature is. Other plants like salvia have a
maximum growth rate at about 22.degree. C., whereas they grow
slower for higher and lower temperatures.
[1201] Example Petunia Coral Pink [1202] The following shows the
respective time to flower (days) at four different temperatures
(14, 17, 20, 23 [.degree. C.]) and four different DLI (daily light
integral) values (5, 10, 15, 20 [mol/m.sup.2d]): [1203] Time to
flower at 14.degree. C.: at 5 mol*m-2*d-1: more than 80 days [1204]
Time to flower at 17.degree. C.: at 5 mol*m-2*d-1: ca. 48 days
[1205] Time to flower at 20.degree. C.: at 5 mol*m-2*d-1: ca. 35
days [1206] Time to flower at 23.degree. C.: at 5 mol*m-2*d-1: ca.
30 days [1207] Time to flower at 14.degree. C.: at 10 mol*m-2*d-1:
ca. 65 days [1208] Time to flower at 17.degree. C.: at 10
mol*m-2*d-1: ca. 40 days [1209] Time to flower at 20.degree. C.: at
10 mol*m-2*d-1: ca. 30 days [1210] Time to flower at 23.degree. C.:
at 10 mol*m-2*d-1: ca. 28 days [1211] Time to flower at 14.degree.
C.: at 15 mol*m-2*d-1: ca. 50 days [1212] Time to flower at
17.degree. C.: at 15 mol*m-2*d-1: ca. 35 days [1213] Time to flower
at 20.degree. C.: at 15 mol*m-2*d-1: ca. 28 days [1214] Time to
flower at 23.degree. C.: at 15 mol*m-2*d-1: ca. 23 days [1215] Time
to flower at 14.degree. C.: at 20 mol*m-2*d-1: ca. 42 days [1216]
Time to flower at 17.degree. C.: at 20 mol*m-2*d-1: ca. 30 days
[1217] Time to flower at 20.degree. C.: at 20 mol*m-2*d-1: ca. 25
days [1218] Time to flower at 23.degree. C.: at 20 mol*m-2*d-1: ca.
20 days
[1219] These examples illustrate how the temperature influences the
growth, particularly the time to flower.
[1220] Plants, however, do not only require a stable temperature,
they also require certain, regular changes in temperature. For
example, the circadian clock of plants is sensitive to temperature.
Many processes of the plant are controlled by the circadian clock.
Some other plants, for example, require low temperature to be able
to complete their development cycle. This phenomenon is known as
vernalization and can imply weeks at low temperature, typically
between 5 and 10.degree. C., for a plant to be able to flower.
[1221] To improve the yield and the quality of plants in an
agricultural facility, it is thus necessary to provide an
agricultural system, which sets the temperature of the agricultural
facility in a controlled way. The controlled way does not target a
stable temperature over the whole time until harvest, but it
targets regular temperature modifications or changes in a proper
and consistent manner.
[1222] 1.sup.st aspect of "Temperature Control": A controlled
agricultural system, particularly for plant breeding, growing,
cultivating and harvesting in an agricultural facility,
comprising:
[1223] a sensor device, comprising temperature measuring means able
to measure the (local) temperature, in some
embodiments/implementations at various locations, in the
agricultural facility,
[1224] an actuator device, comprising temperature influencing means
able to influence/change the temperature in the agricultural
facility,
[1225] a data storage device for storing growth settings for
plants, the growth settings comprising temperature profiles
(temporal and/or spatial),
[1226] a computing device, configured to fetch a growth setting for
a respective plant species from the data storage device,
[1227] the computing device, further configured to adjust the
temperature in the agricultural facility according to the
temperature profile of the growth setting by means of the sensor
device and the actuator device.
[1228] The computing device may contain the growth settings, e.g.
in a database (local, remote or cloud), for a specific plant. These
settings can be fix (preset/default). Furthermore, the computing
device may also have an interface so that the user can choose the
respective plant and the computing device picks the required growth
settings, or the user can pick the growth settings directly via the
interface. The growth settings can be different for each plant
species.
[1229] Temperature adjustments can be conducted in a smooth way
(low change gradient) or at a higher pace or in discontinues ways
(jumps).
[1230] The growth settings comprise a temperature profile over time
(temporal temperature profile). This temporal temperature profile
can be defined to support the circadian rhythm of the plant, i.e.
it repeats itself after a certain time (e.g. 24 hours). A
temperature profile may include higher temperatures during the
daytime and lower temperatures during the nighttime of the plant
(as plants can be grown in vertical farms, the daytime of the plant
can be night time outside, as electrical power is cheaper during
the night).
[1231] This allows supporting the circadian rhythm of the plant. Of
course, the time shift between the temperature profile and the
natural circadian cycle can be freely adjusted. It is also
possible, to set the `artificial circadian` cycle to longer values
than the ones for the (local) natural circadian cycle, or even to
multiples of the natural circadian cycle. Also, the duration
(hours) of `day` vs. `night` can be freely adjusted.
[1232] The temperature profile can also have different settings for
different growth phases of the plants like germination, growing,
flowering etc. Here the overall temperature profile for one growth
phase can have higher or lower average temperatures as for another
growth phase of the plant. Furthermore, the daily difference
between maximum and minimum temperature as well as the absolute
values of the temperature profile can be different for different
growth phases of the plants.
[1233] It is of course also possible, to locally set or adjust the
temperature settings (spatial temperature profile), e.g. in the
soil and at the plant top, differently, i.e. to keep or change a
temperature gradient across the height of a plant (vertical
temperature profile).
[1234] 2.sup.nd aspect of "Temperature Control": The Controlled
Agricultural System according to the 1.sup.st aspect of
"Temperature Control", wherein the temperature influencing means
are configured to influence the temperature differently in
different locations of the agricultural facility.
[1235] 3.sup.rd aspect of "Temperature Control": The Controlled
Agricultural System according to the 1.sup.st or 2.sup.nd aspect of
"Temperature Control", wherein the computing device is further
configured to keep or change a vertical temperature profile across
the height of the agricultural facility or of plants.
[1236] The controlled agricultural system can further comprise an
actuator for influencing/changing/adjusting/controlling the
temperature (temperature influencing means), i.e. a heating and
cooling system like an HVAC (heating, ventilation and air
conditioning), a heating pipe, IR (infrared)-radiator, etc. In a
vertical farm setting, the temperature influencing means can be
different at different height levels, e.g. irrigation, cool
airflow, wind channels, heat shields. Heat can also be applied by
irradiating the plants with Infrared radiation in the wavelength
range between 850 and 4000 nm, or longer. Local heating can be
applied by using e.g. a moveable infrared laser device that emits
IR-radiation on selected plants or selected groups of plants, or at
a certain position on the plant (root, buds, petals, etc.). Cooling
airflow can be applied through ducts along the plants or by focused
jet streams.
[1237] 4.sup.th aspect of "Temperature Control": The Controlled
Agricultural System according to any one of the preceding aspects,
wherein the temperature influencing means of the actuator device
are moveable and/or mobile.
[1238] 5.sup.th aspect of "Temperature Control": The Controlled
Agricultural System according to any one of the preceding aspects,
wherein the temperature influencing means of the actuator device
comprise one or more of the following means: heating device,
cooling device, HVAC, heating pipe, IR-radiator, irrigation,
cool/warm air flow, wind channel, heat shields.
[1239] Furthermore, the controlled agricultural system comprises
temperature sensors that are used to measure the temperature and
provide the information to the computing device. Based on this
information, the computing device determines the difference between
actual and target values and initiates a respective heating or
cooling of the agricultural facility. The sensors and actuators may
be controlled by respective control units.
[1240] The controlled agricultural system may also comprise sensors
to detect ambient lighting, or other ambient environmental
conditions such as CO2-content in the air. This may be used to
align or correlate the temperature-initiated circadian rhythm with
the light-induced circadian rhythm of the plants. Additional
sensors and actuators may be used to monitor and adjust (within
meaningful ranges/boundaries) other correlations, e.g. between
temperature settings and the Daily Light Integral (DLI) or the
Red/Far-Red Photon Flux Ratio, or the amount of applied fertilizers
or pesticides. Furthermore, temperature conditions can be changed
as a function of energy prices.
[1241] 6.sup.th aspect of "Temperature Control": The Controlled
Agricultural System according to any one of the preceding aspects
of "Temperature Control", wherein the sensor device further
comprises one or more sensors able to detect the growth status
(shape, size, color, etc.) of the plants, e.g. imaging devices like
cameras.
[1242] Thus, the controlled agricultural system may also comprise
sensors to detect the growth state of the plants, e.g. cameras,
including thermal and hyperspectral cameras. If a certain growth
state is detected, the computing device may switch the growth
settings accordingly.
[1243] In another embodiment of "Temperature Control", the
computing device has an internal clock (or is connected to an
external clock) and determines only based on the time passed and
the kind of plant (species) when a new growth state of the plant
will begin.
[1244] 7.sup.th aspect of "Temperature Control": The Controlled
Agricultural System according to the 6.sup.th aspect of
"Temperature Control", wherein the computing device is further
configured to determine the growth phase (e.g. breeding, greening,
flowering and harvest) of the plants based on the data from the
sensor device.
[1245] Proper research can measure and assess the necessary
temperature levels in order to reach the desired plant growth
values, like Time to Flower. Such relations can be done with all
plants (or at least with a relevant subset) and stored into a
database. The database then allows producers to adjust the
temperature levels (increase, keep, decrease) appropriately in
order to influence plant growth, flowering or harvesting
parameters. In a preferred embodiment, such a database is stored in
a data storage device connected to the computing device of the
controlled agricultural system.
[1246] In other words, proper research can measure plant growth,
plant morphology, plant chemistry, plant leaf density index, plant
color and other growth and ripening indicative parameters with
various measurement techniques (destructive and non-destructive) at
certain temperatures. These data may then be stored into the
database bank (Growth Parameters GP).
[1247] 8.sup.th aspect of "Temperature Control": The Controlled
Agricultural System according to any one of the preceding aspects
of "Temperature Control", wherein the computing device is further
configured to fetch a growth setting including a temperature
profile dedicated to the present growth phase of the plants from
the data storage device.
[1248] The controlled agricultural system may further comprise an
illumination system coupled to the computing device. The
illumination system may be illuminated using a light recipe, which
may also be stored in the computing device (if the computing units
comprises a data storage device) or in a separate data storage
device connected to the computing device. The computing device
assures that the growth settings containing the temperature profile
and the light recipe are aligned to each other (synchronized), i.e.
the "morning state" of the grow setting is also the "morning state"
of the light recipe (the same for midday, evening or settings in
between).
[1249] In another embodiment, the growth setting and the light
recipe are provided as one dataset, so that no additional alignment
is necessary.
[1250] 9.sup.th aspect of "Temperature Control": A method for
agricultural management, particularly for plant breeding, growing,
cultivating and harvesting in an agricultural facility,
comprising:
[1251] at least one controlled agricultural system according to one
or more of the 1.sup.st to 8.sup.th aspect of "Temperature
Control", and the steps of
[1252] Picking from the data storage device a growth setting
including the correlated (temporal and/or spatial) temperature
profile by means of the computing device,
[1253] Measuring the temperature in the agricultural facility by
means of the sensor device (temperature sensors);
[1254] Checking whether the measured temperature matches with the
nominal value according to the selected temperature profile;
[1255] In case of mismatch between measured and nominal
temperature: Changing the temperature according to the temperature
profile by means of the actuator device 111 (temperature
influencing means).
[1256] 10.sup.th aspect of "Temperature Control": The method for
agricultural management according to the 7.sup.th aspect of
"Temperature Control", further comprising the initial step of
[1257] Choosing a plant species by the user via the user
interface.
[1258] 11.sup.th aspect of "Temperature Control": The method for
agricultural management according to the 9.sup.th or 10.sup.th
aspect of "Temperature Control", further comprising the step of
[1259] Correlating the selected temperature profile with one or
more of the following environmental/plant conditions:
day-night-shift, circadian rhythm of the plant, illumination
conditions, plant growth phase.
[1260] 12.sup.th aspect of "Temperature Control": The method for
agricultural management according to any one of the 9.sup.th to
11.sup.th aspect of "Temperature Control", further comprising the
step of Synchronizing the temperature profile and the light
recipe.
[1261] In an embodiment/implementation for saving energy, the
temperature profile and the light recipe are synchronized to
influence the plants in the same way, for instance, to speed up
plant growth or delay plant growth (see e.g. the element "Flexible
Growth").
[1262] 13.sup.th aspect of "Temperature Control": The method for
agricultural management according to any one of the 9.sup.th to
11.sup.th aspect of "Temperature Control", further comprising the
step of
[1263] Detecting the growth status/phase of the plants by means of
the sensor device.
[1264] 14.sup.th aspect of "Temperature Control": The method for
agricultural management according to the 13.sup.th aspect of
"Temperature Control", further comprising the steps of
[1265] Comparing the presently detected growth data with the
previously detected growth data or data stored in the database and
checking by means of the computing device whether the growth phase
(e.g. breeding, greening, flowering and harvest) has changed,
[1266] If the growth phase has changed:
[1267] Picking from the data storage device a growth setting
including the (temporal and/or spatial) temperature profile
correlated to the new growth phase by means of the computing
device.
[1268] 15.sup.th aspect of "Temperature Control": A computer
program product, comprising:
[1269] a plurality of program instructions, which when executed by
a computer system of a Controlled Agricultural System according to
any one of the 1.sup.st to 8.sup.th aspect of "Temperature
Control", cause the Controlled Agricultural System to execute the
method for Agricultural Management according to any one of the
9.sup.th to 14.sup.th aspect of "Temperature Control".
[1270] 16.sup.th aspect of "Temperature Control": Agricultural
facility ((vertical) farm, greenhouse, etc.) with at least one
Controlled Agricultural System according to any one of the 1.sup.st
to 8.sup.th aspect of "Temperature Control".
[1271] Examples for Light/Growth Recipes
[1272] In practice, the selection of a growth or light recipe can
depend on many factors. Below, some influencing parameters and
boundary conditions are discussed for the purpose of illustration.
Further, some exemplary recipes are shown.
[1273] Growth Phases
[1274] Requirements for optimized lighting conditions can for
instance vary with the three distinctive growth phases, i.e.
a) Establishment growth: occurs after seed germination or while you
are rooting and establishing vegetative b) Vegetative growth:
occurs when leaves and stems are rapidly growing c) Reproductive
growth occurs as plants transition to produce flowers and
subsequent fruit
TABLE-US-00001 RECOMMENDED PPFD (.mu.mol/m.sup.2/s) Establishment
Vegetative Species Seed Cutting Vegetative Reproductive Cannabis
100-300 75-150 300-600 600+ Tomatoes 150-350 75-150 350-600 600+
Cucumbers 100-300 -- 300-600 600+ Peppers 150-350 -- 300-600
600+
[1275] An initial goal for most crops can be to establish large
leaves and stems to provide plants with enough photosynthetic area
to produce carbohydrates that will be allocated to flowers and
fruits during the reproduction phase. The allocation of
photosynthates from `sources` (active leaves) to `sinks` (roots,
shoots, flowers, and fruits) is an important balance influenced by
environmental conditions.
[1276] The principle of limiting factors also relates to
photosynthate allocation. Plants are highly adaptive, due to their
inability to relocate to an ideal environment. If an environmental
variable is not favorable, plants allocate energy resources to
increase their chance for survival. For example, in
nutrient-limited conditions, a plant will allocate resources to
expand root growth, while in light-limited conditions, resources
will be allocated to stem and leaf growth.
[1277] Light Saturation:
[1278] As light intensity (PPFD) increases, photosynthetic rates
also increase until a saturation point is reached. Every plant
species has a light saturation point where photosynthetic levels
plateau. Light saturation normally occurs when some other factor
(normally CO2) is limited.
[1279] Photoacclimation:
[1280] During establishment growth (a), light intensities need to
be kept relatively low as the plant is developing roots, leaves,
and stems that will be used to provide photosynthates during the
vegetative growth phase (b). Increasing light intensity as you
transition into the vegetative (b) and reproductive growth phases
(c) will increase the rate of photosynthesis, which will provide
the plant with more photosynthates used to develop flowers and
subsequent fruit. Plants need time to acclimate to high light
intensities (referred to as photoacclimation). If plants are
exposed to high light intensities too early in the crop cycle,
chlorophyll pigments can be damaged causing photo-oxidation
(photo-bleaching). As a general rule, increasing by 50 .mu.mol/m2/s
or less per day, can be an appropriate approach.
[1281] Photoperiodism
[1282] Photoperiodism is a plant's response to the duration of the
day (light period) in combination with the duration of the night
(dark period). This phenomenon influences different plant responses
such as flowering, vegetative reproduction and dormancy. Plants can
be classified regarding their response to the daylength. The
following are the current classes of photoperiod:
[1283] Short Day Plants (SDP)
[1284] Long Day Plants (LDP)
[1285] Day Length Neutral Plants (DLNP)
[1286] Intermediate Day Length Plants (IDP)
[1287] Dual Induction Plants (SLDP)
[1288] Daily Light Integral
[1289] The term daily light integral (DLI) is used to describe the
total quantity of light delivered to a crop over the course of an
entire day. The DLI is reported as the number of moles (particles
of light) per day. Knowing the quantity of light delivered
throughout the day can be a useful measurement for estimating the
effect of sunlight on plant growth. Many important plant growth
responses, such as biomass accumulation, stem diameter, branching,
root growth and flower number are closely correlated to DLI. DLI
can be a tool for managing the light environment to optimize plant
growth.
[1290] Carbon Dioxide
[1291] Carbon dioxide (CO2) enrichment in a controlled agricultural
environment can improve the yield of high PPFD crops. Typically,
plants have a light saturation point where the maximum rate of
photosynthesis is reached at a specific light intensity. However,
at ambient atmospheric CO2 levels (.about.400 ppm) it is the
limited availability of CO2 that can restrict photosynthetic
activity, not the intensity of light. Generally, optimum levels of
CO2 will be two to four times the normal atmospheric levels
(800-1,400 ppm CO2) when growing under high PPFD conditions. It may
be recommended to supplement>800 ppm CO2 into a controlled
agricultural environment when the plants are provided with >500
.mu.mol/m2/s. When light intensity is increased, also CO2 levels
can be increased as plants acclimate to increased PPFD.
[1292] Leaf Surface Temperature
[1293] Plant growth and development can also be influenced by
temperatures at the growing points of plants (i.e., roots and shoot
tips). It is rather plant temperature (not air temperature) that
drives physiological responses in plants. Air temperature can
differ by as much as 12.degree. C. from plant temperature,
depending on the used light source (e.g. High Pressure Sodium HPS,
Metal-Halide MH, or LED), light intensity, humidity, and air speed.
For example, HPS lights emit a large percentage of their energy in
the infrared (IR) range (800 nm-1000 nm) which is not
photosynthetically active yet significantly increases plant
temperature, whereas suited LED-based systems produce very little
radiant heat.
[1294] Photothermal Considerations
[1295] Crops can have a species-specific base temperature, at which
growth and development will not occur. Above the base temperature,
growth and developmental rates increase with temperature until an
optimum temperature is reached. Above the optimum temperature,
plant development decreases. Light intensity primarily influences
the rate of photosynthesis, while plant temperature primarily
influences developmental rates. Net photosynthesis under increased
PPFD will increase as temperatures approach the optimum temperature
for the species of grown plants; however, the optimum temperature
for photosynthesis depends on the concentration of CO2 in the
growth environment. An important correlation can be that with
increased temperature, also the morphology of the plant will be
changed by increasing developmental rates. The ratio between light
intensity and temperature is known as the photothermal ratio. If
one chooses to grow at warmer temperatures (.gtoreq.80.degree. F.),
it can be necessary to ensure that an adequate light intensity
(.gtoreq.500 .mu.mol/m2/s) is provided, otherwise plants could be
produced that have increased internode distance, small stem
caliper, and an overall spindly growth habit.
[1296] Temperature Differential
[1297] The difference between day/night temperatures (DIF) can also
influence plant morphology. For example, if day/night air
temperature is 24/10.degree. C., a +DIF of 12.degree. C. results,
which will promote stem elongation of most crops. Alternatively, a
warmer night temperature 18/25.degree. C. (day/night) will result
in a -DIF of 12.degree. C., which will suppress stem
elongation.
[1298] Relative humidity, vapor pressure deficit, and air movement
Relative Humidity (RH) is the amount of humidity present at a given
temperature and is expressed as a percentage. When air is
completely saturated, it has a RH of 100%. Temperature, RH, and air
movement can be three main variables that influence the movement of
water throughout a plant. Evapotranspiration is the process plants
use to cool leaf surfaces--as the temperature of a leaf increases,
plants pull more water from the growing media and water is
evaporated from the leaf surface, as a result, the leaf temperature
decreases.
[1299] Vapor Pressure Deficit (VPD) can be a valuable tool to use
when growing in a controlled environment. Maintaining a proper VPD
will help to reduce plant stress brought on by either excessive
transpiration (high VPD values) or the inability to transpire
adequately (low VPD values). When the VPD is too low (humidity too
high) plants are unable to evaporate enough water to enable the
transport of mineral nutrients (such as calcium), and in cases
where VPD is extremely low, water may condense on the plant surface
and provide a medium for fungal growth and disease.
[1300] Air Movement
[1301] Proper Air Movement can also be an environmental variable
that can be adjusted in controlled environment agriculture. Air
flow can be critical to break the boundary layer around a leaf and
allow transpiration and CO.sub.2 uptake. It can also be beneficial
to provide uniform temperature, humidity, and CO.sub.2
concentrations in a controlled agricultural environment.
Furthermore, an air flow against the plants will result in stronger
growth of e.g. the stems. For instance, maintaining an air speed of
0.8-1.2 m/s at the plant canopy can optimize plant growth and
development.
[1302] Exemplary Growth Recipes
[1303] Below, some exemplary growth recipes are shown. The first
one relates to lettuce, in particular to improving red coloration
of red leaf lettuce. The second one relates to basil. These two
growth recipes are static, which means that the same growth
conditions are applied over the whole growth cycle. The third
growth recipe, which relates to Cannabis, is a dynamic recipe. For
the flowering, the intensities given on the right are increased to
a threefold value. In all recipes, the intensities are in indicated
in .mu.mol m.sup.-2 s.sup.-1.
TABLE-US-00002 1st Growth Recipe Spectrum Crop Lactuca sativa
'Diablotin' UV 0 Light intensity 240 .mu.mol m.sup.-2 s.sup.-1 Blue
60 Photoperiod 16 day/8 night Green 0 Temperature 20.degree. C.
day/18.degree. C. night Hyper Red 180 Humidity 60-70% Far Red 0
Growth Cycle 28 days Warm White 0
TABLE-US-00003 2nd Growth Recipe Spectrum Crop Ocimum basilicum UV
10 'Keira' Light intensity 300 .mu.mol m.sup.-2 s.sup.-1 Blue 60
Photoperiod 18 day/8 night Green 30 Temperature 24.degree. C.
day/22.degree. C. night Hyper Red 170 Humidity 60-70% Far Red 0
Growth Cycle 50 days Warm White 30
TABLE-US-00004 3rd Growth Recipe Spectrum Crop Cannabis
sativa/indica UV 5 Light intensity 330 .mu.mol m.sup.-2 s.sup.-1
Blue 70 Photoperiod 16 day/8 night Green 50 (for young plants) 12
day/12 night Hyper Red 200 (for flowering) Temperature 20 Far Red 5
7.degree. C. day/24.degree. C. night Humidity 60% Warm White 0
[1304] A further example of dynamic growth recipe is shown below.
It relates to lettuce and shows three alternatives PPFD I-III.
TABLE-US-00005 Adventitious Temperature rooting [.degree. C.]
Cultivation 20.degree. C. 18.degree. C. Rel. Air Day Night humidity
[%] Germination 60-70% 60-70% Adventitious rooting Cultivation
60-70% 60-70% Air flow 0.1 [m s.sup.-1] Light intensity 240
[.mu.mol m.sup.-2 s.sup.-1] Color PPFD I PPFD II PPFD III Spectral
UV-A 10 distribution (380 nm) (PPFD) Blue 50 60 50 90 50 80
[.mu.mol m.sup.-2 s.sup.-1] (450 nm) Green 30 30 30 (520 nm) Hyper
Red 120 180 120 90 145 90 (650 nm) Far Red 10 10 15 (730 nm) Warm
White 33 33 (2700 K) First Last First Last First Last 20 10 20 10
15 15 days days days days days days Sum 240 240 240
[1305] A further example for influencing the plant properties by
defined environmental conditions is a strengthening of the stem of
flowers, for instance of petunia. A strengthening of the stem can
for instance be achieved by illuminating the plants during the
growth phase (after the formation of the first leaves until flower
formation) with green light, e.g. with a wavelength between 500 nm
and 550 nm and an intensity of at least 400 .mu.mol m.sup.-2
s.sup.-1.
[1306] Another example is an extension of the flowering, which can
be achieved by an illumination with a wavelength between 400 nm and
800 nm, wherein the intensity between 450 nm and 500 nm amounts to
more than 45% of the total intensity.
[1307] Luminaire
[1308] "Light Guides"
[1309] According to the element "Light Guides" of the disclosure, a
light module comprising at least one light guide, which enables
improved illumination of plants, is proposed. Furthermore, an
agricultural lighting fixture comprising such a light module and a
method for agricultural management providing improved illumination
by means of the agricultural lighting fixture is proposed.
[1310] Below, various aspects and details of "Light Guides" are
described.
[1311] 1.sup.st aspect of "Light Guides": A light module, in
particular for plants, comprising holding or fixation means and at
least one light emitting element, wherein the light-emitting
element is mountable to the holding means and wherein the
light-emitting element comprises at least one light guide which is
arranged in a pre-determined distance, in some
embodiments/implementations in a common plane, to a target
area.
[1312] Light Modules, Light Emitting Elements, Light Guides
[1313] According to an embodiment of "Light Guides", a light module
is provided, in particular for illuminating plants. The light
module comprises holding or fixation means adapted to hold or fix
the light module in place or fasten the light module to a
supporting structure, such as a wall, a ceiling, a meshwork, a
grid, beams or other structures. The holding means may also be
provided to support parts of the light module. Separate holding
means may also be provided, in order to hold or fix the light
module and to support elements of the light module. The light
module also comprises at least one light-emitting element. The
light module and/or the light emitting element can comprise or
include a transparent material. The light-emitting element of the
light module comprises at least one light guide, which is arranged
in a predetermined distance to the target area. The light guide, in
particular an elongated light guide, can be arranged in a, usually
horizontal, plane, with a predetermined distance to the target
area.
[1314] The light guide can be placed such that it vertically
extends downward, i.e. towards the plants or the target area. One
or more light guides may be provided, which have portions arranged
horizontally, i.e. forming a plane basically parallel to a target
area and having portions arranged vertically, i.e. substantially
normal to the target area or at least inclined with respect to the
target area. However, multiple light guides may be provided wherein
at least one of the light guides is arranged horizontally, and at
least one, in some embodiments/implementations multiple, light
guides are arranged vertically or at least inclined with respect to
the target area.
[1315] 2.sup.nd aspect of "Light Guides": The light module
according to the 1.sup.st aspect of "Light Guides", wherein the
light-emitting element extends in different vertical layers, in
some embodiments/implementations the layers forming planes and
having a predetermined or adjustable distance to one another.
[1316] Providing light guides on different vertical layers or
spanning different vertical layers, in particular between the
plants, and controlling light parameters in a vertical direction,
i.e. differently for different vertical layers, may improve
illumination and light supply to the plants to be grown.
[1317] 3.sup.rd aspect of "Light Guides": The light module
according to the 2.sup.nd aspect of "Light Guides", wherein the at
least one light guide is arranged in the at least two layers.
[1318] 4.sup.th aspect of "Light Guides": The light module
according to the 2.sup.nd or 3.sup.rd aspect of "Light Guides",
wherein the light-emitting element comprises multiple light guides,
which are arranged in the at least one layer.
[1319] The light module according to the present disclosure may
thus also be referred to as an adjustable inter-canopy light
module, as it allows to adjust light parameters in different
vertical layers even between plants.
[1320] 5.sup.th aspect of "Light Guides": The light module
according to the 4.sup.th aspect of "Light Guides", wherein the
multiple light guides are controllable, in some
embodiments/implementations separately, by a control unit.
[1321] According to an embodiment, a light guide may contain light
sources (e.g. LEDs) that can be controlled individually or in
groups. In particular, these light sources may be placed above or
adjacent to each other along the longitudinal length of the light
guide.
[1322] 6.sup.th aspect of "Light Guides": The light module
according to the 5.sup.th aspect of "Light Guides", wherein at
least one light guide can be controlled to provide a different
spectrum of light and/or a different light recipe compared to at
least one other light guide.
[1323] The light sources may be individual LEDs or one or more
groups of LEDs. These light sources may emit light of different
spectral composition, thus allowing control and adjustment of the
light spectrum emitted to the plants along a vertical
direction.
[1324] In an embodiment, the light-emitting element or at least the
light guide, may be placed with a uniform distance to the target
area and, eventually, to the plants growing in the target area. In
particular, this may also allow the light-emitting element or
portions of the light-emitting element to be placed such that a
uniform distance with respect to the plants may be adjusted, even
if the size of the plants, in particular in a vertical direction,
is not uniform. That way, the element "Light Guides" of the
disclosure may allow vegetated areas and/or plants to be
illuminated more evenly.
[1325] The use of light guides may allow the reduction of the
distance of the light emitting element to the plants or target
area, as they may provide more uniform illumination compared to
point sources, such as single LED elements.
[1326] Further, according to an embodiment, the light module, or at
least the light guide may be arranged in a horizontal way above the
target area. A target area with this respect is an area, which is
to be illuminated by the lighting fixture. It is understood that
neither the lighting fixture, the light module, nor the light guide
have to be arranged horizontally with respect to the target area,
i.e. arranged in parallel to the target area, even if the lighting
fixture, the light module, or the light guide may, at least in
places, be arranged parallel to the target area.
[1327] According to another embodiment, the light-emitting element
of the light module extends in different layers, wherein in some
embodiments/implementations the layers are forming planes and in
some embodiments/implementations are having a predetermined
distance to one another. That way, the present disclosure may
enable to further direct light to different regions of the plant,
in particular to different vertical sections of the plant.
Consequently, those leaves at the tip of the plants may be arranged
between two layers of the lighting fixture, such that leaves and
other plant sections below the uppermost leaves may be supplied
with sufficient light. This may increase the agricultural outcome
(yield). Those layers or parts of the layers being situated below
the uppermost leaves may be controlled to emit light at a reduced
or an increased intensity or with an altered spectrum of light,
respectively a different light recipe. The light characteristics
like photon flux quantity and/or photosynthetically active
radiation (PAR) and/or light spectrum and/or operating conditions,
for example the ON/OFF cycles of the provided illumination, and/or
illumination phases with increased or reduced light intensity, e.g.
boost and dim phases, may be changed over time as the plants grow
and change their morphology.
[1328] According to an advantageous refinement, the at least one
light guide of the light module is arranged in more than one of the
layers forming the light-emitting element. In particular, the at
least one light guide may be arranged in the at least two layers
which can be stacked vertically on top of each other or, at least,
in more than one of the layers. Alternatively, more than one light
guide may be provided in the at least one or in more layers of the
light module. This is to say that one or more light guides may be
provided in one or more layers of the light module. A "layer"
according to the element "Light Guides" of the disclosure means a
portion of the light module that is adapted to illuminate a
different section of the plant, in particular in a vertical
direction, compared to another layer. Different layers may also be
differentiated by their individual distance to the target area or
any of the target areas.
[1329] As at least portions of the light guides may be provided
along a vertical direction, vertical variation of emitted light
spectra may be enabled by controlling light sources within a light
guide. Such individual light sources being arranged in a light
guide may thus form vertical layers as understood in the context of
"Light Guides".
[1330] 13.sup.th aspect of "Light Guides": The light module
according to any one of the 1.sup.st to 12.sup.th aspects of "Light
Guides", wherein the at least one light-emitting element and/or the
at least one light guide comprise or include fiberglass or
plastic.
[1331] This may allow for better defining light guiding properties,
amount and location of the out-coupling of light out of the light
guide and other parameters. For instance, at predetermined
positions, the light guide may be prepared to couple light out of
the light guide. In particular, the light guide may comprise
roughened portions, where the light can leave the light guide at
such predetermined positions.
[1332] 14.sup.th aspect of "Light Guides": The light module
according to any one of the 1.sup.st to 13.sup.th aspects of "Light
Guides", wherein the at least one light guide comprises roughened
portions adapted to guide light to predetermined positions.
[1333] It is also possible that the light guides are designed such
that light with a predetermined wavelength or within a
predetermined wavelength range may couple out of the fiber at one
position, whereas light of different wavelength continues to travel
within the light guide and may exit at another location. Thus, the
"Light Guides" may enable to provide light in an advantageous
manner compared to existing solutions.
[1334] While light guides commonly are perceived to be fiber-like
structures, such as optical fibers, any design suitable for guiding
light may be applied for light guides within the meaning of the
"Light Guides".
[1335] 15.sup.th aspect of "Light Guides": The light module
according to any one of the 1.sup.st to 14.sup.th aspects of "Light
Guides", wherein at least one light guide is a liquid light guide,
in some embodiments/implementations adapted to guide light of the
UV-part of the light spectrum.
[1336] In an advantageous refinement, the light guide may for
instance be a liquid light guide. A liquid light guide within the
perception of "Light Guides" refers to any kind of light guide,
which, at least partially, uses a liquid medium as a light guide,
to guide light of one or more wavelengths. Liquid light guides may
be preferable in order to guide light comprising ultraviolet (UV)
light. Thus, UV light may be guided to plants and even to
predetermined sections of plants. Such light guides may be used
e.g. in order to guide the light below the uppermost layer of
leaves, i.e. the canopy. Thus, bottom sides of the plants and in
particular of the leaves may be illuminated with light, e.g. UV
light.
[1337] UV light may particularly be used to dispatch or control or
minimize pests of various origins or fight at least some diseases
(see also the element "Prophylaxis" of the disclosure). The light
guides may also be provided in close proximity to or directly on
the ground, i.e. the target area, in order to dispatch pests or
vermin living on the ground. This may increase agricultural output
and reduce crop failure. This again may allow enhancing
predictability of the agricultural output and facilitate logistics
before and after harvesting (see also the element "Yield
Prediction" of the disclosure).
[1338] 16.sup.th aspect of "Light Guides": The light module
according to any one of the 1.sup.st to 15.sup.th aspects of "Light
Guides", wherein the light-emitting element comprises non-emitting
portions and/or reflective portions and/or light conversion
portions in order to emit light in the pre-determined
direction.
[1339] In addition to or separately from the light guides, the
light-emitting element may comprise sections with no or only
minimal emission. For instance, the light-emitting element may
comprise non-emitting portions and/or reflective portions, in order
to emit light in a predetermined direction or to block it
completely. Such non-emitting portions may be portions, within
which the light guide is completely covered by a non-transparent
and/or absorbing layer or is provided within a channel or the like.
Reflective portions of the light-emitting element may be sections,
where the light is coupled out of the light guide to one or more
desired directions, whereas no emission takes place in other,
non-desired directions. The reflective portions may in particular
comprise a reflective layer provided on the light guide, in order
to prevent light already from coupling out of the light guide.
Further, the reflective portions may be provided such that light,
which was emitted in a non-desired direction, will be incident on a
reflective element to be reflected into a desired direction. A
desired direction for instance would be toward a plant, a target
area or the like. It is also within the framework of the aspect
"Light Guides" to coat a light guide with a light conversion
material or to implement such a light conversion material into a
light guide, thus enabling a conversion of incoming wavelengths
(excitation wavelength) into other ones, e.g. in the manner of
down-conversion to longer wavelengths. By this, a light guide can
provide different light spectra at different locations depending on
the use of conversion materials and mix thereof.
[1340] 17.sup.th aspect of "Light Guides": The light module
according to any one of the 1.sup.st to 16.sup.th aspects of "Light
Guides", wherein the light-emitting element comprises a light
source which comprises a semiconductor element, in some
embodiments/implementations an LED or OLED element, in some
embodiments/implementations a laser element.
[1341] The light-emitting element may in particular comprise one or
more semiconductor elements as light sources. In some
embodiments/implementations the light source may comprise or
include a light emitting diode (LED) and/or an organic light
emitting diode (OLED). The LEDs may be direct emitting diodes or
so-called phosphor-converting diodes. In some
embodiments/implementations, the light source may comprise or
include a laser element. While, in some
embodiments/implementations, the laser element is a semiconductor
element, in some embodiments, the laser element may be based on
non-semiconductor technologies. Such a laser element can also be
used as part of a Laser Activated Remote Phosphor (LARP) conversion
device. Combination of light guides with semiconductor light
sources may allow simplified coupling of light into the light guide
and delivery of the light to the region of interest, e.g. the
plants, specific plant parts, the target area and the like.
[1342] Advantageously, light originating from different light
sources and/or of different wavelength may be combined in the light
guides, in order to provide light with a pre-determined or desired
spectral composition. Two or more light guides can be connected or
combined into a single light guide, at least over a certain common
length, and be separated again. Thus, different light guides can
form a mesh of light emitting elements with similar or different
lighting properties that can complement each other, for example
with regard to locally emitted light intensity, spectrum, emission
angle, angular beam spread, and operating modes. It is also within
the framework of this disclosure that a light guide can be used as
conducting means, for example by placing pipes or other
transporting means inside a hollow light guide, to apply nutrients,
fertilizer, irrigation and the like to the plants. A light guide
can be made watertight so that it can also be used in aquaponics
growth settings, e.g. as described for instance in the element
"Aquaponics" of the group "System Setup" of the disclosure.
[1343] A light guide can have various cross sections and/or
geometrical product dimensions along its axis or any other spatial
extension. A light guide can emit different light recipes and use
different light-changing or influencing means, as described above,
along its circumference thus providing different lighting scenarios
into different radiation angles, thus making it more versatile for
plant illumination.
[1344] 7.sup.th aspect of "Light Guides": The light module
according to any one of the 1.sup.st to 6.sup.th aspect of "Light
Guides", wherein the at least one light guide comprises flexible
material.
[1345] This allows directing the light along a definable, arbitrary
path toward the target area or sections of the plants. This further
allows mounting the light guide to supporting structures, such as a
meshwork, which is distributed over the target area and in
particular over the plants. The light guides may further be
rotatable designed, in order to further individualize their
respective emission scheme and alter or adapt the emission
direction.
[1346] Control Unit and Lighting Parameters
[1347] Advantageously, the light guide or multiple light guides or
different fractions of one or more light emitting elements or of
the light module are controllable by means of a control unit. More
advantageously, one or more light guides and/or light emitting
elements are controllable separately from one another. With that
respect, the control unit may be configured such that lighting
parameters, such as wavelength, spectrum, spectral composition,
light intensity, time of illumination or other parameters are
controlled.
[1348] Further, the control unit may be enabled to, additionally or
exclusively, control mechanical parameters of the light-emitting
element and/or the light guide, such as the position relative to
the target area, the plant to be illuminated, the holding means, or
between different parts of the light module and/or the orientation
thereof and/or the distance and angle between two or more light
guides.
[1349] The control unit may also control light of at least one
light guide or light-emitting element such that a different light
recipe compared to at least one other light guide or light-emitting
element is applied. This may allow providing the right illumination
to the different parts of the plants, which, eventually, may
increase the yield and quality of the agricultural output
(agricultural produce).
[1350] A light recipe comprises information and control data of
illumination with respect to time, location, light intensity, and
other parameters suitable or necessary to control growth of the
plants or phases of plant growth. A light recipe thus also includes
dark phases, boost phases, dim phases and control of different
spectra to be delivered to the plants. A light recipe may comprise
control data for an entire life cycle of a type of plant or various
types of plants. A light recipe may also comprise control data
specific for abnormal events, such as diseases or pests, specific
periods, such as germination or harvesting, or accelerated
ripening. In particular, a light recipe may comprise information to
control light parameters to vary over time. Light recipes may be
provided to account for plant parameters such as growth phases or
ripening phases of the plants or goods to be harvested. Such plant
parameters may be determined by means of sensors, the measured data
of which being processed in the control unit, particularly for
monitoring the health and growth of the plants (see also the
element "Plant Health and Growth" of the disclosure).
[1351] According to an exemplary light recipe, those light-emitting
elements or light guides situated directly above a plant or a tip
of a plant, may be operated at reduced intensity, while those light
emitting elements or light guides or parts thereof situated below
the tip of the plants may be operated at increased intensity or
spectrum, to compensate for the shading effect of higher leaves, or
vice versa.
[1352] 8.sup.th aspect of "Light Guides": The light module
according to any one of the 2.sup.nd to 7.sup.th aspects of "Light
Guides", wherein the light-emitting element provided in a layer
closer to the target area is adapted or adaptable to emit light
with higher portions of at least one of blue and/or red and/or
far-red, and/or infrared and/or ultraviolet compared to the
light-emitting element provided in a layer further away from the
target area.
[1353] As an example, at least one light-emitting element or light
guide that is provided in a layer closer to the target area
compared to a light emitting element or light guide provided in a
layer further away from the target area is adapted to emit light
with a higher portion of blue light. Arranging that light emitting
element or the respective light guide of this light-emitting
element below the uppermost leaves of the plants allows delivery of
light with an increased amount of blue wavelengths to the lower
parts of the plants. As, commonly, plants in the lower sections do
receive a reduced amount of blue light due to the shading and
absorption by higher leaves, increased illumination of these lower
sections may increase the agricultural output by compensating the
shading due to higher leaves. In a similar way, other light spectra
can be applied, like red, far-red, infrared, and ultraviolet.
[1354] In particular, the light emitted by such a lower placed
light emitting element or light guide can be adjusted, for example
with respect to light intensity, or may be spectrally changed over
time as a function of plant growth or plant morphology. The light
emitting element may thus form a light element, which is spectrally
adaptable in a vertical direction. The light emitting element may
further be temporally controllable, i.e. spectral composition,
light intensity and/or further parameters according to an
applicable light recipe may be controlled to vary over time.
[1355] 9.sup.th aspect of "Light Guides": The light module
according to any one of the 1.sup.st to 8.sup.th aspect of "Light
Guides", wherein the light-emitting element comprises a wire
netting, which is arrangeable in a predetermined shape on or over
the target area.
[1356] In particular, the wire netting may be arrangeable over the
plants to be illuminated. More advantageously, the holding means of
the lighting fixture may comprise the wire netting. The light
guides may be mounted to or attached to the wire netting. That way,
light may be delivered more accurately, under definable incident
angles and in a more individualized manner. Further, the shape and
size of the meshwork may be altered, e.g. over time. Size and shape
of the meshwork may be adaptable e.g. to the size and/or
morphological state and/or morphological change of the growing
plants.
[1357] 10.sup.th aspect of "Light Guides": The light module
according to any one of the 1.sup.st to 8.sup.th aspect of "Light
Guides", wherein the light guide is braided or twisted around the
light-emitting element.
[1358] The light guide may in particular be braided or wrapped
around the light-emitting element, e.g. a wire netting of the
lighting fixture. The wire netting may also be provided as a
separate component. In such embodiments, the light-emitting element
may be supported by the wire netting or meshwork of the
netting.
[1359] Fabric
[1360] 11.sup.th aspect of "Light Guides": The light module
according to any one of the 1.sup.st to 8.sup.th aspect of "Light
Guides", wherein the holding means include or comprise a fabric,
with at least one light guide of the at least one light-emitting
element being provided on or in the fabric.
[1361] The fabric may in particular form a mat-like structure. On
or in the fabric, a light guide of the at least one light module is
provided.
[1362] 12th aspect of "Light Guides": The light module according to
the 11.sup.th aspect of "Light Guides", wherein the fabric is
movably connected with respect to the holding means.
[1363] Further, the fabric may be connected movably with respect to
the holding means of the light module. In particular, the light
guide may be woven into the fabric. The fabric thus may be arranged
over the target area, i.e. over the plants to be illuminated.
Following the growth of the plants, the fabric may be moved, e.g.
raised, in order to keep the distance of the light guides from the
plants constant, or, as the case may be, according to an individual
or predetermined adjustment or control plan.
[1364] The fabric may also be designed rollable. This may
facilitate access to the plants for watering, harvesting, visual
inspection or other tasks, by simply removing the fabric. Furling
or unfurling of the fabric may either be actuated manually or
automatically. Furling and unfurling of the fabric may in
particular be controlled by a control unit, in some
embodiments/implementations by the same control unit, which also
controls the light parameters. Providing such a fabric may also
allow to store away the fabric, if it is not needed, in a
convoluted state. This may reduce storage place and facilitate
handling with the light emitting element.
[1365] Light Source and Control
[1366] 18.sup.th aspect of "Light Guides": The light module
according to any one of the 1.sup.st to 17.sup.th aspect of "Light
Guides", wherein the light source of the light emitting element is
arranged in a remote position from the light-emitting element.
[1367] The light source, in fact, may be placed remote to the
vegetated (cultivated) areas, even in separated rooms or on
different floors of a vertical farm. That way, heat generated by
the light sources or by the control unit or units may be utilized
for heating or climate control of the vertical farm, without
locally and uncontrollably affecting climate conditions in the
vertical farm. The light guides are then provided in order to
deliver the light from the light sources to the respective target
areas.
[1368] A heat pump may be provided, in order to utilize the heat
generated by the light sources. Alternatively, a water cycle,
ventilation system or similar may be provided in order to utilize
the heat generated and to cool the light sources and other
components, if required. Heat generated may thus be used for
heating in air conditioning systems, warm water supply or such,
even in locations remote from the heat source. Alternatively, if
need may be, the heat may be redirected to the plants (see also the
aspect "Heat Reflector", below).
[1369] Light guides or groups of light guides intended for the same
one or more wavelengths or spectral composition may be coupled to
light sources, in particular semiconductor light sources, which may
be separately controllable. That way, groups of light sources may
be formed. "Separately controllable" in this context shall mean
that one or more first light sources may be controlled independent
from at least one or more second light sources. Control parameter
may be, among others, spectral composition, light intensity,
emission time and others. A semiconductor light source may emit
light of essentially one wavelength or of multiple wavelengths,
depending on the type of light source used.
[1370] Thus, different layers of a light emitting element or
different sections thereof may be provided with an individual light
recipe. This may be realized by using light guides of one group or
another. That way, light illumination of the plants may be
improved, in particular of plant sections below the uppermost leave
layer.
[1371] Sensors
[1372] Accordingly, the at least one light guide can bring light
between the leaves of a plant, which may be referred to as
inter-canopy lighting. According to various embodiments of the
aspect "Light Guides", sensors, such as optical, thermal, spectral,
or other sensors, can be attached to the at least one light guide
or implemented within a light guide, to the at least one light
emitting element and/or to the light module. The sensors may also
be provided independent of a light guide at the light emitting
element, the light module, or at any position within the
agricultural lighting fixture or connected therewith. "Connected"
in this context shall mean any connection, physical or via data
connection or any other interaction between sensor and lighting
fixture, including common databases or similar.
[1373] The sensors may check parameters like temperature, humidity
or illumination. The sensors may also be attached to a holding or
supporting structure, such as wires, used to hold the crop or any
other installation between the crops. The sensors may be used to
measure the micro-climate within the canopy, for example air
temperature, ventilation, humidity, CO2 concentration, pheromone
concentration, concentration of toxic substances released from a
plant, and the like. A computing unit considers these data to
optimize the growth parameters, e.g. temperature, humidity, light,
for the specific plant. The computing unit may be a part of the
control unit or provided as a separate element. The sensors could
be connected to a power line and to a network line for data
transfer. The sensors may also be battery operated. The sensors may
transmit data through a data connection, such as LAN, WLAN,
Bluetooth, radio, RFID, near field communication or similar.
[1374] Agricultural Lighting Fixture
[1375] 19.sup.th aspect of "Light Guides": Furthermore, an
agricultural lighting fixture, in particular for plant
illumination, comprises a control unit and at least one light
module according to any one of the 1.sup.st to 18.sup.th aspects,
wherein the control unit is adapted to control at least one of
light intensity, illumination time, illuminated area, spectral
composition of the light, position of at least one light guide,
light emitting element or of the light module, in particular as a
function of plant growth and/or plant morphology.
[1376] Agricultural Lighting fixtures provide lighting of plants,
algae, fungi, transgenic plants, and any other edible or useable
produce as well as for animals, including transgenic animals,
insects, bacteria, and viruses with natural and/or artificial
electromagnetic radiation.
[1377] Agricultural Lighting is applied in order to influence,
stimulate and control the growth and well-being in all stages of
the individual development including shoot development,
reproduction, morphology, maturation, harvesting and storage. In
the following, for the sake of convenience, the term `light` shall
encompass the entire electromagnetic wavelength range from the
ultraviolet (100 to 400 nm) to the visible (400-780 nm) to the
infrared (780 nm to 1 mm) spectral range.
[1378] Agricultural lighting fixtures can be part of a fixed,
moveable or portable growth or storage place. Agricultural Lighting
fixtures can contain light sources, light source drivers and
controllers, sensors, optical components, actuators, as well as
data storage, processing and one-directional, bi-directional and
multi-directional communication devices. Agricultural Lighting
fixtures can contain heating and cooling devices as well as heat
deflecting devices, such as heat reflective walls (see also the
element "Heat Reflector" of the disclosure, below).
[1379] Agricultural Lighting fixtures can contain or be made of
transparent polymeric materials, translucent materials, and
specular or diffusive materials.
[1380] Agricultural Lighting fixtures for plant growth can be
suited to modulate light generated by the light sources with a
rhythmic or aperiodic signal produced artificially or a rhythmic
signal extracted from sound present in nature, and can be suited to
illuminate a plant with the modulated light.
[1381] Agricultural Lighting fixtures can be operated based on the
execution of light recipes. Agricultural Lighting fixtures can have
individual identifiers, like an RFID chip or a digital signature or
IP-address, allowing them to be connected to a computer system or
cloud computer network, so that they can be part of an
Internet-of-Things (IOT)-system, or connected to an Artificial
Intelligence (AI) machine in order to provide useful growth
predictions (see also the aspect "Yield Prediction") and applicable
illumination settings.
[1382] Agricultural Lighting fixtures can be suited for underwater
lighting, sweet and salt water.
[1383] Agricultural Lighting fixtures can be part of an Industry
4.0 standard.
[1384] Lighting fixtures of agricultural purposes can contain
artificial light sources like Light Emitting Diodes (LED) with or
without conversion by using a fluorescent substance, commonly
referred to as phosphor conversion, Laser diodes, OLED light
emitting material on the basis of organic materials, Quantum Dot
light emitters, Fluorescent lamps, Sodium low and high pressure
lamps, Xenon and Mercury Short Arc lamps, Halogen lamps, and the
like. Therefore, such light sources may also be used in a light
module according to various aspects of the present disclosure.
[1385] Lighting fixtures of agricultural purposes can contain
fluorescent or phosphorescent substances, for example applied to
the fixture surfaces. The light source of the lighting fixtures of
agricultural purposes can be adjusted or be optimized for use in
connection to optical components, such as reflectors, symmetrical
or asymmetrical lenses, filters and so on.
[1386] Lighting fixtures of agricultural purposes can be grouped
together or can be arranged in a network or wire-frame manner.
[1387] An agricultural lighting fixture can be rotated, for example
from lighting top-down to lighting bottom-up at various stages of a
rotary growth cabinet.
[1388] An agricultural lighting fixture can be made of a flexible
material that is formable, e.g. bendable, and can therefore be
changed in form and shape. An agricultural lighting fixture may
comprise of one or several lighting modules that can be changed,
individually or as a group, in their form and/or position thus
altering the shape and appearance of the fixture.
[1389] Method for Agricultural Management
[1390] 20.sup.th aspect of "Light Guides": Furthermore, a method
for agricultural management, in particular for plant growth, with a
light module according to any one of the 1.sup.st to 18.sup.th
aspects, comprises the steps of providing a light-emitting element
on or above a target area, in some embodiments/implementations the
target area being populated by one or more plants, seedlings and/or
seeds, controlling, by means of a control unit, parameters of light
being emitted toward the target area, wherein the light emitting
element is provided, in some embodiments/implementations movably,
in a predetermined distance away from the target area.
[1391] By means of a control unit, parameters of light, which is
emitted toward the target area, are controlled. In particular, the
control unit may comprise at least one light recipe. The light
recipe allows controlling a specific, predetermined or adaptively
defined, period of plant growth, including the entire life-cycle of
a plant.
[1392] The light-emitting element and/or the light guide is
provided in a predetermined distance away from the target area. The
light-emitting element and/or the light guide may be provided
movably, i.e. such that the distance thereof with respect to the
target area with the plants, and thus the distance to the plants to
be grown, may be varied. That way, the distance between the
light-emitting element and the plants may be adjusted, in some
embodiments/implementations to an optimal distance in order to
provide a desired light recipe. The control unit may be provided to
control the distance of the light emitting element to the
plants.
[1393] According to "Light Guide", light of different spectral
composition, among other parameters, may be provided in different
vertical layers, such as above the plants and between the plants,
referred to as inter-canopy lighting. Lighting parameters may be
set or controlled to vary over time. Variation of lighting
parameters may depend on predetermined light recipes and/or data
collected, e.g. by means of sensors, and/or manual input. In
particular, lighting parameters such as illumination time or
spectral composition, and in particular spectral composition or
other parameters in different vertical layers, may be defined based
on plant growth phases, ripening phases, morphological condition,
plant size, but also based on economic factors such as planned
harvesting, delivery dates, research and others.
[1394] "Failure Detection"
[1395] According to the element "Failure Detection" of the
disclosure, a controlled agricultural system with a light fixture
is proposed that is configured to be able to detect and, in some
embodiments/implementations, locate a failing light source quickly
so that a repair or replacement action, or any other
countermeasure, can be taken promptly.
[1396] 1.sup.st aspect of "Failure Detection": More specifically,
the controlled agricultural system, comprises a light fixture with
a light source for providing agricultural lighting, wherein the
Controlled Agricultural System is configured for an automatic
failure detection, namely for detecting a reduced emission and/or
total failure of the light source.
[1397] 2.sup.nd aspect of "Failure Detection": The controlled
agricultural system according to the 1.sup.st aspect of "Failure
Detection", comprising a current sensor, the Controlled
Agricultural System being configured to measure, for the failure
detection, an electrical current of the light fixture and/or the
light source.
[1398] In a preferred embodiment, a current sensor is provided for
measuring an electrical current for the failure detection.
[1399] 3.sup.rd aspect of "Failure Detection": The controlled
agricultural system according to the 2.sup.nd aspect of "Failure
Detection", wherein the light fixture comprises a plurality of
light sources, the Controlled Agricultural System being configured
to measure the electrical current of a subset of the light sources
and/or individual light sources.
[1400] Therein, the current can be measured for the light fixture
as a whole or for individual light sources thereof. It is also
possible to measure the current not for each light source
individually but in groups, still allowing at least a certain
localization of the failing light source. Combinations are possible
as well, for instance a measurement in groups (coarse localization)
with a subsequent measurement of the light sources within the
respective group (fine localization). For measuring the current
through the light sources individually and/or in groups, in some
embodiments/implementations a plurality of electrical current
sensors are provided.
[1401] The agricultural system, in particular a computing device
thereof, can be configured for comparing the current or
current/power consumption evaluated by the current sensor with a
target value. The target value can be fixed or in some
embodiments/implementations depend from the lighting conditions
applied, for instance be lower in case of a lower intensity and
vice versa. A deviation from the target value can indicate a
problem with the light fixture/light source. For instance, in case
of a LED light source, a bond wire lift off or other damage of the
electrical wiring can be detected as an open load.
[1402] In general, the light fixture typically comprises a
plurality of light sources, in some embodiments/implementations
light sources having different spectral properties. In some
embodiments/implementations the light sources are LEDs.
[1403] 4.sup.th aspect of "Failure Detection": The controlled
agricultural system according to any one of the 2.sup.nd or
3.sup.rd aspect of "Failure Detection", wherein the light sources
belong to a light fixture assembled from exchangeable modules, each
module comprising a plurality of light sources respectively, the
Controlled Agricultural System being configured to measure the
electrical current for each module individually.
[1404] In a preferred embodiment, the light fixture comprises at
least two exchangeable modules, each of them comprising a plurality
of light sources. When a light source fails, the respective module
can be replaced as a whole by a new module, allowing for a quick
installation and short down time. In a respective multi-module
light fixture, the current measurement can in some
embodiments/implementations be performed for each module
individually.
[1405] 5.sup.th aspect of "Failure Detection": The controlled
agricultural system according to any one of the 2.sup.nd to
4.sup.th aspect of "Failure Detection", comprising a computing
device configured for comparing at least one of the current
measured and a current consumption derived therefrom with a target
value.
[1406] 6.sup.th aspect of "Failure Detection": The controlled
agricultural system according to the 5.sup.th aspect of "Failure
Detection", wherein the target value considers an ageing effect,
namely depends from the service life of the light fixture and/or
the light source.
[1407] In a preferred embodiment, the computing device of the
agricultural system is configured for comparing the measured
current or current consumption with a current value depending on
the service life of the light fixture or light source. This means,
aging effects are considered, enabling a decision on whether a
current drift or drop results from an actual failure or lies within
the normal aging. Any target value referred to in this disclosure
can be stored in a data storage device of the agricultural system
or externally, for instance in the cloud.
[1408] 7.sup.th aspect of "Failure Detection": The controlled
agricultural system according to any one of the 1.sup.st to
6.sup.th aspect of "Failure Detection", comprising a light sensor,
the Controlled Agricultural System being configured to measure, for
the failure detection, a light intensity value of the light source
and/or the light fixture.
[1409] Alternatively or in addition to the electrical current
measurement, a light sensor can be provided for the failure
detection. A drop of the light intensity measured by the sensor can
indicate the failing light source or light fixture.
[1410] 8.sup.th aspect of "Failure Detection": The controlled
agricultural system according to the 7.sup.th aspect of "Failure
Detection", wherein the light sensor is arranged in a growth area
having growth locations for growing plants.
[1411] The light sensor or an array with a plurality of light
sensors can be arranged in the growth area, namely in the area
where the plants are grown. Assuming a top down illumination, the
light sensor can be oriented upwards to the light fixture.
Typically, a plurality of light fixtures are provided above a
growth area. In general, an external light sensor can be
advantageous as it can be oriented towards a light exit surface of
the light fixture, detecting directly the light emitted there.
[1412] 9.sup.th aspect of "Failure Detection": The controlled
agricultural system according to the 8.sup.th aspect of "Failure
Detection", wherein the light sensor is integrated into the light
fixture.
[1413] Alternatively, it is also possible to integrate the light
sensor into the light fixture. The light sensor can for instance be
oriented towards the growth area, detecting light reflected or
scattered there.
[1414] 10.sup.th aspect of "Failure Detection": The controlled
agricultural system according to the 9.sup.th aspect of "Failure
Detection", wherein the light fixture comprises a lens for guiding
light emitted by the light source to a growth location, wherein the
light sensor is optically coupled to the lens.
[1415] When the light fixture comprises a lens for guiding the
light towards the growth area, the light sensor can in some
embodiments/implementations be arranged at an edge thereof. The
lens can be a converging or convex lens for instance, focusing the
light on the growth area. Most of the light emitted by the light
sources of the light fixture will travel through the lens to the
growth field. However, some reflection can occur at the interfaces,
for instance a total internal reflection or Fresnel reflection.
[1416] 11.sup.th aspect of "Failure Detection": The controlled
agricultural system according to the 10.sup.th aspect of "Failure
Detection", wherein the light sensor is arranged at an edge of the
lens to receive a part of the light, which is guided in the lens by
total internal reflection.
[1417] By placing the light sensor at the edge of the lens, the
light reflected sideward can be used for the intensity
measurement.
[1418] 12.sup.th aspect of "Failure Detection": The controlled
agricultural system according to the any one of the 7.sup.th to
11.sup.th aspects of "Failure Detection", comprising a plurality of
light sources, a plurality of light sensors, and a computing
device, wherein the computing device is configured for locating the
light source with the reduced emission and/or total failure by
comparing light intensity values measured by the light sensors.
[1419] In a preferred embodiment, the controlled agricultural
system comprises a plurality of light sensors. Each of them can be
connected to a control unit. This can be a common one for several
sensors or individual units for each sensor.
[1420] The measured intensity values can be collected in a
computing device. In some embodiments/implementations the latter is
configured for locating the failing light source or light fixture
by comparing the intensity values measured by the different light
sensors.
[1421] This localization can be achieved by a triangulation
procedure. The position of the individual light sensors and light
sources is known by the computing device, so that the area
calculated by triangulation based on the sensor signals can easily
be matched with the position of the light source. Depending on the
distances between the light sensors and the failing light source or
fixture, the measured intensity will drop more or less. With target
values of the intensities stored (calculated or measured upfront),
a drop profile results, enabling the failure spot location.
[1422] 13.sup.th aspect of "Failure Detection": The controlled
agricultural system according to the any one of the 7.sup.th to
12.sup.th aspects of "Failure Detection", comprising a computing
device and a sunlight sensor for measuring a sunlight intensity
value, wherein the computing device is configured to evaluate the
light intensity value measured by the light sensor for the failure
detection whilst considering the sunlight intensity value.
[1423] In a preferred embodiment, the controlled agricultural
system comprises an additional sunlight sensor. Likewise, in case
of a greenhouse or glasshouse, or in case of an outdoor farm, the
sunlight intensity can be considered when the light intensities
measured for the failure detection are evaluated, as the intensity
of the sunlight can vary depending on the weather (cloudy or bright
sky) and daytime. With the sunlight sensor, this "background
intensity" can be measured, enabling a differentiation of natural
and artificial variations of the lighting.
[1424] 14.sup.th aspect of "Failure Detection": The controlled
agricultural system according to the any one of the 7.sup.th to
13.sup.th aspects of "Failure Detection", comprising a plurality of
light sources, the Controlled Agricultural System being configured
for modulating the emission of at least one light source
temporarily, namely to impose a defined pattern, wherein a
computing device of the Controlled Agricultural System is
configured to allocate the light intensity measured by the light
sensor to the at least one light source.
[1425] In a preferred embodiment, the controlled agricultural
system is configured for modulating the emission of at least one
light source temporarily. This can for instance be controlled by
the computing device connected to a control unit of the light
fixture, or light source. In general, the modulation could even be
predefined in the control unit of the light fixtures. With the
modulation, a pattern is imposed on the emission, for instance a
periodical intensity change or a switch on/off routine.
[1426] The light intensity measured shows the same modulation. By
an evaluation of this signal, for instance by a Fourier
Transformation, the pattern can be read out. The modulation/pattern
is a direct link between the light source and the measured
intensity. Accordingly, an intensity change, for instance an
intensity drop, can be assigned to the respective light
source/light fixture.
[1427] 15.sup.th aspect of "Failure Detection": The controlled
agricultural system according to the any one of the 7.sup.th to
14.sup.th aspects of "Failure Detection", comprising a plurality of
light sources, the Controlled Agricultural System being configured
to trigger a clocked emission of the light sources in a measuring
interval.
[1428] In a preferred embodiment, the controlled agricultural
system is configured for triggering, in a measuring interval, a
clocked emission of the light sources, either individually or in
groups. The light sources emit one after the other so that the
light intensity measured at different points in time can be
assigned to the different light sources. The duration of the
measuring interval can be in the range of seconds or milliseconds.
The same time scale can be of interest for the modulation mentioned
above.
[1429] 16.sup.th aspect of "Failure Detection": The controlled
agricultural system according to the any one of the 7.sup.th to
15.sup.th aspects of "Failure Detection", comprising a plurality of
light sources having different spectral properties and a plurality
of light sensors having different spectral sensitivities, a
computing device of the Controlled Agricultural System being
configured to correlate light intensity values measured in
different spectral ranges with the light sources (300,400) having
different spectral properties.
[1430] In some embodiments/implementations, a plurality of light
sensors with different spectral sensitivities can be provided. The
spectral sensors can either measure the total spectral range or
their spectral sensitivity can fit to the maxima of the emission of
the light sources used. Thus, it is possible to determine which
spectral region is affected, namely which light source type is
failing.
[1431] The element "Failure Detection" of the disclosure also
relates to a method for controlling a controlled agricultural
system, wherein a reduced emission of total failure of a light
source is detected.
[1432] 17.sup.th aspect of "Failure Detection": More specifically,
the method for agricultural management, according to any one of the
1.sup.st to 16.sup.th aspects of "Failure Detection", comprises at
least one controlled agricultural system, wherein a reduced
emission and/or total failure of a light source is detected.
Regarding further details, reference is made to the description
above.
[1433] The element "Failure Detection" is also applicable to a
group of light fixtures (luminaires) irradiating the same
agricultural space. In one embodiment, all but one light fixture
can be switched off for a predefined time window (measurement time
interval) so that the sensors measure the irradiation from the
operating light source (as described above), which is then repeated
analogously for the other fixtures. Alternatively, all fixtures can
stay in operation mode, wherein during each measuring time interval
each fixture (the light sources thereof) is individually modulated
(for example using a set of different PWM techniques) thus enabling
a simultaneous measurement of all fixtures with the same
sensors.
[1434] Further, the element "Failure Detection" also relates to a
computer program comprising program instructions, which, when
executed by a computing device, execute the aforementioned
method.
[1435] 18.sup.th aspect of "Failure Detection": Computer program
product, comprising a plurality of program instructions, which when
executed by a computing device of a Controlled Agricultural System
according to any one of the 1.sup.st to 16.sup.th aspects of
"Failure Detection", cause the Controlled Agricultural System to
execute the Method for Controlling a Controlled Agricultural System
according to the 17.sup.th aspect of "Failure Detection".
[1436] "Failure Compensation"
[1437] According to the element "Failure Compensation" of the
disclosure, a controlled agricultural system with a light fixture
is proposed that is configured to be able to compensate a failing
light source, namely a reduced emission or even total failure, at
least temporarily, until the failed light source, affected module,
or the light fixture as a whole, is replaced or repaired.
[1438] 1.sup.st aspect of "Failure Compensation": More
specifically, the controlled agricultural system comprises a
plurality of light sources for providing agricultural lighting,
wherein the controlled agricultural system is configured for
compensating a reduced emission and/or total failure of a failing
light source by an emission of another light source.
[1439] For instance, upon detection of the failing light source, an
alert message can be issued, informing operating personnel about
the failure. However, a replacement of the failing light source is
often not possible instantaneously, depending for instance on the
availability of an electrician or the accessibility of the
respective region of the farm. In terms of preventing a
contamination or the like of the plants, accessibility can be
restricted, depending for instance on the growth cycle.
[1440] In this respect, compensating a failing light source
according to the disclosure can prevent the plants from being
illuminated insufficiently at least temporarily, namely until the
light source is repaired or replaced. Even a temporary insufficient
illumination, for instance in terms of the intensity or the
spectral composition, can negatively impact the growth of the
plants.
[1441] The light sources may be configured to emit radiation in the
visible and/or the non-visible spectral range, as for example in
the far-red range and/or in the UV-B region of the electromagnetic
spectrum. It may be configured to emit monochromatic light, e.g.
green 525 nm, or narrow band radiation with a Full Width At Half
Maximum (FWHM) smaller than 50 nm, or broadband radiation with a
Full Width At Half Maximum (FWHM) greater than 100 nm. The light
sources may be an integral part of the light fixture as well as a
remote yet connected element. It may be placed in various
geometrical patterns, distance pitches and may be configured for
alternating of color or wavelength emission or intensity or beam
angle. The fixture and/or light sources may be mounted such that
they are moveable or can be inclined, rotated, tilted etc. The
fixture and/or light sources may be configured to be installed
inside a building or exterior to a building. In particular, it is
possible that the light sources or selected light sources are
mounted such or adapted to being automatically controllable, in
some embodiments/implementations remotely, in their orientation,
movement, light emission, light spectrum, sensor etc.
[1442] The light sources may be selected from the following group
or a combination thereof: light emitting diode (LED) including a
phosphor conversion LED or pc-LED using a fluorescent and/or
phosphorescence substance for conversion, laser diode (LD), laser
activated remote phosphor (LARP), Organic Light sources such as
OLED, quantum dot based light sources, solar radiation, an
incandescent lamp, a halogen lamp, a Xenon or Mercury short arc
lamp, a fluorescent lamp, a high pressure discharge lamp and a low
pressure discharge lamp.
[1443] Below, two options for realizing the compensation of the
failing light source are discussed.
[1444] 2.sup.nd aspect of "Failure Compensation": The Controlled
Agricultural System according to the 1.sup.st aspect of "Failure
Compensation", wherein the other light source is also switched on
in normal operation prior to the compensation, its emission being
increased for the compensation.
[1445] The light sources can typically be arranged array- or
matrix-like. When one of the light sources is detected as failing,
this can be compensated by an increased output of one or more
surrounding light sources. Using more than one light source for the
compensation can be preferred in general, in terms of homogeneity
and in terms of avoiding an overload of the light sources used for
the compensation.
[1446] 3.sup.rd aspect of "Failure Compensation": The Controlled
Agricultural System according to the 2.sup.nd aspect of "Failure
Compensation", wherein the light sources belong to a light fixture
comprising a plurality of light sources, the Controlled
Agricultural System being configured for choosing the other light
source for the compensation on the basis of at least one of the
criteria spatial proximity and spectral matching.
[1447] In a preferred embodiment, the light source(s) driven with a
higher emission for the compensation is/are chosen depending on the
spatial proximity and/or the spectral matching. Thus, those light
sources, which are close to the failing light source and have a
comparable or identical spectral composition or emission wavelength
are chosen to compensate the failing light source. As discussed
below, in some embodiments/implementations the respective decisions
are taken automatically, for instance by a computing device. In
particular, neuronal learning or other artificial intelligence
techniques can be applied to optimize the decision taking.
[1448] 4.sup.th aspect of "Failure Compensation": The Controlled
Agricultural System according to the 2.sup.nd or 3.sup.rd aspect of
"Failure Compensation", wherein the light sources belong to a light
fixture assembled from exchangeable modules, each module comprising
a plurality of light sources respectively, wherein the Controlled
Agricultural System is configured for choosing the other light
source within the module of the failing light source.
[1449] In a preferred embodiment, the agricultural system is
equipped with one or more light fixtures, wherein the light
fixtures are assembled from exchangeable modules respectively. Each
module comprises a plurality of light sources. Therein, the light
sources within a module can have the same spectral properties or
can have a different emission wavelength.
[1450] 5.sup.th aspect of "Failure Compensation": The Controlled
Agricultural System according to the 4.sup.th aspect of "Failure
Compensation", configured for compensating the failing light source
only within the module of the failing light source.
[1451] In some embodiments/implementations, the controlled
agricultural system is configured for choosing the light source for
compensating the failing light source within the same module.
Basically, light sources of other modules can be used in addition.
However, particularly preferred, solely the module of the failing
light source is used for the compensation, i.e. no other light
sources belonging to another module. This can be advantageous, as
the high current operation required for the compensation can reduce
the life time of the light sources which is less critical when the
module is exchanged anyway (since the failing light source has to
be exchanged by exchanging said module).
[1452] 6.sup.th aspect of "Failure Compensation": The Controlled
Agricultural System according to the 1.sup.st aspect of "Failure
Compensation", wherein the other light source is redundant, namely
is switched off prior to the compensation and switched on for the
compensation.
[1453] An alternative approach to compensate the failing light
source is to provide one or more redundant light sources. As long
as no failing light source is detected, the redundant light
source(s) is/are switched off. Providing a redundant light source
could also be combined with using normal operation light sources
for the compensation. In some embodiments/implementations, these
are alternatives, one of them being chosen for the agricultural
system.
[1454] 7.sup.th aspect of "Failure Compensation": The Controlled
Agricultural System according to the 6.sup.th aspect of "Failure
Compensation", wherein the light sources belong to a light fixture
comprising a plurality of redundant light sources switched off
during normal operation.
[1455] In a preferred embodiment, a plurality of redundant light
sources are provided in a respective light fixture. Particularly
preferred, each interchangeable module of the light fixture can be
provided with one or more redundant light sources. Regarding their
spatial alignment, a rather equal distribution of the redundant
light sources can be preferred, even so not required in general.
The redundant light sources can have different wavelengths, the
composition/mixture being adapted to the normal operation light
sources.
[1456] 8.sup.th aspect of "Failure Compensation": The Controlled
Agricultural System according to any one of the 1.sup.st to
7.sup.th aspect of "Failure Compensation", wherein the light
sources belong to a light fixture comprising a plurality of light
sources and a sensor device for sensing the reduced emission and/or
total failure of the failing light source.
[1457] In a preferred embodiment, a light fixture comprising the
light sources (normal operation and/or redundant) comprises also a
sensor device for sensing the failing light source. For instance, a
current sensor can be provided for detecting a change of the
current through the respective light source. Alternatively or in
addition, an optical or light sensor, for instance a photodiode,
can be provided for measuring the light.
[1458] 9.sup.th aspect of "Failure Compensation": The Controlled
Agricultural System according to any one of the 1.sup.st to
8.sup.th aspect of "Failure Compensation", comprising an actuator
device for adjusting the emission of the light source and a
computing device coupled with the actuator device and configured to
cause the actuator device to compensate the failing light source by
the emission of the other light source.
[1459] In a preferred embodiment, the controlled agricultural
system comprises an actuator device for adjusting the emission of
the light source, for instance a drive unit adjusting the current
through the light source. The actuator device can be integrated
into the light fixture or provided externally. Further, the
agricultural system comprises a computing device which is coupled
to the actuator device. The coupling of individual components, for
instance the actuator device and the computing device, can be
achieved wire-based or wireless, any known interface can be used
(WLAN, LAN or Bluetooth for instance). The computing device is
configured to cause the actuator device to compensate the failing
light source as described above. Since the failing light source is
known, the computing device can decide which light source (spectral
properties/position) has to be driven with the appropriate
intensity to achieve the compensation.
[1460] 10.sup.th aspect of "Failure Compensation": The Controlled
Agricultural System according to the 9.sup.th aspect of "Failure
Compensation", comprising a data storage device or being linked to
a data storage device linked to the computing device, a data set
being stored in the data storage device, wherein the data set
comprises data on ageing properties of the light sources, the
computing device being configured for assessing the failing light
source based on the ageing properties.
[1461] In some embodiments/implementations, the controlled
agricultural system comprises a data storage device linked to the
computing device. Therein, a data set is stored in the data storage
device, which comprises data on the ageing properties of the light
source(s). With such data, the decision about which light source
has to be considered as the failing one could even be taken without
any measurement at all. The system knows upfront the time of life
and when a compensation becomes necessary because the emission
decreases. However, in some embodiments/implementations, the ageing
data is used in combination with the sensor detection, increasing
the overall reliability of the decision taking.
[1462] 11.sup.th aspect of "Failure Compensation": A Method for
Controlling an Agricultural System, comprising a plurality of light
sources, wherein a reduced emission and/or total failure of a
failing light source is compensated by an emission of another light
source.
[1463] Furthermore, reference is made to the description above, the
features described there shall also be disclosed in terms of the
method.
[1464] 12.sup.th aspect of "Failure Compensation": The Method for
Controlling an Agricultural System according to the 11.sup.th
aspect of "Failure Compensation", for controlling a Controlled
Agricultural System according to any one of the 1.sup.st to
10.sup.th aspect of "Failure Compensation".
[1465] 13.sup.th aspect of "Failure Compensation": Computer program
product, comprising a plurality of program instructions, which when
executed by a computing device of a Controlled Agricultural System
according to any one of the 1.sup.st to 10.sup.th aspect of
"Failure Compensation", cause the Controlled Agricultural System to
execute the Method for Controlling an Agricultural System according
to the 11.sup.th or 12.sup.th aspect of "Failure Compensation".
[1466] "Heat Reflector"
[1467] According to the element "Heat Reflector" of the disclosure,
a horticultural apparatus is proposed, particularly for use in a
controlled agricultural system, particularly for breeding, growing,
cultivating and harvesting in an agricultural facility,
particularly a plant growing facility and/or an aquaponics
facility, which comprises an agricultural light fixture and a heat
reflector that is able to direct or redirect the heat generated by
the agricultural light fixture to the plants.
[1468] 1.sup.st aspect of "Heat Reflector": More specifically, the
horticultural apparatus, particularly for use in a Controlled
Agricultural System, comprises an agricultural light fixture,
comprising at least one light module, configured for illuminating
plants arranged on a cultivated area below the agricultural light
fixture, a heat reflector arranged above the agricultural light
fixture and configured to be able to reflect heat, emanating
upwards from the agricultural light fixture, downwards to the
plants.
[1469] Cooling of the LEDs is mainly done by heat conduction
(through heat spreaders) and heat convection (through the air).
During operation, due to cooling effects, the air above an
agricultural light fixture comprising LED is hotter than the air
below the agricultural light fixture. To heat the plants, however,
more heat underneath the agricultural light fixture is needed. This
can be achieved by installing a (heat) reflector above and/or
attached to the agricultural light fixture. The reflector traps the
heat (hot air) below. Furthermore, the reflector may comprise an
infrared-reflecting surface, e.g. based on gold-, silver- or a
dielectric coating, which reflects radiation, in some
embodiments/implementations in the infrared range. Other coating
ad/or heat reflective materials are for example, birefringent
dielectric multilayer films and two-component infrared reflecting
films comprising alternating layers of first and second diverse
polymeric materials, Consequently, such a reflector reflects
infrared radiation down to the plants, thus heating the plants and
improving their growth, while recovering the heat energy which
would have been lost otherwise.
[1470] 2.sup.nd aspect of "Heat Reflector": The horticultural
apparatus according to the 1.sup.st aspect of "Heat Reflector",
comprising at least one ventilator configured to be able to direct
the heat from the agricultural light fixture towards the heat
reflector by means of forced convection.
[1471] The air convection from the agricultural light fixture to
the reflector and thus the transportation of heat can be improved
by arranging ventilators on the top face of the agricultural light
fixture, which cool the LEDs by creating an airflow that directs
the air towards the reflectors.
[1472] 3.sup.rd aspect of "Heat Reflector": The horticultural
apparatus according to the 1.sup.st or 2.sup.nd aspect of "Heat
Reflector", wherein the heat reflector comprises a plane arranged
parallel to the top side of the agricultural light fixture.
[1473] In first basic embodiment, the reflector comprises a plane
made e.g. of metal, plastics or glass, which is attached or mounted
above the agricultural light fixture, in some
embodiments/implementations aligned parallel to the agricultural
light fixture. In some embodiments/implementations, the surface
area covered by the reflector is at least as large as the surface
area covered by the agricultural light fixture.
[1474] 4.sup.th aspect of "Heat Reflector": The horticultural
apparatus according to the 1.sup.st or 2.sup.nd aspect of "Heat
Reflector", wherein the heat reflector is shaped such that the heat
emanating from the top side of the agricultural light fixture is
first reflected sideways and then downwards, i.e. around the
agricultural light fixture towards the plants.
[1475] In another embodiment, the reflector is shaped to be able to
reflect the heat around the agricultural light fixture. For
instance, an appropriate form of the reflector first reflects the
heat sideways and then downwards (see for instance FIG. 2).
[1476] 5.sup.th aspect of "Heat Reflector": The horticultural
apparatus according to any one of the 1.sup.st to 4.sup.th aspects
of "Heat Reflector", wherein the heat reflector comprises two or
more movable parts that constitute the reflecting surface.
[1477] Furthermore, the reflector may also be partitioned in two or
more separate parts that can be (automatically or by temperature
sensor feedback control loop) moved apart (split) thus creating
openings for carrying some of the heat away by means of upwards
airflow while reducing the heat radiation downwards, and vice
versa.
[1478] 6.sup.th aspect of "Heat Reflector": The horticultural
apparatus according to the 5.sup.th aspects of "Heat Reflector",
wherein the two or more parts that constitute the reflecting
surface are configured to be able to move apart thereby forming
between the two parts an aperture where heat can escape, enabling
to control the amount of heat reflected towards the plants.
[1479] 7.sup.th aspect of "Heat Reflector": The horticultural
apparatus according to the 5.sup.th or 6.sup.th aspects of "Heat
Reflector", wherein at least one movable parts is configured to be
able to adjust the direction of the reflected heat.
[1480] Furthermore, the orientation or inclination of the
ventilators and/or the reflectors and/or parts of the reflectors
may be adjustable, so that the heat can be directed in certain
directions, e.g. to increase the heat in certain areas depending on
the applied growth recipe.
[1481] 8.sup.th aspect of "Heat Reflector": The horticultural
apparatus according to any one of the 1.sup.st to 7.sup.th aspects
of "Heat Reflector", comprising at least one supplemental heat
source.
[1482] Furthermore, a supplemental heat source may be added to the
agricultural light fixture to enhance the heating if necessary.
[1483] It should also be noted that a heat reflector can contain
heat absorbing and heat storing materials (like phase transition
materials) and thus release thermal energy even after the light
sources were switched off.
[1484] It should also be noted that a heat reflector that is for
example correlated with a specific fixture, can be connected to
another heat reflector of a second lighting fixture thus allowing
transfer of heat across two or multiple heat reflectors.
[1485] Furthermore, a solar panel or photovoltaic cells may be
attached to the upper side of the reflector. Together with the
reflector, the solar panel or the photovoltaic cells can help to
shade the agricultural light fixture against heat from the sun in a
greenhouse and at the same time generate additional energy to
supply e.g. the agricultural light fixture or, as the case may be,
sensors or ventilators.
[1486] 9.sup.th aspect of "Heat Reflector": A Controlled
Agricultural System, comprising at least one horticultural
apparatus according to one of the 1.sup.st to 8.sup.th aspect, a
computing device, configured to be able to control the
horticultural apparatus according to a growth recipe.
[1487] More specifically, the controlled agricultural system is
configured to be able to adjust the heat reflector, e.g. its
position, alignment, shape, according to a growth recipe. The
growth recipe comprises a light recipe, and it may also comprise
temperature values appropriately correlated to the light
recipe.
[1488] 10.sup.th aspect of "Heat Reflector": The Controlled
Agricultural System according to the 9.sup.th aspect of "Heat
Reflector", wherein the growth recipe comprises a light recipe and
correlated temperature values, measured for example at plant
level.
[1489] It should be noted that temperature sensors can be attached
to the reflective planes or be integrated into them, thus allowing
measurement of the local reflector temperatures in real time. The
horticultural light fixture and/or the heat reflector may be
controlled such that the illumination and the temperature at the
plants match with the growth recipe.
[1490] 11.sup.th aspect of "Heat Reflector": The Controlled
Agricultural System according to the 9.sup.th or 10.sup.th aspect
of "Heat Reflector", comprising an actuator device configured to be
able to control the position/alignment and/or the shape of the heat
reflector.
[1491] Furthermore, as the case may be, ventilators and/or
supplemental heat sources, arranged at the agricultural light
fixture, may also be controlled by the computing device via the
actuator device and/or any other suitable control unit.
[1492] 12.sup.th aspect of "Heat Reflector": The Controlled
Agricultural System according to any one of the 9.sup.th to
11.sup.th aspect of "Heat Reflector", comprising a data storage
device for storing the growth recipe and/or control data for
controlling the ventilator and/or control data for controlling the
heat reflector.
[1493] The data storage device may comprise a database in which
growth settings, including light recipes and correlated temperature
values, for example measured at plant level, for various plants
species are stored.
[1494] Furthermore, the computing device is configured to control
the actuator device, including the heat reflector, and the
agricultural light fixture, including--as the case may
be--ventilators and/or supplemental heat sources arranged at the
agricultural light fixture, according to the growth recipe stored
on the data storage device.
[1495] The element "Heat Reflector" of the disclosure also relates
to a method for agricultural management, particularly for breeding,
growing, cultivating and harvesting in an agricultural facility,
particularly a plant growing facility and/or an aquaponics
facility, which enables to redirect the waste heat of the light
fixture to the plants.
[1496] 13.sup.th aspect of "Heat Reflector": A method for
agricultural management, comprising the steps of arranging an
agricultural light fixture above plants arranged on a cultivated
area, illuminating the plants with the agricultural light fixture,
arranging a heat reflector above the agricultural light fixture
such that heat, emanating upwards from the agricultural light
fixture, is reflected downwards to the plants.
[1497] 14.sup.th aspect of "Heat Reflector": The method for
agricultural management according to the 13.sup.th aspect of "Heat
Reflector", further comprising the step of configuring the heat
reflector such that heat, emanating upwards from the agricultural
light fixture, is first reflected sideways and then downwards, i.e.
around the agricultural light fixture towards the plants.
[1498] Accordingly, the heat generated by the light sources of the
light fixture, particularly LEDs, can be used to increase the
temperature of the plants, thus improving the plant growth and
recovering the heat energy.
[1499] 15.sup.th aspect of "Heat Reflector": The method for
agricultural management according to the 13.sup.th or 14.sup.th
aspect of "Heat Reflector", for controlling a Controlled
Agricultural System according to any one of the 9.sup.th to
12.sup.th aspect of "Heat Reflector".
[1500] The measures described above according to "Heat Reflector"
allow establishing, maintaining and adjusting a specific
microclimate around plants or even a single plant.
[1501] 16.sup.th aspect of "Heat Reflector": A computer program
product, comprising a plurality of program instructions, which when
executed by a computer system of an Controlled Agricultural System
according to any one of the 9.sup.th to 12.sup.th aspect of "Heat
Reflector", cause the Controlled Agricultural System to execute the
Method for Agricultural Management according to any one of the
13.sup.th to 15.sup.th aspect of "Heat Reflector".
[1502] After detecting a malfunction of a luminaire according to
"Failure Detection", failing light sources can be compensated
according to "Failure Compensation". Such detecting and
compensating can be applied to luminaires, for instance, of the
kind described in "Reflector heat" or "Light Guides".
[1503] The aspects of "Optical Arrangements" may be combined with
various aspects of "Light Guides" for further enhancing the
efficiency of irradiation to a plant bed. The measures proposed in
"Light Guides" and "Optical Arrangements" can further be enhance
with various aspects of "Extended Light Recipes".
[1504] UV-light can be used to destroy insects (see group "Plant
Health & Growth" of the disclosure). Other wavelengths in the
visible range or near infrared range can be used to provide photons
to the plant to trigger specific hormone production, or other plant
reactions, which are related to specific wavelengths. "Heat
Reflector" describes an add-on to a luminaire, which can influences
the plant growth (see group "Light/Growth Recipes" of the
disclosure).
[1505] Smart Grid
[1506] According to the element "Smart Grid" of the disclosure, a
controlled agricultural system with a connection to a smart grid is
proposed. Furthermore, the agricultural system is configured to
withdraw more current during times of a great electricity supply
(i.e. low price) and withdraw less current in times of a lower
supply (i.e. high price), by dynamically adjusting the light
recipes for the plants.
[1507] The system uses growth recipes (see e.g. "Customized
Requirements"). A growth recipe consists of values for light recipe
(spectrum, intensity, photoperiod), CO2, temperature, humidity,
nutrients, EC, pH, H2O, etc.
[1508] The growth recipe has an optimum value and value ranges for
good, sufficient and short-term tolerable. Optimum values are
self-explaining. Good values are high efficient values which lead
to good economics, sufficient values keep the plants growing but
slow and/or in not good quality and/or quantity, short-term
tolerable values are values where the plant could live/grow for a
short-term (e.g. 5 min.) but thereafter would die or have
diseases.
[1509] To reduce/increase energy consumption, actuators could be
orchestrated according to these values, but also production
preparation activities (e.g. seeding) and post-production
activities (e.g. cleaning of trays) could be shifted. Actuators
could be water pumps, HVAC systems, lighting system, internal
transportation/logistics, harvesting robots, production systems
like seeding machines.
[1510] Different optical and ambient sensors are tracking all
relevant data and a computer unit onsite or in the cloud is
analyzing the data, e.g. due to the sensor data available from a
substrate moisture sensor, it can be calculated how long the
irrigation pumps can be shut down. Also with the data from
optical/image plant sensors it can be detected if stress in the
plant occurs and reduce cooling, irrigation etc., within the
tolerance level of the plant.
[1511] In case of light treatments/adjustments, light might be
switched off (or only the energy intensive part of the spectrum
could be switched off or reduced), depending on the plants. For
some plants, the light intensity can be reduced to the compensation
point. The (light) compensation point is the light intensity on the
light curve where the rate of photosynthesis exactly matches the
rate of cellular respiration. At this point, the uptake of CO.sub.2
through photosynthetic pathways is equal to the respiratory release
of carbon dioxide, and the uptake of O.sub.2 by respiration is
equal to the photosynthetic release of oxygen. Keeping the
illumination above the compensation point prevents the plant from
losing energy.
[1512] However, when doing this, the reaction of the plant to high
or low illumination has to be taken into account. There are long
day and short day plants whose activities depend on the length of
the day. Example Cannabis: This is a short day plant; if the
critical day length will be shorter than .about.14 hours (depending
on variety) they will initiate flower; this would be bad if the
branching of the plants were not complete and it would result in a
lower biomass/flower production.
[1513] 1.sup.st aspect of "Smart Grid": More specifically, a
controlled agricultural system with a connection to a smart grid,
comprises an acquisition unit for acquiring data from the smart
grid, a computing device connected to the acquisition unit and
configured to calculate a dynamic light recipe for a plant to be
illuminated using the data from the smart grid, a control unit
connected to the computing device, a light fixture connected to the
control unit and configured to convert the dynamic light recipe
into control signals for the light fixture and thereby produce a
light intensity curve and/or a spectrum curve of the light
fixture.
[1514] The smart grid provides information about energy costs, and
so energy-intensive apparatuses can be operated at times when the
prices are low (or is even offered credit if electricity is taken
from the grid) because the demand is low or the supply is high
(such as on very windy days, for example).
[1515] The agriculture system is calculating and showing the grower
the cost estimation and revenue potential per project based on the
utility company data, especially in case of grid stress. Based on
that the agriculture system develops the best possible cost-revenue
production planning and gives recommendations to the grower if it
is economically reasonable if extra energy should be taken and for
how long.
[1516] In addition, the status of the production has to be taken
into account (provided e.g. by real-time sensor data) to see if any
deviations from the production plan due to higher or lower
availability of energy is acceptable.
[1517] The grower, of course, can define projects as mandatory so
that they are executed as planned in any case. These settings are
considered in the remaining production planning.
[1518] A step-by-step approach to supply more power to the system
over time could make sense for user acceptance. Therefore, at the
beginning the system is just giving notifications/recommendations
regarding flexing of the smart grid. Later on the system decides
and implements the growth conditions totally independent.
[1519] In case of grid stress, the amount of electricity to be
taken from the grid, prices and duration for how long the
electricity should be taken will be provided (the system generally
provides the price level and the electricity availability).
[1520] To take into consideration the availability of (cheap)
energy for production planning, the controlled agricultural system
may comprise an API to a weather forecast system and an API to the
utility company is beneficial to get real-time data and to perform
the smart grid approach. The system can also contain an API to a
growth recipe input providers.
[1521] With the help of price information items from the past and
weather forecasts, it is possible to identify when the electricity
price will be low or negative.
[1522] Furthermore, it is also possible to use time-zone effects,
e.g. the import of electricity from EU or other countries that are
already in the "night phase"--or are currently consuming less
energy.
[1523] Therefore, the controlled agricultural system according to
"Smart Grid" serves to balance the electricity consumption in a
smart grid ("grid balancing").
[1524] 2.sup.st aspect of "Smart Grid": The controlled agricultural
system according to the 1.sup.st aspect, comprising an energy
storage configured to be able to receive electrical energy in the
case of an electricity surplus and/or in the case of a cheap
electricity rate in the smart grid.
[1525] 3.sup.nd aspect of "Smart Grid": The controlled agricultural
system according to the 1.sup.st or 2.sup.nd aspect, comprising an
energy storage configured to be able to output electrical energy in
the case of an electricity deficit and/or in the case of an
expensive electricity rate in the smart grid.
[1526] In a preferred embodiment, the vertical farm can have local
energy storages in order to capture brief times of surplus or
deficit. Consequently, the vertical farm can serve as a battery in
the smart grid. Furthermore, energy can be stored in the local
energy storages when prices for electrical energy are low and used
for operating the controlled agricultural system when prices for
electrical energy are high.
[1527] The acquisition unit is configured to be able to acquire,
e.g. via the Internet or other databases, store and evaluate the
energy costs (in some embodiments/implementations electricity in
this case).
[1528] Furthermore, according to "Smart Grid", a method for
agriculture/agricultural management is proposed that balances the
electricity consumption of the controlled agricultural system
according to the supply from a smart grid power supply.
[1529] 4.sup.th aspect of "Smart Grid": A method for agriculture,
comprising a controlled agricultural system according to any one of
the 1.sup.st to 3.sup.rd aspect of "Smart Grid" and the following
method steps: acquiring data, in particular the electricity price,
from the smart grid by the acquisition unit, calculating a dynamic
light recipe for a plant to be illuminated by means of the
computing unit, taking account of the data, in particular the
electricity price and/or the available amount of electricity, from
the smart grid, actuating the light fixture by the control unit,
which converts the dynamic light recipe from the computing device
into corresponding control signals for the light fixture, as a
result of which a light intensity or light intensity curve is
produced by the light fixture.
[1530] 5.sup.th aspect of "Smart Grid": The method for agriculture
according to the 4.sup.th aspect of "Smart Grid", comprising the
step of predicting the curve of the electricity price by means of
the computing device based on the data from the smart grid.
[1531] 6.sup.th aspect of "Smart Grid": The method for agriculture
according to the 5.sup.th aspect of "Smart Grid", comprising the
step of taking account of the predicted curve of the electricity
price when calculating the dynamic light recipe by means of the
computing device.
[1532] The controlled agricultural system moreover comprises a
computing device, which is configured to be able to predict the
curve of the electricity price with the aid of the smart grid when
using the acquisition unit, for example using historical data of
the electricity curve depending on parameters such as time or
weather.
[1533] The computing device is configured to render the light
recipes dynamic. By way of example, the DLI is known on account of
the available, static light recipes. The dark times of the plants
and, possibly, other parameters are likewise known. The computing
device now knows the target spectrum over time, i.e., the energy
consumption over time. It has available a prediction of the energy
availability and, using this, it is able to calculate what energy,
i.e., light intensity, can be made available at what time. The
computing device now optimizes (minimizes) the costs for the energy
supply, with it being ensured that boundary parameters such as the
entire photon flux per day required by the plants is reached but
also that dark times (i.e. rest periods of the plants) are
observed.
[1534] These information items are then transmitted to the control
units (light control units) of the light fixtures (agricultural
light fixtures), said control units actuating the light fixtures
according to this profile. Depending on the electricity price, the
profile substantially changes in terms of the overall intensity
and/or the actuation of the individual light colors or spectral
regions. Initially, the relative intensity of the individual
wavelength regions with respect to one another remains unchanged.
However, it is also conceivable for the spectrum itself to change
as a consequence of rendering the spectrum dynamic.
[1535] By way of example, it is conceivable that the spectrum is
restricted in a targeted manner to those LEDs that produce
electricity efficiently such that the daylight sum can be obtained
with low costs (e.g., the light fixture can actuate only blue LEDs
and deactivate other colors that operate less efficiently since the
light is converted therein, or only operate said other colors in
dimmed fashion).
[1536] Moreover, it is possible to undertake a change between
different light sources and/or change a mode of operation of
different light sources by means of the control unit that is
connectable to a smart grid. By way of example, in the case of a
mixed illumination, there can be a change from a predominant
illumination with conventional halogen or discharge lamps to a
predominant illumination using light-emitting diodes, and vice
versa.
[1537] 7.sup.th aspect of "Smart Grid": The method for agriculture
according to any one of the 4.sup.th to 6.sup.th aspect of "Smart
Grid", comprising the step of absorbing a brief electricity surplus
by way of correspondingly increasing the light intensity of the
light fixture (grid balancing) and/or charging the energy
storage.
[1538] A brief surplus may also be taken up by a vertical farm
according to the disclosure. Here, the light fixtures are operated
with a higher intensity than what is provided for by the light
recipe. The control unit has available the maximum illumination
that a plant can accept without stress. In a first step, the
illumination intensity (and hence the electricity consumption) is
increased to this value.
[1539] However, it is also possible to briefly increase the
intensity of the illumination above this threshold if a very large
current supply is present and the grid power supply has to be
relieved quickly (in order to take the "pressure" out of the power
supply grid in real time; i.e., it is possible to also control the
light fixtures in real time). Plants can withstand illumination
that is too strong for a certain amount of time. In some
embodiments/implementations, the stress on the plants is checked
using a sensor for stress detection such that these are not
stressed too strongly. A sensor for stress detection can be a
fluorescence sensor, which measures the efficiency of the
photosystem, or a cuvette for measuring gas exchange (CO.sub.2
fixation in the plant), with the cuvette being attached at
representative positions.
[1540] The sensors may provide data about the maximum capacity of
the photosystem for the plants. Then the system can make decisions
about how much electricity it can use for the lights (intensity or
spectrum) without damaging the photosystem.
[1541] By measuring the activity of the photosynthesis and creating
a light curve with regard to factors like temperature, and carbon
dioxide level, the light level can slowly be increase up to the
point where it is most comfortable to the plants. (Note: plants can
adapt over time to higher light intensities) so a few days later
maybe the comfortable zone could be higher or lower, depending on
past illumination levels.
[1542] One way to prioritize certain products, is to implement
current market prices for the crops. If possible, local prices
would be the best
[1543] Since a vertical farm may also house different types of
plants, the computing device can in some
embodiments/implementations apply the brief stronger irradiation to
those plants that are less susceptible to elevated illumination
intensities.
[1544] Moreover, the computer device has access to information
about what products are grown in the coming days and what light
recipes are required to this end. The light recipes are associated
with time-resolved energy consumption. In a conventional grid power
supply, the light recipes would simply be run through.
[1545] Typical behaviors of the computing device appear to be: the
plants are illuminated with a lower photon flux and/or a different
spectrum in the case of high energy costs. In exchange, a higher
photon flux and/or a different spectrum can be made available at
times with lower energy costs.
[1546] Vertical farms may also be operated predominantly at night,
with the adaptations or control mechanisms described above also
being carried out here on account of electricity price
variations.
[1547] The computing device checks the actual costs and predicted
costs of the illumination profile at regular intervals. A new
optimization of the illumination profile is undertaken if the
deviation exceeds a set threshold.
[1548] 8.sup.th aspect of "Smart Grid": The method for agriculture
according to the 7.sup.th aspect of "Smart Grid", comprising the
steps of recalculating the planned light intensity curve after the
end of the brief electricity surplus and taking account of the
previously increased light intensity profile on account of the grid
balancing.
[1549] These brief phases of excess irradiation are then taken in
account by the computing device when calculating the dynamic light
recipes; i.e., phases of excess irradiation are compensated by
phases of lower irradiation or by a reduction in the irradiation
time or by a change in the irradiation spectrum. The term "dynamic"
can thus relate both to a time-varying irradiation intensity (e.g.,
photon flux) and to a time-varying irradiation spectrum of the
respective light recipe. Thus, irradiation components of spectral
regions, for example blue to dark-red, can be changed over time and
can be adapted to the selected energy options. The timescales for
change or adaptation may be implemented in a second, minute, hour
or day clock or longer, depending on how the energy supply or the
energy costs change.
[1550] However, unlimited amounts of energy are not available at
all times in a smart grid if limits are placed on the costs or if
the intention is to profit from times of particularly low or
negative prices. According to the disclosure, the light recipes are
not simply left statically but the light recipes are made dynamic;
i.e., the light recipe, in particular the intensity of the emitted
light, is modified depending on the availability of the energy.
[1551] As a result of rendering the light recipes dynamic, an
optimal use of cost-effective electricity for the operation of the
plant light fixtures is possible. Moreover, the controlled
agricultural system is configured to also act as an energy storage
for the smart grid (grid balancing). To this end, provision is made
of adapting the dynamic light recipes to brief electricity
surpluses or deficits or to low or high electricity costs and/or of
charging or discharging an energy storage.
[1552] When the farm has decided how much energy it could consume,
it feedbacks the information back to the grid which can either
accept or reject the offer (rejection e.g. in case surplus needs to
be taken). The API may include a user identification, so that the
power supplier directly knows who is making the offer and/or whom
it is talking to.
[1553] When the modified power supply is applied, the effect on the
plants is checked regularly with regards to thresholds prescribed
by margins of the growth recipe i.e. to see if not too much stress
in introduced on the plant. Light sensor is an example of a sensor,
which could be used for verification, but also pH- and/or
EC-sensors could be used to monitor water content if circulation is
increased, or visual sensors for stress detection if only the
spectrum rather than switching off the light are manipulated.
[1554] For the time being, it appears that the "smart grid" only
provides tariffs, in the form of: [1555] Time-based (time during
the day, day during the week, season); [1556] Location-dependent
(city/rural, degrees of separation or distance from core
distribution network); [1557] Tier-bound (min/max energy demand of
the customer); [1558] Charge type (fixed price, consumption-based,
demand-based, etc.).
[1559] Therefore at the moment the smart grid can only react to the
price conditions provided by the energy supplier without providing
an active response--e.g. given the demand of particular crops in
coming times and their associated growth recipes, the software can
only figure out an optimal match to the available tariffs, i.e.
plan the optimal growth settings.
[1560] An alternative to planning and reactive operation would be
to buffer the energy in power banks at the time when prices are low
and using that reserve when the prices are high. This could
especially be used to store energy when the prices are negative.
The stored electricity could then simply be sold in times of
positive prices.
[1561] In conclusion, according to the disclosure, the control, as
explained above, of the controlled agricultural system in a smart
grid not only obtains economical advantages by an optimal use of
more cost-effective current, instead the controlled agricultural
system also acts as an energy buffer in a smart grid (grid
balancing). These aspects are assisted as a result of rendering the
light recipes dynamic.
[1562] Naturally, a controlled agricultural system connected to a
smart grid power supply (smart grid) can also store energy, for
example in batteries, flywheel energy storages and the like, and
then can either use the stored energy itself at a later time or,
for example, supply its stored energy to another agricultural
system, controlled thus, that is connected to a smart grid power
supply (smart grid) (exchange of energy between controlled
agricultural systems).
[1563] In a further refinement of "Smart Grid" the light recipes
may be adjusted according to the various elements of the group
"Light/Growth Recipes" in order to reduce overall energy cost.
Alternatively or additionally, the temperature in the horticultural
facility may be optimized as well according to "Temperature
Dependent Illumination" and/or "Temperature Control" in order to
maximize energy savings.
[1564] Furthermore, adjustments of suitable parameters can be
conducted by the controlled agricultural system in order to
compensate negative effects that may result when the system reduces
the energy consumption because of high prices for electrical
energy. Specifically, when the control unit of the system adjusts
the parameters such that energy consumption is reduced, the growing
conditions for plants may not be optimal or even adverse. For
instance, too low temperatures may decelerate the growth of plants.
Therefore, the light recipes may be adjusted to compensate the
effect of low temperatures according to "Temperature Dependent
Illumination" and "Temperature Control". Further parameters, such
as humidity, CO.sub.2-concentration, etc. that influence the growth
of plants may be adjusted as well.
[1565] Customer Interaction
[1566] "Customer Requirements"
[1567] According to the element "Customer Requirements" of the
disclosure, a controlled agricultural system comprises actuators
that influence the plant health and growth based on the target
product defined by the customer.
[1568] "Customer Requirements" allows the customer not only to
order the type and amount of a plant or product but also to set
certain characteristics of the plant. The characteristics may
include (not exhaustive): color, content (e.g. vitamins, THC and
other cannabinoids, etc.), the morphology (i.e. form of the plant),
degree of maturity, etc.
[1569] By way of example, the term plants should include the
following products in this case: wheat, grapes, berries, algae,
fungi, flowers, crops and the like, but also fish (aquaponics).
[1570] Below, various aspects and details of "Customer
Requirements" are described.
[1571] 1.sup.st aspect of "Customer Requirements": A controlled
agricultural system for customized plant growth, comprising an
acquisition unit for acquiring the definition of the target product
by the customer, actuators configured to be able to act on the
plant (target product) or plant growth, a control unit connected to
the actuators, a computing device connected to the acquisition unit
and the control unit and configured to be able to establish control
parameters for the actuators from the definition of the target
product.
[1572] It has been established that plants react to light
(including ultraviolet and infrared) and other environmental
parameters. Thus, the chlorophyll portion of broccoli can be
increased if it is irradiated by UV light prior to harvest, just
like the proportion of glucosinolates (cardiac or mustard oil
glycoside). Other wavelengths excite the height growth of the plant
or ensure a more compact form (morphology) or stimulate the
production of certain ingredients (active ingredients, enzymes,
etc.).
[1573] Thus, a customer may select his/her product or product
properties, such as content (e.g., vitamin C content), plant form,
quality of the plants or fruits (such as firmness to bite), color,
etc., from a multidimensional parameter set or a correspondingly
displayed graphical representation. The selection options for the
customer may also be divided in predefined quality categories or
quality certificates, simplifying a selection and order
process.
[1574] For this purpose, the controlled agricultural system may
comprise a communications device with the customer, for example, a
Graphical User Interface (GUI), which provides a selection menu for
selecting a product order variant. The GUI may also make available
to a customer an augmented or virtual reality representation of the
desired result.
[1575] Furthermore, the controlled agricultural system may comprise
a computing device with storage, data processing and data analysis
equipment, a database, software or a computer program, API
interfaces.
[1576] 2.sup.nd aspect of "Customer Requirements": The controlled
agricultural system according to the 1.sup.st aspect of "Customer
Requirements", comprising sensors connected to the control unit and
configured to check the plant growth or the plant health (actual
values), wherein the computing device is configured to establish
adapted control parameters for the actuators in the case of an
unscheduled deviation of the sensor data (actual values) from an
expected profile of the plant growth for the target product
(intended values).
[1577] The (grown) products may be subject to constant quality
monitoring. To this end, the controlled agricultural system may
also comprise corresponding sensors, for example, electric,
thermal, magnetic, spectroscopic, cameras, etc.
[1578] 3.sup.rd aspect of "Customer Requirements": The controlled
agricultural system according to the 1.sup.st or 2.sup.nd aspect of
"Customer Requirements", wherein the actuators comprise a
horticultural light fixture.
[1579] 4.sup.th aspect of "Customer Requirements": The controlled
agricultural system according to any one of the 1.sup.st to
3.sup.rd aspect of "Customer Requirements", wherein the sensors
comprise a camera.
[1580] The controlled agricultural system converts this customer
requirement into a suitable growth recipe (in fully or partly
automated fashion), which may actually be a light recipe. The light
recipe can be provided by an appropriately embodied plant
illumination unit (horticultural light fixture). In some
embodiments/implementations, light-emitting diodes are used as
light sources for the illumination unit.
[1581] A light recipe means a temporal change in the spectrum
(i.e., temporal light phases), to be precise in relation to, inter
alia, spectrum (spectral distribution), intensity (photon flux,
photobiologically active radiation), incoming radiation direction,
dark times, pulsed operation, shock treatment with UV light, etc.
Thus, the light recipe for the germination phase may have a
spectrum with a certain embodiment, said spectrum may have a
further embodiment for the growth phase and a third embodiment for
the maturing phase. The duration of the temporal phases and further
growing conditions can be set in a light recipe (on the basis of
empirical values or predictions, for example).
[1582] However, in addition to a light recipe, a growth recipe may
also comprise further parameters, such as the temperature, the
CO.sub.2 content, the humidity, the watering or the use of
fertilizers and pesticides, for example.
[1583] 5.sup.th aspect of "Customer Requirements": The controlled
agricultural system according to the 3.sup.rd and 4.sup.th aspect
of "Customer Requirements", wherein the control parameters comprise
the control signals of a light recipe, by means of which the plant
light fixture is actuated.
[1584] The growth recipes are now used to appropriately operate the
light fixtures over the planted fields (light recipe, position,
form, location) such that the characteristics of the plants desired
by the customer are produced. Additionally, as already described
above, nutrients and other parameters may also be adapted
appropriately.
[1585] In the case of deviations in the growth or maturing
parameters or in the case of the identification of diseases or
pests, the light recipe (spectrum, intensity, time duration) and,
optionally, further influencing variables (fertilizer, watering,
pest control, etc.) are modified.
[1586] By way of example, the irradiation duration and growth state
can be actively monitored using a sensor system. Thus, the end of
the germination phase may be defined by virtue of the plants (or
some of the plants in a bed) having reached a certain height or
having formed a certain number of leaves or a certain leaf
density.
[1587] 6.sup.th aspect of "Customer Requirements": A method for
agriculture, comprising a controlled agricultural system according
to any one of the 1.sup.st to 5.sup.th aspect of "Customer
Requirements" and the following method steps: acquiring the
definition of the target product by the customer with the aid of
the acquisition unit, calculating the control parameters for the
actuators by the computing device on the basis of the definition of
the target product, actuating the actuators with the control
parameters by the control unit.
[1588] 7.sup.th aspect of "Customer Requirements": The method for
agriculture according to the 6.sup.th aspect of "Customer
Requirements", further comprising the steps of checking the plant
growth or the plant health (actual values) on the basis of the
sensor data by way of the computing device, adapting the control
parameters by way of the computing device if the check (actual
values) shows unscheduled deviations in relation to an expected
profile of the plant growth for the target product (intended
values).
[1589] Control parameters for actuators that influence the plant
growth or the plant health are established based on the definition
of the target product by the customer. In some
embodiments/implementations, the plant growth or the plant health
is monitored by means of a sensor system (actual values). The
control parameters are suitably adapted in the case of unscheduled
deviations in relation to an expected profile of the plant growth
for the target product (intended values).
[1590] 8.sup.th aspect of "Customer Requirements": The method for
agriculture according to the 6.sup.th or 7.sup.th aspect of
"Customer Requirements", comprising the step of predicting the
profile of the plant growth (intended values) on the basis of the
definition of the target product and the control parameters
suitable to this end, e.g., the light recipe, by way of the
computing device.
[1591] 9.sup.th aspect of "Customer Requirements": The method for
agriculture according to any one of the 6.sup.th to 8.sup.th aspect
of "Customer Requirements", comprising a database in which the
optimal profile of the plant growth of the target product (intended
values) is stored.
[1592] 10.sup.th aspect of "Customer Requirements": The method for
agriculture according to any one of the 7.sup.th to 9.sup.th aspect
of "Customer Requirements", comprising the step of transmitting
information items in relation to the plant growth or the plant
health (actual values) to the customer.
[1593] If active monitoring of the growth occurs, then these
information items may also be made accessible to the customer, for
example as a data record, as an image (or camera recording) or in
the form of a graphical representation (e.g. virtual or augmented
reality). Furthermore, the customer can be informed in respect of
the expected delivery date and an appropriate product certificate
may also be issued to them.
[1594] "Success Score"
[1595] According to the element "Success Score" of the disclosure,
a controlled agricultural system is configured to be able to
evaluate a success score for growing a customized plants based on
the setup of the agricultural system. Furthermore, the controlled
agricultural system is able to control and/or (re-)adjust the
growth parameter and other relevant parameters such that the goal
is reached (if feasible), in some embodiments/implementations in
the optimal way or at least approximately.
[1596] 1.sup.st aspect of "Success Score": A Controlled
Agricultural System, comprising an interface for submitting and/or
receiving requests for a customized plant, a data storage device
comprising growth recipes of plants, a computing device, configured
to choose a growth recipe from the data storage device matching to
the request, the computing device, further configured to render a
model plant (digital plant twin) based on the chosen growth recipe,
an actuator device able to adjust growth parameters of plants, a
sensor device able to measure distinctive characteristics of
plants, particularly suitable for monitoring plant growth (measured
data of real plants), the computing device, further configured to
control the actuator device based on the data stored in the data
storage device, particularly for conducting growth recipes, the
computing device, further configured to collect the data from the
sensor device, particularly for monitoring the growth status of the
plants, the computing device, further configured to compare the
data of real plants measured by the sensor device with the data of
the model plant stored on the data storage device and to identify
possible differences between the real plant and the model
plant.
[1597] The grower can insert his demand or the demand of his
customer in a special customized plant project dashboard (or any
other user interface), which may be a general platform, e.g. a
digital platform like an online-platform, to which several growers
are connected. The customer of the grower, which may be a retailer,
e-grocer, pharma company or food processor, may even be directly
linked to the digital platform and submit his/her demands
directly.
[1598] The demand may include plant quantity, plant quality and/or
delivery time. Plant quality is mainly defined by primary and
secondary metabolites as well as appearance. Plant quantity is
defined by yield (fresh or dry weight). As an example, if an
e-grocer wants to run a summer campaign for spicy mojitos and needs
special mojito mint, which tastes strong/spicy, he can insert this
demand into the platform. The platform automatically finds hits
where this mint has been grown with a special spicy flavor profile
and suggests a "Customized growth recipe" to create this customized
product.
[1599] 2.sup.nd aspect of "Success Score": The Controlled
Agricultural System according to the 1.sup.st aspect of "Success
Score", wherein the computing device is further configured to
choose the best-match growth recipe currently available in the data
storage device.
[1600] Furthermore, the controlled agricultural system is
configured to assess, which growth recipe might be needed/suitable
to achieve the desired results under the premises that for example
taste, sugar content, acid content, and content of aromatic
components can be controlled and adjusted by different growth
parameters (environmental) and by nutrients and, if necessary,
pesticides.
[1601] One example is getting hotter chili peppers by doing the
cultivation very dry (less water supply)). The growth recipes can
be predefined growth recipes from sources like growth substrate
manufacturers, lighting companies, universities, and governmental
institutions.
[1602] The growth recipes are stored in an accessible database. The
database can be updated by the platform provider or by the growth
recipe provider through APIs. In some embodiments/implementations,
the controlled agricultural system choses the best-match growth
recipe currently available in the database.
[1603] The controlled agricultural system according to the
disclosure comprises a computing device. Considering all inputs
(e.g. quality, pricing, available capacity), the computing device
is configured to either select or calculate which growth recipe can
be used to reach the goal, in some embodiments/implementations in
the optimal way.
[1604] To do this, the computing device "knows" which environmental
or other growth parameters influence the plant parameters for the
specific plant or biologically similar plants (e.g. from the same
plant family) and can either select or suggest suited growth
parameters for the desired result, for example by calculating
suited growth parameters (including suited light recipes) by
applying artificial intelligence (AI) or similar methods based on
the currently available database information and customer
input.
[1605] A growth recipe comprises for example values for light
recipes (spectrum, intensity, photoperiod), CO2-content of the air,
temperature, humidity, nutrients, EC (electrical conductivity), pH,
H2O, etc. A light recipe may comprise a time-sequential set of
individual light recipes.
[1606] 3.sup.rd aspect of "Success Score": The Controlled
Agricultural System according to the 2.sup.nd aspect of "Success
Score", wherein the computing device is further configured to
analyze whether the best-match growth recipe can be realized with
the available setup of the controlled agricultural system and,
otherwise, suggests a feasible growth recipe.
[1607] However, the actual setup (light sources, lighting fixtures,
placement of lighting fixtures, actuators) will be different for
almost every grower so that the pre-defined growth recipe might not
provide the optimal result for each and every case. New
requirements that have not been tested before might also not lead
to or even prohibit the desired results.
[1608] The controlled agricultural system comprises a sensor device
(sensor device system) that measures the deviations and
collects/stores the data (e.g. in the cloud or a local data storage
device) and feeds the collected information into the database. The
sensor device system may contain a variety of different sensor
types in order to measure a variety of relevant plant growth data
as well as post-harvest plant data, like the concentration of
certain enzymes or the concentration of vitamins and glucose. The
sensor device may be configured to establish a communication
network between themselves.
[1609] Digital Model Plant ("Digital Twin")
[1610] Based on all the collected data describing the "real" plant
growth and selected or calculated and applied growth parameters
that should lead to a desired plant growth, the computing device is
configured to render a model plant, a "digital plant twin", e.g.
based on artificial intelligence. This digital plant twin
encompasses the applied input factors (=growth recipes which
includes pre-defined recipes and recipes from growers) and delivers
the correlated output factors (=growers results). A digital
horticultural plant can also be called a virtual plant or a digital
twin model.
[1611] With the help of the digital plant twin, the computing
device is configured to analyze deviations to the ideally wanted
plant and assesses which growth parameters (may) lead to deviations
from the ideal plant. To do the assessment, the computing device is
configured to compare the digital plant twin, which is described by
all relevant growth parameters (=growth recipe) with the
measured/collected real growth data plus the post-harvest data
referring to plant quality and quantity as documented in the
controlled agricultural system by the grower/user. The deviations
between both datasets (model vs. real) are automatically recorded
by the system and stored in the database. Based on several
installations (different customers), these deviations are
documented and influencing patterns are identified and interpreted
by algorithms (=machine learning) in order to define that a
specific deviation to the model (=growth recipe) led to a specific
effect in the plant growth and post-harvest results. Thus, the
disclosure enables to define growth recipes adapted to a specific
growth environment.
[1612] Examples of different results compared to the digital model
could be faster growth time, different plant quality (e.g. more
anthocyane in a lollo rosso lettuce or higher glycemic index (GI)
values in a strawberry) or more yield (e.g. more tomatoes per
m.sup.2). In case the data set is insufficient or the types of
sensors are inadequate to find an acceptable solution, the
computing device can suggest selection and placement of additional
sensors based on stored database information.
[1613] 4.sup.th aspect of "Success Score": The Controlled
Agricultural System according to any one of the 1.sup.st to
3.sup.rd aspect of "Success Score", wherein the computing device is
further configured to adjust the growth parameter by means of the
actuator device in order to minimize any differences between the
real plant and the model plant.
[1614] 5.sup.th aspect of "Success Score": The Controlled
Agricultural System according to any one of the 1.sup.st to
4.sup.th aspect of "Success Score", wherein the actuator device
comprises one or more actuators able to adjust one or more of the
following growth parameters: water, nutrient, light (intensity,
spectrum), humidity, temperature, air ventilation, pesticides.
[1615] 6.sup.th aspect of "Success Score": The Controlled
Agricultural System according to any one of the 1.sup.st to
5.sup.th aspect of "Success Score", wherein the sensor device
comprises one or more sensors able to measure one or more of the
following parameters: temperature, illumination (intensity, color
temperature, spectrum), and/or the color and/or the chemical
constituents and/or or the morphology of the plants and fruits,
and/or optical devices, e.g. cameras for imaging methods.
[1616] 7.sup.th aspect of "Success Score": The Controlled
Agricultural System according to any one of the 1.sup.st to
6.sup.th aspect of "Success Score", wherein the computing device is
further configured to evaluate a success score based on data stored
in the data storage device from similar configurations regarding
customer demand, result of the corresponding plant project and the
setup of the respective agricultural system.
[1617] In a preferred embodiment, the controlled agricultural
system is configured to use artificial intelligence (AI) or Deep
Learning methods to calculate customized growth recipes based on
different grower data. The likelihood of a successful growth
according to the customer's wishes highly depends on the database,
i.e. the available knowledge about the desired plant features. For
example, the likelihood is high (e.g. >90%) if several customers
(e.g. >2 customer) had the same wishes and have successfully
grown the customized product. However, the likelihood is low
(<10%) if no customer has grown the respective plants with
comparable requirements. This likelihood can also be expressed in
terms of statistical standard deviations, like 1, 2 or 3 sigma. The
higher the likelihood of getting the desired results, the higher
the success score.
[1618] Furthermore, the controlled agricultural system may have an
automatic algorithm to search for data overlap of growing
conditions (plant, facility, sensors, actuators, etc.), required
plant expression or characteristics (=customized plant) and
successful growth according to requirements. Based on that, the
system is generating and displaying an estimated success score at
the beginning of a possible project to the customer. The success
score could go for example from 1 to 10 points whereas 10 is
expressing total confidence of a successful plant growth according
to the desired outcome (=likelihood 100%) and 1 is meaning very low
confidence.
[1619] 8.sup.th aspect of "Success Score": The Controlled
Agricultural System according to the 7.sup.th aspect of "Success
Score", wherein the computing device is further configured to
suggest measures for improving the success score if the evaluation
initially resulted in an unacceptable low value.
[1620] For low success score values for example below 7 (=70%
likelihood) the system recommends measures to increase the
confidence level for a successful growth. The suggested measures
could include a pilot test together with a description how to set
it up. It could also include cultivation support by a respective
expert in the field. The support can be done physically or remotely
over the platform in form of a webcast. Another measure could be to
suggest directly connecting two growers growing the same cultivar
to enable information sharing between both parties. This of course
should be approved by both parties beforehand.
[1621] 9.sup.th aspect of "Success Score": A method for
agricultural management, comprising at least one controlled
agricultural system according to any one of the 1.sup.st to
8.sup.th aspects and the steps of, receiving a demand on the
platform (growers view), submitted by a customer via the dashboard
of the platform (customers view), determining the growth parameters
that influence the plant characteristics relevant to the customer's
demand, calculating a growth recipe (preferably best-match;
optionally extrapolating from existing growth recipes) by means of
the computing device based on the information of the previous steps
and the database, e.g. a collection of growth recipes and results
achieved under various environmental conditions and agricultural
system setups, rendering a model plant (digital plant twin) by
means of the computing device based on the growth recipe determined
in the previous step.
[1622] 10.sup.th aspect of "Success Score": A method for
agricultural management according to the 9.sup.th aspect of
"Success Score", further comprising the steps of comparing the
growth of the real plant with the model plant by means of the
computing device based of the data from the sensor device and the
digital plant twin and detecting possible deviations between real
plant and model plant.
[1623] 11.sup.th aspect of "Success Score": A method for
agricultural management according to the 10.sup.th aspect of
"Success Score", further comprising the steps of analyzing which
growth parameters caused the deviations between the real plant and
the model plant by means of the computing device, adjusting the
growth parameters of the growth recipe by means of the actuator
device and the computing device in order to minimize the detected
deviations.
[1624] All projects are documented in the database (located on
platform and/or local data storage device) including customer and
price. Additionally the platform of the grower may be connected
through APIs to utility companies, weather companies, growth recipe
input providers, etc. Based on this data as well as the input
factors of the customized growth recipe, a cost per
kg/plant/tray/etc. is calculated.
[1625] 12.sup.th aspect of "Success Score": A method for
agricultural management according to any one of the 9.sup.th to
11.sup.th aspects of "Success Score", further comprising the steps
of storing the environmental data and growth data of the real
plant(s) collected by means of the sensor device and the
post-harvest data (particularly regarding the characteristics
relevant to the customer's demand) into the database.
[1626] All the above-described measures have the intention to
increase the success score for the grower and improving the
database of the system. If the goal is reached and the likelihood
is increased, the grower feeds the information back to the system.
The information could be changing parameters to the growth recipe
according to the consultation feedback or successful trial.
Thereafter, the grower is starting with the growing according to
the (updated) parameters of the digital plant twin. The real data
and post-harvest data are thereafter brought back in the system for
usage of customized plant growth recipes and success scores.
[1627] 13.sup.th aspect of "Success Score": A method for
agricultural management according to any one of the 9.sup.th to
12.sup.th aspects of "Success Score", further comprising the steps
of analyzing by means of the computing device which growth recipe
is feasible with the available setup of the controlled agricultural
system, in some embodiments/implementations based on the best-match
growth recipe, optionally extrapolating from existing growth
recipes.
[1628] 14.sup.th aspect of "Success Score": A method for
agricultural management according to any one of the 9.sup.th to
13.sup.th aspects of "Success Score", further comprising the steps
of searching the database for similar configurations (setup, growth
recipe) by means of the computing device, calculating a success
score for estimating the chances of success for growing the
customized plant, by means of the computing device based on the
search result.
[1629] Customized Plant Growth
[1630] Appropriate ("best match") growth recipes may be provided by
third parties. However, the use of 3.sup.rd-party growth recipes
may require a royalty payment (license fee). Therefore, the
controlled agricultural system may be configured to be able to
calculate the overall costs for using the recipes and alternatives,
including used materials like nutrients, costs for electricity,
wear of the equipment and the probably achievable quality, and
chose an optimum.
[1631] The revenue potential can be calculated based on the target
price of the customer or market prices received via APIs from other
customers or online-marketplace.
[1632] The platform is calculating and showing the grower the cost
estimation and revenue potential per project. Based on that the
platform develops the best possible cost-revenue production
planning with maximum capacity utilization.
[1633] The grower, of course, can select projects (or certain
features e.g. concerning quality) as mandatory so that they are
executed in any case. These settings are considered in the
remaining production planning.
[1634] If the grower has idle acreage/space to grow crops he wants
to, i.e. he has no binding customer projects, the platform suggests
the best crop to grow based on relevant data like maximum margin or
tests to improve quality/quantity of regularly demanded products or
product features.
[1635] Based on this planning, delivery times are calculated. If
the customer wants to push the delivery date the platform suggests
changes to the production planning to the grower.
[1636] 15.sup.th aspect of "Success Score": A method for
agricultural management according to any one of the 9.sup.th to
13.sup.th aspects of "Success Score", further comprising the steps
of preparing an offer based on customer's demand, calculated costs
and, optionally, the success score calculated, submitting the offer
to the customer, in some embodiments/implementations via the
platform, by addressing the dashboard of the customer who submitted
the request.
[1637] When a customer is inserting a demand for a customized plant
(via dashboard), the platform gives the corresponding offer of a
grower either directly to the customer through an API or open
platform (success score, delivery time and price) or personally to
the customer.
[1638] 16.sup.th aspect of "Success Score": A method for
agricultural management according to the 15.sup.th aspect of
"Success Score", further comprising the step of requesting
amendments (e.g. price, plants characteristics, delivery . . . ) to
the offer by the customer, in some embodiments/implementations via
the platform.
[1639] If the customer wants to change the offered time, price or
is not satisfied with the success score (i.e. the calculated
probability to reach the goal), he can insert this additional
demand into the dashboard. Either the platform has the rights to
consider adjustments to the production planning or reports this
requests to the grower who may approve or reject the demand.
[1640] 17.sup.th aspect of "Success Score": A method for
agricultural management according to the 15.sup.th or 16.sup.th
aspect of "Success Score", further comprising the step of making a
respective contract between the costumer and the grower, in some
embodiments/implementations via the platform, if both parties agree
to the deal.
[1641] If agreed by both parties the deal making process is
completed and the contract is established in the checkout process
of the platform. If no deal has been established the platform could
suggest another grower (match making).
[1642] 18.sup.th aspect of "Success Score": A method for
agricultural management according to any one of the 9.sup.th or
17.sup.th aspects of "Success Score", further comprising the step
of presenting the growth status of the customized plants to the
customer, in some embodiments/implementations via the platform,
e.g. on customer's dashboard.
[1643] Once the project is started the customer can see his
customized plant project in a special dashboard including all
relevant data (fertilizer use, pesticide use, CO2 footprint, seeds,
space, water use, planned output on day X in /$, current status of
the technical equipment-running time of luminaries, pumps
etc.+estimated running time of plants). The dashboard can also be
open to the end consumers if wished. Furthermore, the percentage of
completion may be shown. In case of delays or problems during the
production the customer is informed through notifications of the
platform. In case of major problems, the grower is informed so
he/she can personally inform the customer.
[1644] All relevant data is send as a report or automatically
through an API to the grower for traceability and for content
marketing towards the end customers.
[1645] If wished special landing pages and dashboards can be
created for the customer e.g. "Your Mojito from Seed to Drink--Join
the food and beverage revolution".
[1646] 19.sup.th aspect of "Success Score": A computer program
product, comprising a plurality of program instructions, which when
executed by a computer system of a Controlled Agricultural System
according to any one of the 1.sup.st to 8.sup.th aspect of "Success
Score", cause the Controlled Agricultural System to execute the
method for Agricultural Management according to any one of the
9.sup.th to 18.sup.th aspect of "Success Score".
[1647] 20.sup.th aspect of "Success Score": An agricultural
facility, e.g. (vertical) farm, greenhouse, etc., with at least one
Controlled Agricultural System according to any one of the 1.sup.st
to 8.sup.th aspect of "Success Score".
[1648] "Picture Taking & Evaluation"
[1649] According to the element "Picture Taking & Evaluation"
of the disclosure, a method for agricultural management, which
enriches the data that may be captured by a controlled agricultural
system, by means of taking and evaluating pictures for monitoring,
tracking and optimizing plant growth.
[1650] Below, various aspects and details of "Picture Taking &
Evaluation" are described.
[1651] 1.sup.st aspect of "Picture Taking & Evaluation": A
method for agricultural management, particularly for plant
breeding, growing, cultivating and harvesting in an agricultural
facility, comprising a mobile device with a camera (still and/or
video), configured to be able to contribute to the following steps:
starting a picture mode on the mobile device, providing a picture
frame shown on a screen of the mobile device and indicating how to
achieve alignment for taking a standardized picture of an
horticultural object, targeting a horticultural object with the
camera and aligning the viewer picture to the picture frame,
checking alignment, re-aligning if still out of alignment and
taking a standardized picture of the horticultural object if in
alignment.
[1652] To enable comparable and usable data gained from pictures,
standardized pictures need to be taken. These standard pictures
could have different motives, dimensions and angles but are
predefined. Standard pictures could be distance shot, figure shot,
full shot, medium shot, close-ups, extreme close-ups, etc.
[1653] To facilitate taking these standardized pictures, the
present disclosure suggests a software program for a suitable
mobile device (app), e.g. a smartphone app, which assists the user
when taking standardized pictures. For this purpose, the
(smartphone) app has a dedicated picture taking function. This
function helps growers to make standardized pictures by giving
picture frame orientation on the respective mobile device (e.g.
mobile phone) screen (e.g. by yellow rectangle and when motive fits
into frame, frame gets green and picture will be taken).
[1654] 2.sup.nd aspect of "Picture Taking & Evaluation": The
method for agricultural management according to the 1.sup.st aspect
of "Picture Taking & Evaluation", further comprising the step
of selecting an object type from a set of object types, e.g. plant
(single, multiple), growing cabinet.
[1655] The frames for the standardized pictures may be predefined
depending on the growth environment (e.g. a specific vertical farm
or a growth cabinet). The present environment may be input
manually. Alternatively, the app may contain a picture recognition
software for identifying the environment.
[1656] 3.sup.rd aspect of "Picture Taking & Evaluation": The
method for agricultural management according to the 1.sup.st or
2.sup.nd aspect of "Picture Taking & Evaluation", further
comprising the step of selecting a picture style from a set of
picture styles, e.g. distance shot, figure shot, full shot, medium
shot, close-ups, extreme close-ups.
[1657] 4.sup.th aspect of "Picture Taking & Evaluation": The
method for agricultural management according to the 3.sup.rd aspect
of "Picture Taking & Evaluation", further comprising the step
of taking multiple pictures of the same object with same or
different picture styles.
[1658] Of course, in addition to (still) pictures, also videos
(motion pictures) can be taken. Smartphone pictures are usually
taken in daylight without the use of a flash, but during night
situations, a flash (or a flash working as a continuous auxiliary
lighting) with a (standardized) setting can be used. In addition, a
smartphone camera may be suited to take pictures in the infrared,
for example by using an IR-LED or VCSEL (Vertical Cavity Surface
Emitting Laser), for flash or auxiliary lighting purposes.
[1659] In addition, a face or eye tracking/scanning system of a
smartphone (e.g. Apple iPhone X) may be adapted for gathering
further information. When a smartphone with such a system is used,
the device could directly measure the physiognomy/morphology of a
nearby plant (close up) and provide this data to the app. This
helps to come up with plant morphology recognition much faster than
feeding it to a separate software program, and it can be posted
directly on social networks and to user groups.
[1660] 5.sup.th aspect of "Picture Taking & Evaluation": The
method for agricultural management according to any one of the
1.sup.st to 4.sup.th aspect of "Picture Taking & Evaluation",
further comprising the step of evaluating the picture(s) and
showing the results, particularly with respect to plant growth
status and plant health.
[1661] 6.sup.th aspect of "Picture Taking & Evaluation": The
method for agricultural management according to any one of the
1.sup.st to 5.sup.th aspect of "Picture Taking & Evaluation",
wherein the picture frame comprises indications (e.g. four arrows,
one arrow in each corner of the frame oriented to the center of the
frame) for indicating to the user how to achieve alignment for
taking a standardized picture of the horticultural object.
[1662] 7.sup.th aspect of "Picture Taking & Evaluation": The
method for agricultural management according to any one of the
1.sup.st to 6.sup.th aspect of "Picture Taking & Evaluation",
wherein aligning the viewer picture to the picture frame comprises
adapting the position and/or the orientation (vertically and
horizontally) of the mobile device with respect to the respective
horticultural object (e.g. plant).
[1663] In a further refinement of the disclosure, based on the
taken pictures, software algorithms are provided for calculating
plant growth indices like Leaf Area Index (LAI) or NDVI (Normalized
Difference Vegetation Index), give feedback about
coloring/pigmentation, give feedback on plant health based on
colors and growth, count fruits and vegetables, plant morphology,
pest manifestation, insects, mildew etc.
[1664] The data analytics/algorithms may be provided directly in
the app or the data may be uploaded to the cloud and analyzed there
(by means of a dedicated software service). Furthermore, the
software (app), for example, may be designed to develop a
topographic map or 3D data models based on different pictures, e.g.
taken at different positions, possibly also under different
angles.
[1665] The results provided by the software, here also named
Graphical Output (GO), may be displayed to the grower on the
graphical user interface (GUI) of the mobile device (e.g.
smartphone) with graphs, growth trackers, time lapse videos, etc.
Additionally, the (smartphone) app may automatically
benchmark/compare to other growers/users and to the grower's own
historical results and displays these historical and benchmarking
values on the GUI.
[1666] Based on the real-time, historical and benchmarking data the
(smartphone) app may give scores and badges to the grower according
to the success. Additionally, the software (algorithms, AI) may be
designed for calculating and doing forecasts to estimate harvest
dates.
[1667] Furthermore, the software may be designed to recognize
abnormalities in the pictures. Finally, the software may be
designed to compare the captured pictures with a picture database
to determine plant abnormalities (mold, pest, nutrient lack, tip
burn, etc.).
[1668] 8.sup.th aspect of "Picture Taking & Evaluation": A
Controlled Agricultural System, particularly for breeding, growing,
cultivating and harvesting in an agricultural facility,
particularly a plant growing facility and/or an aquaponics
facility, comprising a mobile device with a camera configured to
perform the steps according to any one of the 1.sup.st to 7.sup.th
aspect of "Picture Taking & Evaluation".
[1669] 9.sup.th aspect of "Picture Taking & Evaluation": The
Controlled Agricultural System according to the 8.sup.th aspect of
"Picture Taking & Evaluation", further comprising a data
storage device, e.g. for storing the pictures and/or the plant
growth results deduced by evaluating the pictures.
[1670] Furthermore, the (smartphone) app may be designed to suggest
new plant growth recipes (i.e. adjustments to the present growing
conditions).
[1671] The (smartphone) app may also be designed to directly
connect to the climate control system, a growth cabinet, or the
like of the facility so that the actuation of an actuator is
directly controlled via the mobile device (e.g. smartphone). Direct
connection may be established, for instance, via Bluetooth, WiFi,
Radio Frequency, VLC (Visible Light Communication). If it is
directly connected, the smartphone app may also ask the grower if
the conditions should be adjusted to the new recipe and by
approving of the grower, this is done automatically.
[1672] 10.sup.th aspect of "Picture Taking & Evaluation": A
Controlled Agricultural System, particularly for breeding, growing,
cultivating and harvesting in an agricultural facility,
particularly a plant growing facility and/or an aquaponics
facility, comprising one or more lighting fixtures for illuminating
the plants, and/or one or more actuators, e.g. heating, wherein at
least one lighting fixture and/or at least one actuator is
configured to be controllable by means of a mobile device, e.g. a
smartphone.
[1673] 11.sup.th aspect of "Picture Taking & Evaluation": The
Controlled Agricultural System according to the 10.sup.th aspect of
"Picture Taking & Evaluation", further comprising a sensor
device able to measure environmental parameters, e.g. the ambient
temperature of the agricultural facility, and/or growth parameters
of the plants.
[1674] 12.sup.th aspect of "Picture Taking & Evaluation": The
Controlled Agricultural System according to the 10.sup.th or
11.sup.th aspect of "Picture Taking & Evaluation", further
comprising a computing device, configured to be able to access and
control the sensor device and the data storage device.
[1675] 13.sup.th aspect of "Picture Taking & Evaluation": The
Controlled Agricultural System according to the 12.sup.th aspect of
"Picture Taking & Evaluation", wherein the computing device is
further configured to evaluate the environmental data and/or growth
data measured by the sensor device and outputs a notification if
the measured data exceeds a tolerance range.
[1676] 13.sup.th aspect of "Picture Taking & Evaluation": The
Controlled Agricultural System according to the 13.sup.th aspect of
"Picture Taking & Evaluation", configured to be able to send
the notification to a mobile device, e.g. via a dedicated app
software.
[1677] All the data from the Graphical Output Interface (GOI) may
be displayed on a user-friendly dashboard for constant monitoring,
notification and optimization. The grower can share and comment
results in the app and on social media if wanted.
[1678] 15.sup.th aspect of "Picture Taking & Evaluation": A
method for agricultural management, particularly for plant
breeding, growing, cultivating and harvesting in an agricultural
facility, comprising a Controlled Agricultural System according to
any one of the 10.sup.th to 14.sup.th aspect of "Picture Taking
& Evaluation", wherein the mobile device is configured to be
able to contribute to the following steps: controlling and
regulating the at least one lighting fixture and/or actuator based
on executable command data transmitted by the mobile device.
[1679] If the app is not connected to the dedicated climate control
system, the app may be designed to communicate with and control the
actuators of the controlled agricultural system like HVAC, light,
water pumps, etc. via the smartphone microphone/speaker and
dedicated ultrasonic sequences. For this, the actuators need to be
equipped with ultrasonic sensors and respective controllers.
Alternatively, the respective actuation may be controlled by
modulations of a smartphone photoflash LED, also called Visible
Light Communication (VLC), or a specific IR-LED.
[1680] 16.sup.th aspect of "Picture Taking & Evaluation": A
method for agricultural management according to the 15.sup.th
aspect of "Picture Taking & Evaluation", wherein the executable
command data comprise dedicated (ultra)sonic sequences generated by
the speaker of the mobile device or modulations of a photoflash LED
or a specific IR-LED.
[1681] In a further embodiment, the controlled agricultural system
comprises horticultural lighting fixtures that employ sensors
(photoelectrical, piezo, etc.). Optionally, the (Smartphone) app is
designed to connect to these fixtures (as described above) and to
control and regulate the fixtures based on the transmitted
executable command data.
[1682] 17.sup.th aspect of "Picture Taking & Evaluation": A
computer program product, comprising a plurality of program
instructions, which when executed by a mobile device with a camera
cause the mobile device to execute the Method for Agricultural
Management according to any one of the 1.sup.st to 7.sup.th aspect
of "Picture Taking & Evaluation".
[1683] 18.sup.th aspect of "Picture Taking & Evaluation": A
computer program product, comprising a plurality of program
instructions, which when executed by a mobile device with a camera
cause the mobile device to execute the Method for Agricultural
Management according to the 15.sup.th or 16.sup.th aspect of
"Picture Taking & Evaluation".
[1684] "Eco Certificates"
[1685] According to the element "Eco Certificates" of the
disclosure, a method for agricultural management, in other words a
method for managing an agricultural facility, comprising a
life-cycle assessment is proposed, based on which an operator,
customer or other user can act and, for example, take account of
ecologically evaluated light recipes or an ecological overall
balance.
[1686] Furthermore, a breeding and/or growing and/or raising
facility (agricultural facility) with an improved ecological
compatibility is proposed.
[1687] Below, various aspects and details of "Eco Certificates" are
described. Particularly, a multiplicity of irradiation variants and
illumination controls for breeding and/or growing plants are
highlighted. By way of example, ecologically evaluated light
recipes can be used for illumination purposes, or an ecological
overall balance can be taken into account when selecting the
illumination variants.
[1688] 1.sup.st aspect of "Eco Certificates": A method for
agricultural management, more specifically a method for operating a
breeding and/or growing and/or raising facility, in particular a
breeding and/or growing and/or raising facility for plants and/or
animals (agricultural facility), comprising the steps of inputting
input data into a computing device by way of an input device,
processing the input data in the computing device and outputting
output data to an output device by the computing device, wherein
the output data at least contain information items in relation to a
life-cycle assessment, an energy consumption or a carbon
footprint.
[1689] In this way, a life-cycle assessment can be observed when
producing the products of the breeding and/or growing and/or
raising facility.
[1690] 2.sup.nd aspect of "Eco Certificates": The method for
agricultural management according to the 1.sup.st aspect of "Eco
Certificates", wherein the output data for controlling the facility
are inputted into a control device in one method step, wherein, in
particular, the control unit also may comprise the input device,
the computing device and/or the output device.
[1691] That is to say, the data calculated by the computing device
in the control unit can be used as new input data either in this
control unit or in a further control unit. This may permit a
control loop, and so adaptive control of the breeding and/or
growing and/or raising facility, of the illumination device or else
of individual light sources may be implemented on the basis of
evaluated data, e.g., in relation to growth and the like, or else
on the basis of additional data, e.g., on account of customer
requirements, system-related restrictions, legal requirements or
the like.
[1692] 3.sup.rd aspect of "Eco Certificates": The method for
agricultural management according to the 2.sup.nd aspect of "Eco
Certificates", wherein the control is modified by the control
device on the basis of the output data in such a way that a
predetermined life-cycle assessment, an energy consumption or a
carbon footprint, in particular of an added-value process of the
products or of a growth or maturing process, is not exceeded.
[1693] Such a modification of a control or actuation of the
facility or the components thereof can allow a user, operator or
customer to produce or select products that meet certain ecological
or economical requirements.
[1694] 4.sup.th aspect of "Eco Certificates": The method for
agricultural management according to any one of the 1.sup.st to
3.sup.rd aspect of "Eco Certificates", wherein the method includes
a step in which the computing device calculates and/or selects a
light recipe in order to obtain a predefined effect, in some
embodiments/implementations boundary conditions defined by input
data, in particular in order to observe a predetermined life-cycle
assessment or meet ecological boundary conditions.
[1695] In particular, these boundary conditions may be the
observance of a predetermined life-cycle assessment or other
ecological prescriptions. Here, light recipes can be stored in a
database and already be evaluated and assessed in respect of their
life-cycle assessment, energy consumption or similar parameters. By
calculating new light recipes, for example on the basis of newly
employed light sources, on the basis of the application to new
types of plants or animals or on the basis of simply an improvement
of existing light recipes, it is thus possible to match an energy
consumption to the actual requirements of the products.
[1696] 5.sup.th aspect of "Eco Certificates": The method for
agricultural management according to any one of the 1.sup.st to
4.sup.th aspect of "Eco Certificates", wherein the method includes
a step for determining a life-cycle assessment resulting from the
energy consumption of an illumination apparatus, in particular a
horticultural illumination, and/or the entire energy consumption
and/or CO.sub.2 equivalent of the facility.
[1697] 6.sup.th aspect of "Eco Certificates": The method for
agricultural management according to any one of the 1.sup.st to
5.sup.th aspect of "Eco Certificates", wherein a light recipe is
established by a control device, wherein the step of establishing
the light recipe provides for at least the evaluation of an energy
consumption data record of energy consumers provided in the light
recipe, wherein the light recipe is determined in such a way that
an energy consumption lies below a pre-determinable threshold.
[1698] 7.sup.th aspect of "Eco Certificates": The method for
agricultural management according to any one of the 1.sup.st to
6.sup.th aspect of "Eco Certificates", wherein the method includes
a step for determining an entire photon flux of a light recipe of
the breeding and/or growing and/or raising facility, wherein the
step for determining the photon flux includes reading at least one
sensor and/or reading at least one data record with information
items relating to photon flux of light sources used in the light
recipe.
[1699] The corresponding data, also sensor data, may be stored in a
database, for example, contain current sensor data, directly
acquired by a sensor and transmitted to the control device, or
contain both. In particular, it is also possible to process data
from different sensors, both local and distant, and/or different
databases in the process.
[1700] 8.sup.th aspect of "Eco Certificates": The method for
agricultural management according to any one of the 1.sup.st to
7.sup.th aspect of "Eco Certificates", wherein the data in relation
to life-cycle assessment are output on a display apparatus and/or
stored in a database in a method step such that the data are
provided to a user, operator and/or customer.
[1701] 9.sup.th aspect of "Eco Certificates": A method for
agricultural management, more specifically a method for operating a
breeding and/or growing and/or raising facility, in particular a
breeding and/or growing and/or raising facility for plants and/or
animals, comprising a step for processing an order of at least one
product produced in the breeding and/or growing and/or raising
facility, wherein a control device has at least one input means
with a communications unit such that a data entry, in particular an
indication of demand, is assignable to a production or planned
production in the control device from an external interface.
[1702] In particular, an ordering platform can be directly or
indirectly coupled to a control device of the agricultural facility
and so a need can be acquired directly on the basis of incoming or
pending orders and can be taken into account in controlling and
organizing the breeding and/or growing and/or raising facility.
Thus, for example, sowing can be actuated, in particular by a
sowing apparatus or sowing robot, in order to sow a desired product
in order to service an increased demand that cannot be covered by
existing growing products.
[1703] 10.sup.th aspect of "Eco Certificates": The method for
agricultural management according to the 9.sup.th aspect of "Eco
Certificates", wherein the external interface may comprise an input
terminal, wherein the input terminal is embodied in such a way that
a user and/or a machine and/or program code can input at the input
terminal an indication of demand in respect of one or more products
to be produced in the agricultural facility.
[1704] In this way, a need can be planned more precisely and
overproduction can be avoided. Moreover, a completion of the
production can be matched to the demand, and so storage times, and
losses and reductions in quality caused thereby, may be
reduced.
[1705] 11.sup.th aspect of "Eco Certificates": The method for
agricultural management according to the 9.sup.th or 10.sup.th
aspect of "Eco Certificates", wherein the input of an indication of
demand for the ordering of plant and/or animal products includes a
step for evaluating and/or monitoring a life-cycle assessment of
the products.
[1706] Here, an indication of demand can be an order at the same
time, or merely the announcement of a demand in future, for example
in order to plan a corresponding utilization of the breeding and/or
growing and/or raising facility in timely fashion. Taking account
of life-cycle assessments or ecological boundary conditions for
production already at the time of establishing demand can ease the
observance of these boundary conditions and thus improve the
ability of planning production. Thus, observing the set boundary
conditions can be better ensured, particularly in cases where the
use of alternative light recipes is necessary for treatment
purposes owing to unforeseen events, such as in the case of pest
infestation or disease.
[1707] 12.sup.th aspect of "Eco Certificates": The method for
agricultural management according to any one of the 9.sup.th to
11.sup.th aspect of "Eco Certificates", wherein the method includes
a step for automatically triggering an indication of demand of a
plant and/or animal product depending on whether a selected product
has reached a predefined threshold, in particular a predetermined
plant growth and/or a degree of maturity and/or a nutrient content
and/or a mineral content.
[1708] This may allow a customer to indicate demand, for example on
a transfer platform, and this may allow production to be
implemented, either on the basis or independently thereof, such
that once the boundary conditions and preconditions saved by the
customer are reached, this can be automatically acquired and
processed as an order; in particular, harvesting and delivery may
be implemented.
[1709] The data can be provided at a single occasion, at regular
intervals, when certain growth or maturity phases are reached, or
else virtually in real time, depending on sensor data and
measurement intervals, for example.
[1710] These data of one or more breeding and/or growing and/or
raising facilities can be compared on the transfer platform with
indications of demand of one or more customers, in some
embodiments/implementations a multiplicity of customers. As soon as
a predefined criterion is reached, for example a criterion that was
predefined by a customer, an automatic order can then be triggered
on the transfer platform.
[1711] 13.sup.th aspect of "Eco Certificates": A data storage
medium, containing a control program for carrying out a method
according to any one of the 1.sup.st to 12.sup.th aspect of "Eco
Certificates".
[1712] 14.sup.th aspect of "Eco Certificates": The data storage
medium according to the 13.sup.th aspect of "Eco Certificates",
wherein the data storage medium contains at least one database with
light recipes and/or life-cycle assessments of a breeding and/or
growing and/or raising facility, illumination device, light source,
etc., and/or data in relation to requirements of the products to be
produced in respect of growth, health, contents or the like.
[1713] 15.sup.th aspect of "Eco Certificates": An agricultural
facility, more specifically a breeding and/or growing and/or
raising facility, in particular a breeding and/or growing and/or
raising facility for plants and/or animals, comprising at least one
input device, a computing device and an output device, wherein the
computing device is embodied to output output data to the output
device and wherein the output data include at least information
items in relation to a life-cycle assessment, an energy consumption
or a carbon footprint, and wherein the output device has means for
outputting the output data to a user or a control unit.
[1714] A production of products within the scope of predetermined
boundary conditions, in particular ecological boundary conditions,
can be facilitated in such a facility.
[1715] 16.sup.th aspect of "Eco Certificates": A building
configured for vertical farming and comprising at least one
agricultural facility according to the 15.sup.th aspect of "Eco
Certificates" or being at least part of such a facility and/or
comprising a control device configured to carry out a method
according to any one of the 1.sup.st to 12 aspect of "Eco
Certificates".
[1716] Light Sources
[1717] Characteristics of Light Sources
[1718] Discharge lamps, for example low-pressure sodium vapor lamps
or high-pressure mercury vapor lamps, and halogen lamps are
available as light sources for an illumination device of a breeding
and/or growing and/or raising facility according to the disclosure.
With the development of light-emitting diodes (LEDs), radiation
sources that emit substantially in monochromatic fashion and
radiation sources with a wavelength conversion element, also
referred to as a converter or phosphor, have become available.
Depending on the embodiment, LED light sources can emit in the
ultraviolet, visible or infrared spectrum. The wavelengths of the
emission radiation can be accurately set by means of quantum dot
LEDs. Organic LEDs (OLEDs), electroluminescence light sources,
electrodeless induction lamps and mercury-free dielectric barrier
discharge lamps can also be used as a light module. The light
sources can have a compact or areal embodiment and can be equipped
with primary and secondary optics, such as lenses, light guides,
stationary and/or movable reflectors or radiation-reflective
optical devices, holographic elements, partly transparent or
completely light-opaque films, heat-reflecting films, luminescent
films or the like. Furthermore, use can be made of laser light
sources, in particular those that produce white or colored light by
means of LARP (laser-activated remote phosphor) technology, i.e.,
an activation of a wavelength converter arranged at a distance from
a laser light source. Consequently, a multiplicity of light sources
are available for illuminating the plants and the entire radiation
spectrum (UV, visible, IR) can be covered. Some of the light
sources listed above can also emit wholly or partly polarized
light.
[1719] Different light sources can be combined, for example sodium
vapor lamps and LED light sources. Radiation reflectors can be
moved and/or tilted rhythmically, for example with circadian
control, i.e., depending on solar altitude, with the sun being
visible or else not. Illumination devices can be adaptively matched
in terms of their form and emission direction to the plant growth,
i.e., become narrower or wider or keep the distance from the plant
surface constant or set the distance according to a predetermined
or selected or calculated mathematical function, for example in
order to avoid shadowing of the plants lying further to the
outside. The distance from a plant surface and/or the geometric
form of an adaptively changeable light fixture can also be
implemented depending on the leaf area index or the leaf area
density index (see below in this respect).
[1720] Here, the "light" and "illumination" terms should also
include the radiation components that are not visible to the human
eye, in particular UV and infrared.
[1721] Here, the phrase "plant-growth-promoting illumination"
should also comprise aquaponics illumination. As alternative
phrases, use can be made of "growth-promoting and
maturity-promoting illumination" and "breeding and/or growing
and/or raising illumination".
[1722] [End of "Characteristics of Light Sources" ]
[1723] Operating Mode of Light Sources
[1724] Here, the light sources can be operated in multifaceted
ways, in particular with constant performance data, with
time-variable performance data, for example in a pulsed operation
(basic level, higher or lower level; the time durations can be
equal or different) or in PWM operation (e.g., with a milli-second
or .mu.s clock). The performance data can be controlled within the
scope of feedback. In particular, sensors can be used as a
controlled variable, which is also referred to as a parameter, of
feedback, said sensors outputting a measurement signal on the basis
of one or more influencing variables, such as ambient temperature,
humidity, time of day (circadian), CO.sub.2 content, methane gas
content, ground moisture, substance toxicity, color, reflectivity
of a plant in the visible, ultraviolet and infrared spectral range,
the component of polarized reflection radiation, reflectivity of
the surroundings of a plant in the visible, ultraviolet and
infrared spectral range, respectively also the component of
polarized reflection radiation therefrom, or soil acidity, the
measurement signals being usable by means of an evaluation and
control unit for regulating an emission spectrum and mode of
operation of the light sources, for example, or else for setting
photosynthetically active radiation (PAR), measured in terms of
photon energy or photon flux and expressed in .mu.mol/(m.sup.2*s)
or .mu.Einstein/(m.sup.2*s).
[1725] [End of "Operating Mode of Light Sources" ]
[1726] Parameters of Light Sources/Sensors
[1727] Consequently, light sources can be regulated, in particular
in automated fashion, by acquired parameters, as described above.
On the other hand, it is also possible to accordingly set the light
spectrum, in particular in automated fashion, on the basis of a
plant-specific parameter, such as, e.g., leaf reflectivity or
vitamin C content, or external influencing variables, such as,
e.g., temperature and soil acidity.
[1728] The corresponding sensors can be attached at many locations,
for example in the greenhouse, in the growing chamber, on the
plants, in the ground or in the water tank and/or on the roots.
[1729] The irradiation units may have a modular design, i.e., can
be put together into relatively large units and can also be
removed, for example according to demand, in a manual process or in
a process that is automated by means of a control loop.
[1730] [End of "Parameters of Light Sources/Sensors" ]
[1731] Plant
[1732] Here, the term "plant" should comprise all types of grown
products, such as, e.g., salads, fungi, flowers, cannabis, medical
plants, hydroponic and aeroponic plants, salads, tropical plants,
algae, water plants, cannabis, seedlings and seeds. Fish and plants
are bred and grown in so-called aquaponic farms. Here, the plants
are watered by the nutrient-rich wastewater from the fish.
[1733] [End of "Plant" ]
[1734] Characteristics of Illumination for Light Recipes
[1735] It is known that the plants or growth and also seeds require
optimal radiation of a suitable wavelength distribution and
intensity depending on the growth and maturity phase. This is also
referred to as a growth-related light recipe. Expressed
differently, a targeted control of the properties of the light
sources such as, e.g., the spectral intensity, the emission
characteristic, the color locus, the variation in the spectral
individual intensities and hence in the color locus of a
plant-growth-specific illuminance and plant-specific light spectrum
can be provided for an optimal photomorphogenic influence on
plants, for example in respect of growth and maturity.
Consequently, an optimal illumination scenario, i.e., an
illumination recipe, can be provided depending on the growth and
maturity phase of the plants. Here, illumination can be implemented
from above, from below or from the sides; it is also possible to
illuminate the roots of plants. Plants growing hanging down from
above can be irradiated from below in analogous fashion. A
plant-specific illumination can change over time in terms of its
intensity (radiant flux), emission direction, emission angle,
polarization and spectral properties. Different spectral regions
can be provided simultaneously or sequentially. Different spectral
regions can be provided with different radiant fluxes and with
different ON-OFF cycles. Thus, every spectral region can have an
independent irradiation cycle in this case. The spectral regions
can be disjunct or at least partly overlap. Preferred spectral
regions are: 350 to 520 nm, 520-550 nm, 550-800 nm. Further
preferred spectral regions are: 420-450 nm, 450-470 nm, 500-550 nm,
510-540 nm, 570-600 nm, 580-600 nm, 610-660 nm, 625-650 nm.
Preferred color temperatures, a quantity known from illumination
engineering, may be less than 5000 K or greater than 5000 K, for
example up to 10 000 K. The color rendering index of an
illumination device for white light may lie in the region of
greater than 90.
[1736] LED light sources may be grouped according to their light
properties; by way of example, blue light sources, in particular
all blue light sources, can be grouped together and/or red light
sources, in particular all red light sources, can be grouped
together. However, they can also be arranged in mixed fashion,
inter alia in the form of geometric patterns, too. By way of
example, three blue LEDs could be surrounded by eight red LEDs.
LEDs with different spectral properties can be placed in
triangular, rectangular or polygonal arrangements, for example.
They can fill up an area without gaps. The arrangement can also be
unordered and arbitrary. The light-emitting sources can also be
arranged in a light fixture in such a way that different emission
regions, which are equipped with at least two different light
sources, emit the same photon flux (.mu.mol/(m.sup.2*s)) for
different unit areas of the light fixture. However, it is also
possible to occupy different emission regions with light sources in
such a way that certain photon fluxes arise, as will still be
discussed below.
[1737] It is also possible to use light sources whose radiation is
polarized. Here, the polarization can be the same or different for
all spectral regions. It is also possible to use polarized and
non-polarized light sources simultaneously or alternately in time.
The polarization can be stored in a so-called light recipe.
[1738] Light sources, or a combination of light sources, can emit
radiation whose spectra are matched in respect of direct light
and/or in respect of light reflected by objects. Furthermore, the
light sources can be adapted for water illumination.
[1739] [End of "Characteristics of Illumination for Light Recipes"
]
[1740] Light Recipes
[1741] Light recipes define illumination conditions. A light recipe
can be stored in program code and can be implemented by way of
computer-implemented software or a program, by way of a
user-defined or user-selected program code or by a sensor-triggered
signal. A light recipe can contain information items and executable
commands, which control the light wavelength, for example matched
to chlorophyll absorption curves, light intensity, including photon
flux, physical light properties such as polarization, focus and
coherence, photon flux conditions in certain wavelength regions,
for example the ratio of blue to red radiation, or blue to infrared
radiation (730 nm) or UV-B to red radiation or green radiation to
red radiation, durations of the on-times (illumination) and
off-times (no illumination), irradiation with light for measurement
purposes, such as, e.g., monochromatic laser radiation for
fluorescence measurements.
[1742] A light recipe can be adaptive, i.e., it can be part of a
regulating feedback loop that depends on external trigger
signals.
[1743] A light recipe can contain information items in relation to
activating and controlling light operating modes, such as, e.g.,
dimming, pulsation, pulse width modulation, light pattern,
increase, for example in the millisecond range, data production for
light-based communication, including the synchronization with other
illumination devices or agribusiness operating networks for energy,
material and waste management, or other agribusiness growing
sites.
[1744] A light recipe can be used for plant treatment and for
disinfection purposes.
[1745] A light recipe can contain information items regarding the
repulsion of insects by light properties and regarding light
properties for insect use, such as some wavelengths in the
ultraviolet region, regarding the component of light polarization,
for example the component of left-hand or right-hand circular
polarization, or regarding thermal radiation and the like.
[1746] A light recipe can contain information items about the
component of photosynthetically active radiation (PAR) or flux
density.
[1747] A light recipe can be part of a growth recipe, which can
contain information items about the overall energy consumption of
the activated or chosen light recipe in relation to the overall
illumination time duration or in relation to an energy equivalent,
such as the production of CO.sub.2, oxygen or methane gas, or said
light or growth recipe can be selected on the basis thereof.
[1748] A light recipe may contain information items about the
residual energy or an equivalent thereof, for example the amount of
light energy until harvest.
[1749] A light recipe can be selectable and allow producers or
customers to order a production at all times and make available the
necessary residual light data or the remaining light data.
[1750] A light recipe can be user-defined, i.e., interactive.
[1751] A light recipe can be certified; in particular, light
recipes can be established for breeding and/or growing and/or
raising or maturing medical plants, for example for obtaining
certain content concentrations or the like.
[1752] A light recipe can be sold or licensed as intellectual
property.
[1753] Light recipes can define the amount of illumination for
plant covers and plant interstices.
[1754] A light recipe can contain information items in respect of
the location and the form of an illumination device and can contain
instruction code to move a device into a specific position or
form.
[1755] A light recipe can be stored in an accessible database
system.
[1756] Light recipes can also be provided to include the actuation
of a combination of different light sources, such as, e.g.,
metal-halide lamps, sodium-vapor lamps, organic and inorganic
light-emitting diodes. Light recipes may contain an interaction
between different light sources.
[1757] Light recipes may contain the form and/or emission angle
and/or photon flux of an irradiation light fixture or a group of
irradiation light fixtures depending on a leaf area index and/or a
leaf area density.
[1758] Irradiation light, in particular ultraviolet light in the
UV-B range, i.e., 280-315 nm, and in the UV-C range, i.e., less
than 280 nm, can be used to reduce or even entirely avoid an onset
of disease in plants. Even a low photon flux of UV-B radiation
appears to have a positive influence on the plant's health.
[1759] Various light fixtures or light fixture groups can have the
same or different illumination scenarios. Various light fixtures or
light fixture groups can be operated with one or more light
scenarios (light recipes), which are interchanged cyclically or
according to a predetermined pattern or stochastically. Here, light
fixtures or light fixture groups can communicate with one another
and interchange data, for example via Bluetooth, WLAN, radio or via
a decentralized data network or a controller.
[1760] Plants can be illuminated from above, from below and/or from
the side, with the irradiation direction being able to be set
adaptively, for example depending on the plant growth or the degree
of maturity.
[1761] Artificially produced and natural light can be used together
or in alternation. By way of example, an irradiation using a
non-daylight-equivalent spectrum can follow a daylight-equivalent
spectrum in alternating fashion. An artificial spectrum can have a
circadian light spectrum and can be applied synchronously with the
solar altitude, or else with a time offset, or it is possible to
apply a circadian light spectrum with a multi-day rhythm. An
artificial spectrum can also reproduce the currently prevalent
conditions (clouds, rain, snow) by virtue of the current light
spectrum or the spectral intensity distribution thereof being
measured by way of an external measurement device and then being
stored and being provided to a control device, which sets the
artificial light source (plant illumination) accordingly such that
the current spectral conditions can be reproduced synchronously or
else with a time offset. A plant irradiation can also be
synchronized with external parameters, such as, e.g., music,
ambient noises, external wind speeds, rain, etc.
[1762] An irradiation sequence can be followed by a dark phase,
with relatively long dark phases leading to an accelerated length
growth of the plants.
[1763] By way of example, light recipes can be established
scientifically by way of trials, wherein the influencing factors,
such as, e.g., light spectrum, photon flux, photon density,
irradiation cycles, modes of operation, nutrients, pesticides,
ground properties, etc., are varied statistically and are then
evaluated when measuring the desired plant characteristics. This
can also be assisted by the use or implementation of deep learning
methods. Moreover, light recipes can be created or developed by
individual tests or test sequences and/or by direct simulation of
natural conditions, for example on the basis of sensor data
evaluations and the like.
[1764] [End of "Light Recipes" ]
[1765] Matching the Wavelength to Fields of Application
[1766] Here, the spectrum and, optionally, a dark phase of an
irradiation cycle can be matched to the photochemical properties of
a plant, for example to the absorption properties of chlorophyll or
vitamin C production. Furthermore, the spectrum and the irradiation
cycle can be matched to the photochemical properties of fertilizers
and pesticides. Furthermore, the spectrum and the irradiation cycle
can be matched to the photobiological properties of insects, bees,
etc., which contribute to the pollination of the plants. To this
end, the irradiation light can be polarized. Furthermore, the
irradiation light can intensify spectral regions in which the
photoreceptors of Hymenoptera, for example, are particularly
radiation sensitive, i.e., 340 nm, 430 nm and 535 nm, 600 nm, for
example, by radiation sources that emit narrowband or monochromatic
light, for example. Light recipes can take account of these
requirements and can actuate light sources accordingly for the
purposes of emitting predetermined wavelengths or wavelength
regions.
[1767] Natural light, for example directly from the sun, the sky or
the moon, has a high proportion of radiation with wavelengths of
less than 450 nm. By contrast, radiation reflected by natural
objects, such as from plants or the ground, for example, has a
large component of green and yellow light. Light recipes can take
account of these demands and can accordingly reproduce or simulate
direct and indirect radiation.
[1768] Infrared radiation can likewise be used for illuminating and
heating purposes. By way of example, ultraviolet light can be used
for short-term irradiation of plants, for a so-called irradiation
shower for the plants. This may bring about an increase in
resistance or may regulate growth. Such requirements can also be
taken into account by light recipes.
[1769] Such an illumination scenario or else light recipe may also
contain dark phases in which no visible light is emitted; however,
depending on requirements, ultraviolet radiation, in particular
UV-B, i.e., 280-315 nm, and/or red radiation and/or infrared
radiation are applied.
[1770] Irradiation may also be implemented with monochromatic
light, for example with narrowband laser radiation at 525 nm.
Alternatively, monochromatic radiation can be complemented by a
further irradiation component with a certain spectral width, for
example in the range of 605-645 nm.
[1771] Irradiation may contain radiation components that correspond
to the natural light such as light from the sun, the sky or the
moon, for example, said light having a large component of radiation
with wavelengths of less than 450 nm, and/or radiation components
that correspond to light reflected at natural objects, such as
leaves, the ground, etc., or at artificial objects, such as, e.g.,
walls or glass, etc. By contrast, radiation reflected by natural
objects, such as plants or the ground, has a large component of
green and yellow light. Light recipes can take account of these
requirements.
[1772] Irradiation may also be switched back-and-forth between the
two modes of irradiation; or certain regions are illuminated by one
radiation and other regions are illuminated by the other radiation.
Light recipes can take account of these requirements.
[1773] Water absorbs light particularly strongly in the red and
infrared spectral range. Therefore, light sources for water
illumination, for example for breeding and/or growing and/or
raising algae or fish, can be adapted accordingly to the
requirements, for example by virtue of having greater red and
infrared components, or by virtue of not emitting these spectral
regions at all, or only with a lower radiant flux, such that energy
can be saved. Light recipes can take account of these
requirements.
[1774] Irradiation can be switched back-and-forth between a
multiplicity of irradiation modes, or else said modes may be
operated together for simultaneous illumination, or certain
irradiation regions are illuminated by one radiation and other
regions are illuminated by the other radiation. Here, a
multiplicity of combinations are possible, in particular also
interval, modulation and pulsed operations. Light recipes can take
account of these requirements.
[1775] [End of "Matching the wavelength to fields of application"
]
[1776] Spectral Compositions
[1777] It is also possible to apply different spectral components
with a set or time-variable ratio, for example: blue (450 nm) to
red (680 nm) in a ratio of 7:1 to 1:7. These spectral ratios can be
applied alternately, for example with an interval of 5-15 minutes
or longer. Here, a spectral component can be operated with a
modulation, for example pulsed operation, PWM modulation or the
like. Additionally, both spectral components can be operated with
the same or different modulation. The modulation can be varied in
time and, within the scope of an illumination arrangement, in
space, in particular locally, as well. This mode of operation can
be applied within the scope of the interaction of various light
sources. Light recipes can take account of these requirements.
[1778] Other spectral ratios can be as follows: blue, in particular
with a wavelength of 460 nm--470 nm, with an irradiance
(.mu.mol/(m.sup.2*s)) of e.g. at most 6% to 8% of that in the
orange-red spectral range, i.e., 600-700 nm. Forming the ratio may
also include UV and IR light. Light recipes can take account of
these requirements.
[1779] Alternatively, other ratios are likewise possible. Thus, the
photon flux of red to green to blue can be: 0.68 to 0.44 to 1.0, or
as 9:0:1, or as 67:0:2, 92:0:16; 62:0:10; 56:11:5; 112:22:10. Light
recipes can take account of these requirements.
[1780] Other photon flux ratios can be: red to green to blue as
75-85% to 5-15% to 5-15%. The light spectra or the ratios of light
spectra also can be matched to the photoreceptor proteins, which
occur in plants, algae, bacteria, cyanobacteria and fungi. They
measure the ratio of light red to dark red light, for example the
ratio (photon flux) of red radiation at 660 nm and dark red
radiation at 730 nm, and control a broad spectrum of responses to
light stimuli, for example the turning of green of plant parts, the
shade avoidance in plants or the seed germination in plants. In
addition to cryptochromes and phototropins, they are the most
important class of photoreceptors. Light recipes can take account
of these requirements.
[1781] Specifically, the radiation ratio of red, i.e.,
approximately 660 nm, to dark red, i.e., approximately 730 nm, has
a great influence on the plant growth and the maturing process. For
plants, the red to dark-red radiation ratio is an indication for
the density of planting since dark red is reflected more strongly
by other plants and consequently increases the photon flux for
adjacent plants. A light recipe can update the red-to-dark red
ratio with increasing plant growth, for example in automated
fashion by way of a camera-based identification of the growth
stage. Light recipes can take account of these requirements.
[1782] The radiation ratio of UV-B (UVB) to the ratio of red (R) to
dark red (DR), i.e., UVB/(R/DR), is also an important regulating
factor for plant health. Light recipes can take account of these
requirements.
[1783] The photon flux ratios can also be related to surface
regions of a light fixture or a light fixture group, as already
discussed. Light recipes can take account of these
requirements.
[1784] Under the assumption that a product requires a certain
photon flux to reach maturity or obtain a desired maturity state
when considered independently of a cyclical application of the
light for simulating a circadian rhythm, determining the photon
flux up to a certain time of maturity can also determine the
further photon flux that is required until a desired maturity state
occurs. Thus, if the previous overall photon flux is known or
determinable, it is possible, according to the present disclosure,
to establish a photon flux for residual irradiation after delivery
of a plant and/or animal product.
[1785] Establishing the time duration of residual irradiation can
also be implemented taking account of the local natural
irradiation, for example taking account of the available or
predicted sunlight.
[1786] In particular, it is possible to establish the time duration
of residual irradiation taking account of the local irradiation
consisting of sunlight and/or artificial light sources. The use of
sensors that measure a photon flux can be particularly advantageous
here, as it is possible to acquire light of both natural and
artificial origin, if need be using various sensors. This can be
taken into account when determining residual irradiation.
[1787] [End of "Spectral Compositions" ]
[1788] Dependence on Leaf Area Parameters
[1789] The photon flux ratios can also be regulated according to
the so-called leaf area index (LAI) or green leaf area index
(GLAI), or according to the leaf area density (LAD). Both are
parameters for the planting density and can be considered,
accordingly, as leaf area per unit of ground surface (LAI, GLAI) or
leaf area per unit volume (LAD). By way of example, a coniferous
forest has an LAI value of 5; fields of maize have a value of
between 4 and 10. Since the LAI or LAD values change within the
scope of the growth stage, there is also change in the reflection
of light off leaves. Therefore, it is advantageous to regulate the
radiant flux or the photon flux of the plant illumination as a
function of the LAI or LAD values. Here, the relationship is
usually nonlinear and can follow a mathematical curve, for
example.
[1790] By way of example, the LAD values of magnolias change as
follows: 0.1 at 0.5 m growth height, 0.3 at 1 m, 0.4 at 3 m, 0.2 at
4 m, and less than 0.1 at 5 m. Light recipes can take account of
these requirements.
[1791] [End of "Spectral Compositions" ]
[1792] Irradiation Sequences
[1793] It is also possible to pass over light spectra in regions,
for example, an irradiation with blue light for a time duration of
a few milliseconds, seconds or minutes, then with the subsequent
spectral color, e.g., green in the region of 550 nm, wherein the
time interval can be the same or different, and then with the
subsequent spectral color, e.g., red with a wavelength in the
region of 600 nm, wherein the time interval can be the same as, or
different to, the preceding ones. The respective spectral regions
can be narrowband, i.e., have a small full width at half maximum of
a few nanometers. In some embodiments/implementations, radiation
has a full width at half maximum (FWHM) of at least 50 nm in the
spectral range of 600-700 nm; radiation in the spectral range of
440-500 nm has a full width at half maximum of at most 50 nm. Light
recipes can take account of these requirements.
[1794] When seen spectrally, the sequence of spectral regions can
run from shorter to longer wavelengths, or in reverse, with a
stochastic distribution or in random fashion. The sequence and
intensities, for example in respect of photon flux per spectral
range or wavelength and the like, can be made available within the
scope of a light recipe from a database.
[1795] [End of "Irradiation Sequences" ]
[1796] Further Irradiation Effects
[1797] It is also possible to irradiate plants with an irradiation
in the wavelength range of 400-700 nm and a photon flux of 40 to
2000 .mu.mol/(m.sup.2s) for 1 to 3 days during or after the growth
stage, or else in the mature state, in order to reduce the
concentration of nitrates in the plant, for example. This can
likewise be taken account of by light recipes.
[1798] Plants can be heated or cooled during the irradiation (see
also elements "Temperature Dependent Illumination" and "Temperature
Control"). Thus, it is also conceivable, in principle, to keep the
plants at a low temperature in a type of refrigerator and irradiate
them there with light.
[1799] [End of "Further Irradiation Effects" ]
[1800] Illumination/Imaging
[1801] Radiation that is effective from a photo-biological point of
view also can be replaced briefly by irradiation that is better
suited to recording an image, for example by means of a camera, a
spectroscope or the human eye, particularly when data that
characterize the quality are established. In particular, it is
possible to determine the exact location of a person in a plant
breeding and/or growing and/or raising facility by way of a sensor
acquire and modify the light in terms of its properties there in a
targeted manner, for example toward white light or light with a
higher color rendering index, or light without ultraviolet
radiation.
[1802] Furthermore, the aforementioned light sources and modes of
operation can also be used for illuminating plants that are used
for soil remediation. Here, soil remediation is understood to mean
that the plants remove unwanted constituents, often toxic
constituents, from the ground, i.e., take these up or influence the
latter via their roots. Furthermore, the aforementioned light
sources and modes of operation can also be used for illuminating
plants that are used for extracting chemical elements, for example
for obtaining rare earths, for example by growing Arabidopsis
halleri. The technology linked therewith is often referred to using
the following keywords: bio-augmentation as part of renaturation
ecology, phytoremediation, phytomining, phytoextraction,
rhizofiltration.
[1803] [End of "Illumination/Imaging" ]
[1804] Examples of Light Recipes
[1805] A light recipe for an irradiation device that determines or
takes account of the photon flux ratio of red (approximately 660
nm) to dark red (approximately 730 nm).
[1806] A light recipe for an irradiation device that determines or
takes account of the photon flux ratio of UV-B (280-315 nm) to red
(approximately 660 nm).
[1807] A light recipe for an irradiation device that determines or
takes account of the photon flux ratio of UV-B (280-315 nm) to dark
red (approximately 730 nm).
[1808] A light recipe for an irradiation device that determines or
takes account of the photon flux ratio of UV-C (200-280 nm) to red
(approximately 660 nm).
[1809] A light recipe for an irradiation device that determines or
takes account of the photon flux ratio of UV-C (200-280 nm) to dark
red (approximately 730 nm).
[1810] A light recipe for an irradiation device that determines or
takes account of the photon flux ratio of UV-B (280-315 nm) to the
photon flux ratio of red (approximately 660 nm) to dark red
(approximately 730 nm).
[1811] A light recipe that determines or takes account of the
photon flux ratio of UV-B (280-315 nm) to the photon flux ratio of
red (approximately 660 nm) to dark red (approximately 730 nm),
depending on the growth state and/or growth density of plants.
[1812] A light recipe which regulates the photon flux of a light
source in the UV-B range in such a way that this photon flux is
less than 5% of the overall photon flux in the ultraviolet emission
spectrum of a light source.
[1813] A light recipe which regulates the photon flux of a light
source during dark phases, during which no visible light is emitted
but during which ultraviolet radiation, in particular UV-B (280-315
nm), and/or red radiation and/or infrared radiation is applied if
required. That is to say, such ultraviolet radiation and/or red
radiation and/or infrared radiation may be appliable when
necessary.
[1814] A light recipe, which regulates the photon flux of a light
source depending on the leaf area index (LAI). Thus, light of a
certain wavelength can be supplied in augmented fashion such that
leaf growth is excited in order to accelerate a growth process, for
example. By way of example, this can be implemented by increasing a
component of red light or long-wavelength red light, which is also
referred to as far red.
[1815] A light recipe which regulates the photon flux of a light
source depending on the leaf area density (LAD). Depending on the
type and/or age of a plant, a LAD that is typical for the
respective development or growth stage may be stored in a database
for this purpose. As mentioned previously, the actual LAD can be
acquired or determined by appropriate sensors. Should there be
deviations between the actual LAD and the stored LAD, a control
unit can then increase the photon flux in order to cause increased
growth, or it can reduce the former.
[1816] [End of "Examples of Light Recipes" ]
[1817] Sensors
[1818] Plant germination, growth and maturity can be measured by
sensors or cameras, wherein different parameters can be measured
depending on plant and desired degree of ripeness, such as leaf
color, pigmentation, fluorescence, radiation absorption, vitamin C
content, nitrate content, rigidity, blossom, height and width of
the planting spacing and the ground porosity and humidity, for
example. Individual plants or groups of plants can be identified
and their growth can be measured using cameras or other imaging
methods such as radar, lidar or ultrasonic sensor systems, for
example. Using these measurement methods, the leaf area index or
the leaf area density can then be implemented and can then be used
as controlled variable, as will still be explained below.
[1819] In a development of the disclosure, provision can be made of
a spectroscope, in particular a spectroscope embodied to measure a
leaf color, pigmentation, radiation absorption, fluorescence, etc.
Moreover, provision can be made of at least one camera embodied to
measure a planting spacing, a blossom, a leaf density and the like.
Moreover, a breeding and/or growing and/or raising method according
to the disclosure may contain a step for determining a vitamin C
content, for example by way of titration. Moreover, the method
according to the disclosure may contain a step for determining the
plant porosity, for example by means of pulse thermography and
ultrasonic reflection measurement. An appropriate ultrasonic
measurement device can be provided in a development of the breeding
and/or growing and/or raising facility according to the disclosure.
In a further method step, a rigidity of the plants or of plant
parts can be acquired, for example by means of a pendulum
resistance measurement. Moreover, provision can be made of a photo
sensor such that a nitrate content can be measured in a method step
using a photo sensor by way of radiation absorption, in some
embodiments/implementations in the blue (400-500 nm) and red
(600-700 nm) wavelength range. Moreover, provision can be made of a
potentiometer, for example in order to carry out a ground moisture
measurement in a possible method step.
[1820] In general, one or more measuring devices can be provided
for acquiring plant-specific and/or environment-specific
parameters. It is also possible to provide one or more evaluation
devices for analyzing plant-specific and/or environment-specific
parameters, and one or more control devices for selecting and
implementing a light recipe that was selected on account of the
acquired and analyzed parameters.
[1821] [End of "Sensor" ]
[1822] Data Analysis and Database
[1823] Controlling Growth
[1824] These measurement variables can serve as controlled
variables for adapting the radiation or adapting the mode of
operation. Here, an image analysis may require downstream object
identification and possibly object classification. Different object
classes can be illuminated differently. Here, sensors and cameras
can be movable and travel along a planted area. Sensors can be
combined to form an interconnected system. The data can be
processed externally, for example by way of cloud computing. The
irradiation units (light fixtures) can also be grouped and combined
to form an interconnected system and, for example, be actuated in
decentralized fashion. Thus, even plant breeding and/or growing
and/or raising devices that are far apart can be matched to one
another, leading to uniform plant growth and quality. Thus, the
planted area is illuminated with the same light recipes, possibly
with a time offset where required, depending on the geographic
position.
[1825] [End of "Controlling Growth" ]
[1826] Database
[1827] Light recipes can be stored in a database and can be applied
according to need. Here, the suitable light recipe can be selected
manually. It is also conceivable for the light recipe to be
selected according to a set schedule. Moreover, it is conceivable
for the selection of the light recipe to be implemented in
automated fashion on account of measurement data and an evaluation
unit, which then applies a suitable irradiation scenario for a
certain amount of time. The selection can also be implemented in
semiautomatic fashion, for example by virtue of possible actions
being proposed on the basis of measurement data, empirical values
or a different input and a confirmation or selection being
implemented by a further entity, in particular a user.
[1828] A light spectrum can also be coupled to a further controlled
variable, for example irrigation, water atomization or ventilation.
The light or light scenario can moreover contain further control
commands, which then control further functions such as water
atomization, ventilation, fertilization and the like. Consequently,
a light spectrum or light recipe stored in a database may already
contain such additional control commands. Then, these can either be
applied or deactivated.
[1829] [End of "Database" ]
[1830] Fields of Application
[1831] Light spectrum or light recipe and further controlled
variables coupled thereto can be requested by a customer or by a
measurement system, inter alia within the scope of a licensing
model. Thus, e.g., for allocating access rights to a database or a
transfer platform, for example, a control device of a breeding
and/or growing and/or raising facility may obtain access to
alternative light recipes containing further functions, such as
recipes for pest control, increased growth, life-cycle assessments
and more.
[1832] A light recipe database can be provided by the operator of a
plant breeding and/or growing and/or raising facility, a research
institute or a user. It is also conceivable for customers to
provide a light recipe of a database that has been modified
according to their requirements or experience, possibly once again
within the scope of a licensing model.
[1833] Measurement data acquired by one or more sensors can be
supplied to an image-producing method and can be implemented, for
example, as a 2-D or 3-D model. Then, this can be provided to the
operator of a planting device or their customers, for example by
means of a display or AR glasses.
[1834] Neuronal networks connected to databases can record the
growth behavior under different illumination scenarios and can
identify optimal patterns and supply these to a control mechanism.
Furthermore, it is possible that extrapolation methods in respect
of the expected growth and maturity behavior of the plants are used
for applied light scenarios, said extrapolation methods pictorially
highlighting the predicted growth behavior to an operator or
customer or transferring the appropriate data to them.
[1835] [End of "FIELDS OF APPLICATION" ]
[1836] Urban Farming
[1837] With increasing growth of the Earth's population and
increased density in urban areas, food production in situ is
becoming very important. This is described, for example, using the
phrases urban farming or indoor farming, be this in buildings,
shopping malls or at home, for example in a kitchen. Such planting
methods can be incorporated in so-called smart city concepts. Here,
it is also conceivable that ever more production halls specifically
designed therefor, particularly production devices arranged
vertically in levels, often also referred to as vertical farming,
and skyscrapers that are also populated by humans, also referred to
as agritecture, are designed and built. Skyscrapers configured for
vertical growth may have different types of planting or animal
rearing on different levels.
[1838] [End of "Urban farming" ]
[1839] Cluster Farming
[1840] Naturally, small, portable or transportable planting devices
may also be used, in particular those that are able to be stacked
on one another, connected to one another or coupled with one
another. By way of example, electrical and/or mechanical or other
connections may be provided to this end. Here, information items
may be exchanged between individual units. By way of example, light
recipes and/or control commands of the illumination sources can be
transferred from one unit to another, or individual units could
take over the complete control for an entire group of units or
clusters in the style of a master-slave circuit. Alternatively,
such stackable planting devices can be controlled by an external
controller via data transfer, for example via WLAN, Bluetooth, etc.
To this end, each stacking unit has appropriate light sources,
alternative transmitter units, receiver, operating and/or control
devices.
[1841] According to one aspect of the present disclosure, a cluster
of irradiation devices, is provided, with the irradiation devices
being connected to form a data network. In a cluster of irradiation
devices, the light control thereof can be undertaken by local
control devices. Moreover, in a cluster of irradiation devices, the
light control thereof can be undertaken by one or more external
control devices.
[1842] Here, it should be noted that all illumination and
measurement scenarios described herein can also be used for, or are
appliable to, seeds and germ buds.
[1843] [End of "Cluster Farming" ]
[1844] Life-Cycle Assessment
[1845] Having an expedient life-cycle assessment is becoming ever
more important for food production. It is not only the light
sources that consume energy, but also the ventilation, watering,
heating or cooling, disposal and then also the sale and
distribution of the biomass that has arisen. The life-cycle
assessment can (and should) also include the workforce or the
production of harvesting robots.
[1846] Here, natural energy sources may be the following: The Sun
(solar energy), wind (wind turbines), water (hydroelectric power,
tidal power plants), geothermics, conversion of biomass and more.
All energy consuming variables should be acquired for the overall
life-cycle assessment, i.e., from the provision of the seed via
planting, fertilizing, watering, setting the temperature,
illumination, growth control, data acquisition and evaluation,
feedback devices, customer information and marketing, harvest,
waste disposal, cleaning, delivery and sale of the produced
biomass, and so on.
[1847] A vertical aquaponics device, in which for example
butterhead lettuce and tilapia fish are grown and raised, may have
an area of approximately 1000 m.sup.2, for example. The salads and
fish could be only illuminated at night, for example, when, as a
rule, energy is cheaper than during the day. In general, the
illumination can be planned in such a way that the costs for energy
are lowest, provided this is compatible with the requirements of
the plants and animals. The irradiated power per m.sup.2 for
raising tilapia can be 400 W, for example. In the case of an
irradiation duration of 4 hours per day, this results in an energy
consumption of approximately 50 000 kWh per month. Accordingly, the
energy requirement for larger breeding and/or growing and/or
raising devices can be significantly higher. Therefore, a reduction
in the energy costs is desirable. To this end, efficient LED light
fixtures, for example, can be used for illumination purposes.
Moreover, it is possible to create or use light recipes that are
designed for low energy consumption.
[1848] Another aspect of "Eco Certificates" also relates to a
method for determining a light recipe of a breeding and/or growing
and/or raising facility taking account of ecological boundary
conditions, a method for determining a light recipe of a breeding
and/or growing and/or raising facility taking account of an energy
consumption resulting therefrom, and a method for determining the
entire photon flux of such a light recipe of a breeding and/or
growing and/of raising facility. By way of example, sensors for
acquiring an overall photon flux, i.e., photon flux caused by
artificial and natural illumination, can be used for determining a
photon flux. It is also conceivable for the photon flux of the
light source to be determinable directly by the actuation of the
light source on account of knowledge about the employed artificial
light sources and that use is made of sensors that only acquire
light of a natural origin. Moreover, mixed forms are conceivable.
In this way, there can be open-loop or closed-loop control of the
photon flux and further factors relevant to the illumination.
[1849] By way of example, such methods can be defined by trials on
the basis of the evaluation of results. Since a result could be
influenced by a very subjective impression of users, it is
therefore also conceivable for the creation or definition of new
methods or light recipes to be implemented by means of an
intelligent computer control or a learning or self-learning
software or database. By way of example, ecological boundary
conditions, such as energy consumption, use of specific wavelengths
for treating the products, irradiation durations, etc., can be
predetermined; these are also relevant in a so-called life-cycle
assessment. The goal of such a method for creating or determining a
light recipe for a breeding and/or growing and/or raising facility
may then be to obtain a predetermined maturity state, nutrient
content, health state and the like without departing from the
ecological boundary conditions. It is conceivable for one or more
sensors to acquire this growth process or individual parameters and
for an automatic or manual adaptation of the illumination to be
implemented in order to maximize the result. After running through
at least one, probably several, growth loops, a light recipe may
then be created, said light recipe developing an optimized result
within the boundary conditions set. Naturally, it is likewise
conceivable for such a learning or self-learning system to have
further optimization requirements, even beyond the creation of such
a light recipe. Thus, it is also conceivable for parameters from
alternative light recipes or light recipes for alternative types of
product to be applied. In this way, it is also possible to identify
synergies, for example by combining certain types of plants within
the same growing region. This may be accompanied by a further
increase in yield.
[1850] Similarly, it is possible to determine a light recipe for a
breeding and/or growing and/or raising facility taking account of
an energy consumption arising therefrom. Thus, an energy balance
can be created for each employed light fixture or each light module
of an illumination device. This may be implemented on the basis of
data sheets, which are stored in a database, with an energy
consumption specified in the data sheet underlying the creation of
the energy balance. Moreover, it is conceivable for a power meter
or other sensors or detectors to acquire the energy supplied for
illuminating the plants.
[1851] As an alternative or in addition thereto, it is also
conceivable for the photon flux reaching the plants to be measured
exactly with the aid of sensors, independently of the employed
light source. Here, the sensor or sensors can have a
wavelength-dependent embodiment, and so a sensor is only sensitive
to a certain wavelength range, while other wavelength ranges are
covered by one or more other sensors.
[1852] A 59-story so-called sky farm--in this case, this means a
vertical farm for salad, carrots, spinach, soybeans, pepper, wheat,
potatoes, cucumbers and other products--designed by Gordon Graff
would require an illumination energy requirement of a total of 82
million kWh per year, for example.
[1853] A life-cycle assessment can be created for each included
product, such as water, fertilizer, seed transport, current,
heating etc. By way of example, this can be implemented in the form
of a CO.sub.2 certificate. A life-cycle assessment can also be
created for the illumination of the plants. Moreover, a life-cycle
assessment could be made in each case for the costs relating to
control, sensor systems, evaluation, light control, data provision,
data evaluation, data presentation, etc. Then, this life-cycle
assessment can relate to the biomass produced.
[1854] The included measurement variables can be related to the
overall energy outlay in this case, including consumption outlay of
a plant breeding and/or growing and/or raising facility, for
example converted into energy costs or an energy equivalent, such
as the CO.sub.2 production, connected therewith, of the energy
sources available in the plant breeding and/or growing and/or
raising facility, or the use thereof. The energy or consumption
outlay can contain the actual costs of the facility, such as house,
devices, repairs and maintenance, for example, possibly reduced by
amortization costs, etc., and, in particular, the running energy
costs: power, water, illumination, climate control,
dehumidification, nutrients, pollination, herbicides, care,
control, harvesting, and also storage, packaging, sale including
transport costs, communication, data acquisition, data analysis,
data storage, waste disposal and recycling, etc. Here, both
renewable and non-renewable sources of energy should be taken into
account. Energy recuperation, for example by biomass, can be taken
into account as a positive balance. The special energy variables
for breeding fishes, such as water cleaning, specialist feed,
medical checks and the like, should likewise be taken into account
for aquaponics devices.
[1855] An aspect of "Eco Certificates" thus also relates to a
method for determining a life-cycle assessment resulting from the
energy consumption of a breeding and/or growing and/or raising
illumination, a method for determining a life-cycle assessment
resulting from the energy consumption of a plant illumination and
the entire energy consumption and/or CO.sub.2 equivalent of a
breeding and/or growing and/or raising facility, and a method for
indicating/displaying such a life-cycle assessment. In addition to
the information items that are known or supplied from the included
products in respect of the life-cycle assessment thereof, or that
are able to be taken into account in any other way, the values
according to the illumination can be used directly for calculating
and updating the life-cycle assessment. Here, it is conceivable
that the information items relating to the amount of energy
consumed for illumination purposes are obtained directly from the
employed light recipes, are combined in appropriate data packages
and are stored in corresponding databases. Moreover, it is
conceivable for sensors arranged between the plants or animals to
be used in order to obtain an independent source of information and
in order to be able to better key the energy assessment in spatial
terms. Moreover, this could also implement an acquisition to the
effect of which components of light from different spectra in the
acquisition region of a sensor were used for these wavelengths and
for what duration this was the case. Such sensors could also be
used, for example, for fishes in aquaponics devices, for instance
by direct application to the skin.
[1856] According to "Eco Certificates", it is possible to acquire
the entire life-cycle assessment of a sold product. This life-cycle
assessment can then be made available to an operator and a
customer. By way of example, the information can be provided in
situ or by way of the Internet. This can allow a customer to make a
decision to buy based on, for example, an energy requirement during
production, i.e., based on whether or not these are energy-friendly
products. Additionally, a customer is put into a position where
they can prescribe a life-cycle assessment as an additional order
or purchase decision for the operator. Thus, a customer can
prescribe a life-cycle assessment upper limit, or a bandwidth
within which the product has to be produced. By way of example,
trade may occur on a transfer platform, as is yet to be described
below.
[1857] Here, operators can also exchange or sell ecological
certificates, with it then being possible to present an overall
life-cycle assessment for an operator, for example a chain store.
In this way, a user or consumer or customers can be provided with
additional information items in respect of a life-cycle assessment
and, provided this is desirable, the latter can form a further
basis of negotiations or commercial transactions. By way of
example, such ecological certificates can be exchanged on a
transfer platform, as described below. Trading of ecological
certificates can be implemented in a manner corresponding to the
trade of emission rights, for example, or may be subject to legal
regulation.
[1858] A life-cycle assessment can also be provided for light
recipes. Said life-cycle assessments can then likewise be provided
to the operator or customer for the selection of a suitable
illumination scenario.
[1859] Thus, the disclosure also relates to a method for
interactive and/or automated determination or development of a
light recipe for a breeding and/or growing and/or raising facility
with acquisition of a life-cycle assessment, a method for applying
such a light recipe for a breeding and/or growing and/or raising
facility and a method for changing from light recipes with a poorer
ecological assessment to light recipes with a better ecological
assessment. This can be implemented on a platform configured to
this end, said platform being accessible by customers, operators or
other users. All available light recipes, or the light recipes made
available, can be stored here with data or information items in
respect of a life-cycle assessment or can be labeled here by
certificates which are granted on the basis of a grouping in
different life-cycle assessments or life-cycle assessment groups.
It is conceivable that an assignment of the life-cycle assessment
moreover includes further influencing factors. An assignment of a
life-cycle assessment can be implemented manually, automatically or
semi-automatically. The light recipes can be displayed to a user on
a display apparatus or can be read from a database and output as
output data upon request, for example by way of an input means.
[1860] Consequently, customers are able to buy plants that have
achieved or else fallen within a predetermined life-cycle
assessment. The customer can then either consume said products in
said state or subsequently expose them to a natural light source,
in particular the sun, for subsequent irradiation. Here, it is
possible to communicate the necessary residual irradiation duration
to the customer. Consequently, it is possible to satisfy
ecologically oriented customer needs. By displaying a life-cycle
assessment, a customer or consumer is consequently put into a
position of being able to select a product from a first producer
H1, which was produced with a first life-cycle assessment 1, or the
same product from a second producer H2, which was produced with a
second life-cycle assessment 2.
[1861] Also, it is possible that the customers are automatically
informed if growing products or growing products selected by the
customer have reached a certain maturity state, vitamin content,
for example of vitamin C, or a certain amount of plant
constituents, nutrients or minerals, or have satisfied a
predetermined life-cycle assessment, and can be collected or
shipped.
[1862] Further, an operator or customer is able to change from a
light recipe with a poorer ecological assessment to a light recipe
with a better ecological assessment. Such light recipes can be
revealed in a database or offered to the operator or customer.
[1863] A further aspect of "Eco Certificates" relates to a method
for applying such a light recipe in a breeding and/or growing
and/or raising facility.
[1864] According to one aspect of "Eco Certificates", consumers or
operators of a breeding and/or growing and/or raising facility can
thus be provided with a life-cycle assessment established using the
methods described herein.
[1865] Moreover, one aspect of "Eco Certificates" relates to a
method for ordering plant and/or animal products, which contains a
step for observing an established life-cycle assessment. In this
way, it may be possible to use a further reliable information item,
in respect of the life-cycle assessment in this case, within the
scope of a purchasing decision.
[1866] Furthermore, an aspect of "Eco Certificates" relates to a
method for an automated order or offer for a plant and/or animal
product, triggered by a certain plant growth and/or a degree of
maturity and/or a nutrient content and/or mineral content being
reached. In addition, or as an alternative thereto, such a method
can contain a step for an automated order or offer of a plant
and/or animal product, triggered by a predetermined life-cycle
assessment being achieved. What this can facilitate is that an
order can be matched exactly to the customer's wishes. In
particular, this can facilitate bringing about a certain degree of
maturity, for example a certain vitamin content being obtained,
without the rest of the plant having to be matured completely.
Thus, maturing times can be optimized according to purpose.
[1867] An automated ordering process depending on one or more
maturity states being reached can moreover be advantageous to the
extent that there can be better planning for demand and no, or
less, storage and warehousing time is necessary. This can reduce
product decay on account of storage and the like. In a case where a
certain life-cycle assessment being reached, i.e., an energy outlay
for maturing the product in this case, triggers harvest and further
processing, and not a maturity state, it is possible, in
particular, to supply an information item with the products to be
processed further, said information item stating whether or for how
long further maturing is necessary, for example under natural
conditions and light, in order to obtain a predetermined maturity
state.
[1868] Naturally, it may require scientific examinations to analyze
the advantages of a certain plant maturity or a nutritional value
or a chemically effective plant constituent and be able to market
this in view of customer requirements. By way of feedback in
respect of their own experiences, the taste of the plants, the
storability and the like, customers can actively be included in the
design of light recipes that take account of a life-cycle
assessment.
[1869] [End of "Life-Cycle Assessment" ]
[1870] Database
[1871] An aspect of "Eco Certificate" moreover relates to a method
for interactively establishing light recipes. To this end, a
database can be provided in order to store various data of one or
more light recipes. A further aspect of the present disclosure also
relates to a method for establishing a life-cycle assessment for
such interactive light recipes. Here, interactive means influenced
by current measurements, for example a pest infestation, problems
when breeding and/or growing and/or raising plants or animals, or
the like, or a customer can modify a selected light recipe, and
consequently a life-cycle assessment, for example. By way of
example, the life-cycle assessment can be determined by virtue of
the information items about the energy consumption or the overall
energy consumption, etc., that are available or establishable in
relation to the light recipes, but also in relation to further
growth parameters, such as watering, temperature, etc., being
processed or calculated depending on the respectively set growth
parameters.
[1872] Here, the data may include information items in relation to
the illumination per se, such as intensity, duration of the on/off
cycles, spectral composition of the light, etc., but also
information items in relation to origin or amount of the employed
energy, residual illumination durations, further environmental
conditions such as humidity, temperature, etc., and the like. Such
a database can be stored on a local data storage medium, a server,
or at a non-local storage location or decentralized storage
location. The database may be connected to an illumination device
or control device of the illumination device such that data from
the database can be considered for direct use during the
illumination. Here, access to the database can be restricted by
means of an access control. Thus, depending on access status,
selected users may be provided on the database with read
authorization, write authorization or read and write authorization.
As a result of read authorization, the data stored in the database
can be read, and so the light recipes stored therein and the
additional information items can be made available to a user. With
write authorization, in particular, a user can be allowed to store
own light recipes, which are made available to them or, optionally,
to further users as well, or else to modify existing light recipes
or adapt these to special conditions. An optimization of the result
can be achieved in this interactive manner for creating light
recipes or modifying existing light recipes.
[1873] Such a database can be configured to be reachable by the
user or users or operators by way of a network connection, a
wireless network connection, a telecommunications connection or by
way of other communication paths. To this end, the database or a
data storage medium containing the database may be provided in a
computing device, in particular a computer. The computing device
may have communication means in this case, such as a network
device, a transmitter device and/or a receiver device. A user and
operator of the database can obtain access, even remote access, to
the database by means of a further transmitter and/or receiver
device. Here, the second transmitter and/or receiver device can be
a computing device or else a mobile terminal. Here, all devices
that are equipped with a communications interface and that need not
be operated locally are considered to be mobile terminals, such as,
for example, cellular telephones, portable computers such as
laptops or tablets, and also smart watches, AR glasses or VR
glasses, and the like.
[1874] [End of "Database" ]
[1875] Transfer Platform
[1876] Such a database can be part of a transfer platform. In
principle, such a platform can be provided for all aspects
connected with an addition of value to be offered, sold, purchased,
exchanged or modified. Primarily, this relates to products such as
plants and/or animals. Thus, a plant product can be ordered by way
of the platform in such a way that, for example, a certain amount
in a predetermined maturity state is provided for delivery or
collection at a certain time.
[1877] Furthermore, it is conceivable for certain light recipes,
which improve or optimize various aspects of the production, for
example, to be traded. By way of example, these light recipes can
be made available to users, for example as downloadable databases,
as locally executable programs or else as programs that are
executable via the network. In particular, it is conceivable that
an execution of the programs or an application of the light recipes
is facilitated within the scope of so-called apps for mobile
devices. As already mentioned, the mobile device or any other
computing device can serve for implementation purposes, but also
merely for display, selection, control or other maintenance or
remote maintenance purposes, with the controlling program in fact
being executed on a platform that is independent of the computing
device or on an independent computer, which is indirectly or
directly connected to a breeding and/or growing and/or raising
facility.
[1878] Incidentally, as already mentioned, it is possible for
so-called life-cycle assessments to be linked to the products or
for the products to be labeled using such life-cycle assessments.
Since a life-cycle assessment according to the present disclosure
is primarily designed to document the resources or energy used for
production and to present this transparently, an ecological
certificate can be issued for a complete batch that was produced
using a predetermined light recipe, for example. A transfer
platform according to the present disclosure could also represent a
platform embodied for trade with such ecological certificates.
Moreover, it is conceivable to label non-modified light recipes
with ecological certificates such that the products produced using
such a light recipe accordingly fall under this certificate.
[1879] [End of "Transfer Platform" ]
[1880] Further Aspects
[1881] According to a further aspect of "Eco Certificates", a
method is provided, said method creating or establishing a
life-cycle assessment of a light recipe, in particular of an
interactive light recipe. At least one computing device is
connected to a data source for the purposes of creating such a
life-cycle assessment on the basis of a light recipe, in particular
an interactive light recipe. The data source may be a database, for
example a database as described above, one or more sensors, a
manual user input, an output of one or more further computing
devices or the like, or a mixture of the aforementioned sources.
Depending on what information items should be included in the
life-cycle assessment, it is possible to evaluate the data of a
light recipe, in particular in respect of an illumination duration,
illuminance, spectral composition, etc., the energy footprint of
which is directly determinable depending on the employed light
modules and the like. In similar fashion, this can be established
for interactive light recipes by analyzing the employed light
modules and the applied illumination parameters. To this end, a
so-called look-up table could be stored in a database or in one of
the remaining data sources or in a local storage device of the
computing device, for example, said lookup table presenting a
simple correlation between light module, lighting parameter and
energy consumption. By way of example, light modules of third-party
suppliers may also be included in such a system for light planning
purposes. In order to create a life-cycle assessment, it is also
conceivable for only the photon flux or the previous overall photon
flux to be taken into account, and not all secondary energy
consumers.
[1882] Further influencing factors, which should be taken into
account in a life-cycle assessment, can be taken into account in a
similar fashion, optionally by way of external data sources. The
various data or data packets can be combined and evaluated in the
computer unit such that an overall energy consumption or another
selected variable, the information of which is made available, is
evaluated. A life-cycle assessment created thus, for example over a
life-cycle of a product, can then be output on an output device.
Once again, the output device can either be a local unit or a
mobile unit, as already described above.
[1883] A further aspect of "Eco Certificates" relates to a method
for exchanging light recipes. Here, a user or operator may have
selected a certain light recipe, which is used for illumination
purposes. Here, additional or other light recipes may be stored in
a database, for example a database as described above, said
additional or other light recipes either being optimized for the
envisaged use or having special properties or merely being intended
as alternative recipes which, for example, have different
life-cycle assessments, different durations to maturity or the
like. Access to the database may allow the computing device for
controlling the breeding and/or growing and/or raising facility to
replace an active light recipe with another light recipe that is
stored in the database. By way of example, factors relating to the
exchange of a light recipe could be the presence of an
extraordinary situation, for example the occurrence of diseases or
pests, which can be fought by means of specific light recipes, or
else a requirement to slow down or accelerate the maturing process.
The method for exchanging a light recipe may also be implemented,
in particular, on the basis of sensor data that monitor parameters
of the plant growth, or on the basis of a user request or a user
specification. Such a method for exchanging a light recipe may thus
include the steps of: acquiring a data input, for example from
sensor data or a user request, possibly acquiring or analyzing the
present light recipe in respect of the data input, selecting a
predetermined light recipe or a light recipe appropriate for the
data, deactivating the current light recipe provided a light recipe
is selected and active, and activating a light recipe or the new
light recipe.
[1884] [End of "Further Aspects" ]
[1885] Data Storage Medium
[1886] A further aspect of the disclosure relates to a data storage
medium. The data storage medium contains a control program for
carrying out a method for operating a breeding and/or growing
and/or raising facility as described herein.
[1887] In particular, a data storage medium may contain at least
one database. Here, the database may have light recipes and/or
life-cycle assessments of a breeding and/or growing and/or raising
facility, illumination device, light source, etc., and/or data in
respect of requirements of the products to be produced in respect
of growth, state of health, contents or the like.
[1888] [End of "Data Storage Medium" ]
[1889] Irradiation Unit
[1890] A further aspect of the present disclosure relates to an
irradiation device. In particular, the irradiation device can be
connected to a control device. By way of example, the control
device can be part of a computer or can be embodied downstream of a
computing device.
[1891] The irradiation device can be embodied to emit an
irradiation light, the light properties of which are regulated by
one or more light recipes.
[1892] The irradiation device can be embodied to emit a light
spectrum, the photon fluxes per spectral region of which are
regulated by one or more light recipes.
[1893] The irradiation device can be embodied to emit a light
spectrum, the photon fluxes per spectral region and spatial
emission of which are regulated by one or more light recipes.
[1894] The irradiation unit according to one aspect of the present
disclosure can also be embodied as a mobile irradiation device.
Here, this mobile irradiation unit can be embodied to carry out at
least one of the methods described herein. By way of example,
mobile irradiation devices can be: trucks, trains, ships,
spaceships or space stations, shopping carts, mobile household
devices and the like.
[1895] A further aspect of the present disclosure relates to an
irradiation device, the form and/or emission angle and/or photon
flux of which is defined depending on a leaf area index and/or the
leaf area density.
[1896] Two or more such irradiation devices can also be combined to
form a cluster, wherein the light control thereof is undertaken by
an external control device. It is moreover conceivable for a
control device to be provided for each cluster element, wherein the
individual control devices are actuated by one or more computer
units.
[1897] [End of "Irradiation Unit" ]
[1898] Agricultural Facility
[1899] An agricultural facility, i.e. a breeding and/or growing
and/or raising facility for plants or animals according to the
present disclosure may comprise at least one illumination device,
which is also referred to as irradiation unit. An illumination
device, in turn, has at least one light source provided for
illumination purposes. In some embodiments/implementations, an
illumination device has a multiplicity of light sources. Here, the
light sources can be actuatable individually, in groups or
together. Here, the light sources can emit spectra that deviate
from one another. Individual light sources or groups of light
sources can be embodied here for the purposes of emitting
individual wavelengths or narrow wavelength ranges. Other light
sources or groups of light sources can emit a broadband spectrum or
emit light with a predetermined or adjustable color
temperature.
[1900] Moreover, an agricultural facility may have a control unit.
The control unit can have an input device, a computing device and
an output device. Here, the control unit is embodied to control the
facility or at least part of the facility, in particular an
illumination device, but also further components such as, for
example, at least one watering system, at least one ventilation
system, at least one climate-control system, a sensor system
arrangement, writing data to, and reading data from, databases, and
the like.
[1901] Moreover, an agricultural facility according to the present
disclosure may also have a multiplicity of illumination
devices.
[1902] [End of "Irradiation Unit" ]
[1903] Building
[1904] A further aspect of the present disclosure relates to a
building configured for agricultural management, e.g. for vertical
farming or any other form of controlled environmental agriculture,
a greenhouse, etc. This means that a building according to the
disclosure is configured to breed and/or grow and/or raise plants
and/or animals on one or more levels, e.g. stories, of the building
and, by way of at least partly artificial illumination in
particular, develop growth or maturing conditions which mimic
natural light, which are improved or optimized in relation to
natural illumination or which influence a growth or maturing
process of products in any other way. Such a building can be part
of a breeding and/or growing and/or raising facility according to
the disclosure. Conversely, it is also conceivable for a breeding
and/or growing and/or raising facility to be part of such a
building such that, where applicable, only parts of the building
are assigned to a breeding and/or growing and/or raising facility.
A control unit can be provided in the building or in the breeding
and/or growing and/or raising facility, said control unit
controlling the breeding and/or growing and/or raising facility or
at least part of the breeding and/or growing and/or raising
facility or the building or at least one part of the building.
[1905] [End of "Building" ]
[1906] "Medical Certificates"
[1907] According to the element "Medical Certificates", a method
for agricultural management, in other words a method for managing
an agricultural facility, is proposed, wherein the breeding and/or
growing and/or raising of a product is adapted to a specific use of
the product. Particularly, growth parameters of medically active
plants may be adapted to a planned medical use.
[1908] The method may comprise medically active plants grown with a
specified growth process resulting in a specified content of
medically active agents.
[1909] The method may comprise improved definitions or
documentations of the growth process of the plants.
[1910] A multiplicity of irradiation variants and illumination
controls for growing and/or breeding plants are highlighted, as are
the methods enabling this and the corresponding breeding and/or
growing facilities.
[1911] The following list specifies some paragraphs of "Eco
Certificate", which are also relevant for "Medical Certificate",
because, for example, a customer of medical products may also want
to order a product on its ecological footprint. Furthermore, these
paragraphs may be of general relevance to the disclosure. To avoid
duplication of large text parts, these paragraphs are incorporated
here by reference, and again cited in the following description at
appropriate text passages to facilitate the comprehension of
"Medical Certificate" without lengthy repetition of
description.
[1912] Light Sources [1913] Characteristics of Light Sources [1914]
Operating Mode of Light Sources [1915] Parameters of Light
Sources/Sensors
[1916] Plant
[1917] Characteristics of Illumination for Light Recipes
[1918] Matching the wavelength to fields of application
[1919] Spectral compositions
[1920] Irradiation sequences
[1921] Further irradiation effects
[1922] Illumination/Imaging
[1923] Examples of light recipes
[1924] Sensors
[1925] Data analysis and database [1926] Controlling Growth [1927]
Database
[1928] Fields of Application
[1929] Urban farming
[1930] Cluster farming
[1931] Life-Cycle Assessment [1932] Database [1933] Transfer
platform [1934] Further aspects
[1935] Data storage medium
[1936] Irradiation unit
[1937] Agricultural facility
[1938] Building
[1939] 1.sup.st aspect of "Medical Certificates": A method for
agricultural management, particularly for operating a plant
breeding, growing, cultivating and harvesting facility, in
particular a breeding and/or growing and/or raising facility for
plants and/or animals (agricultural facility), comprising the steps
of: inputting input data from an input device into a computing
device, processing the input data in the computing device and
outputting output data from the computing device to an output
device, wherein the output data contain at least information items
in relation to a degree of maturity of a breeding and/or growing
and/or raising product, an active agent content and/or an active
agent concentration of at least one active ingredient in the
breeding and/or growing and/or raising product.
[1940] Here, in particular, the input data can contain measured
values of plants that allow a determination of active agents,
active agent content and/or active agent concentration or that
directly contain these values.
[1941] 2.sup.nd aspect of "Medical Certificates": The method for
agricultural management according to the 1.sup.st aspect of
"Medical Certificates", wherein, in one method step, the output
data for controlling the breeding and/or growing and/or raising
facility are input into a control device, wherein, in particular,
the control unit also may comprise the input device, the computing
device and/or the output device.
[1942] 3.sup.rd aspect of "Medical Certificates": The method for
agricultural management according to the 2.sup.nd aspect of
"Medical Certificates", wherein a control by the control device is
modified on the basis of the output data in such a way that an
active agent concentration of an active ingredient in the breeding
and/or growing and/or raising product lies within a predetermined
range or does not exceed or drop below a pre-determinable limit of
an active agent content.
[1943] Such limits may be prescribed on the basis of medical data,
legal requirements, requirements from certifications and the like.
Here, it is conceivable for corresponding institutions or
establishments that predetermine such limits make available
databases that are made available by way of access, for example by
means of a remote access method. In this way, these data can be
taken into account in a breeding and/or growing and/or raising
method and, in particular, can also be taken into account
automatically. Here, in the present case, a "breeding and/or
growing and/or raising product" should comprise plants and/or
animals that are raised or grown, at least in part or at least
intermittently, by means of a breeding and/or growing and/or
raising method as described here.
[1944] 4.sup.th aspect of "Medical Certificates": The method for
agricultural management according to any one of the 1.sup.st to
3.sup.rd aspect of "Medical Certificates", wherein the method
includes a step in which the computing device calculates and/or
selects a light recipe in order to obtain a predefined effect, in
some embodiments/implementations by inputting defined boundary
conditions, in particular in order to obtain a predetermined active
agent content or a pre-determinable active agent concentration.
[1945] In this way, determining the light recipe that accordingly
fits best to the circumstances can be implemented, wherein, in this
case, it is also possible to include factors such as future
maturing times, development of active agents and plant growth and
the like in the assessment of the light recipe selection in order
to facilitate a better prediction and an improved load of the
breeding and/or growing and/or raising facility.
[1946] 5.sup.th aspect of "Medical Certificates": The method for
agricultural management according to any one of the 1.sup.st to
4.sup.th aspect of "Medical Certificates", wherein the method
includes a step for determining an active agent content resulting
from a sensor-based acquisition of a breeding and/or growing and/or
raising product and evaluation of the acquired data.
[1947] These sensor data can be input into the control device as
input data.
[1948] 6.sup.th aspect of "Medical Certificates": The method for
agricultural management according to any one of the 1.sup.st to
5.sup.th aspect of "Medical Certificates", wherein a light recipe
is established by a control device, wherein the step for
establishing the light recipe at least includes the evaluation of a
current degree of maturity or an active agent content of a breeding
and/or growing and/or raising product.
[1949] Here, the light recipe can be determined in such a way that
a target active agent content or target range of the active agent
content or the active agent concentration is reached in the
breeding and/or growing and/or raising product or can be expected
at the end of the breeding and/or growing and/or raising stage in
accordance with the chosen light recipe.
[1950] 7.sup.th aspect of "Medical Certificates": The method for
agricultural management according to any one of the 1.sup.st to
6.sup.th aspect of "Medical Certificates", wherein the data in
respect of a maturing process and/or an active agent content and/or
a health state and the like are, in one method step, output on a
display apparatus and/or stored in a database such that the data
are provided to a user, operator and/or customer.
[1951] This allows a user to track or else document the breeding
and/or growing and/or raising process. This can also allow
parameters during the breeding and/or growing and/or raising to be
controlled or adapted manually on the basis of the displayed output
data. Here, the display apparatus can be a local or a non-local
display apparatus. In particular, the display apparatus can also be
an appliance that is connected via a telephone network, radio
network, LAN or similar network, such as, for example, a tablet
computer, a cellular telephone or the like. Moreover, the display
apparatus can be part of a computer, either locally or at a
distance (remote client). It is likewise conceivable for the
display apparatus to be a display apparatus of any unit connected,
for example, via a network such as LAN, W-LAN, Internet, etc., said
unit also being able to be configured for data output only.
[1952] 8.sup.th aspect of "Medical Certificates": The method for
agricultural management according to any one of the 1.sup.st to
7.sup.th aspect of "Medical Certificates", wherein the method
includes a step for processing an order of at least one product
produced in the breeding and/or growing and/or raising facility,
wherein a control device has at least one input means with a
communications unit such that a data input, in particular an
indication of demand, from an external interface is assignable to a
production or planned production in the control device.
[1953] In particular, an ordering platform can be directly or
indirectly coupled to a control device of the breeding and/or
growing and/or raising facility and so a need can be acquired
directly on the basis of incoming or pending orders and can be
taken into account in controlling and organizing the breeding
and/or growing and/or raising facility. Thus, for example, sowing
can be actuated, in particular by a sowing apparatus or sowing
robot, in order to sow a desired product in order to service an
increased demand that cannot be covered by existing growing
products.
[1954] In respect of medical plants, in particular, this can allow
various orders of one or more users to be bundled, particularly if
this relates to small amounts, and thus allow logistical outlay to
be reduced. Moreover, it is possible to conserve resources if
products with the same or similar requirements in relation to the
environmental conditions are processed together.
[1955] 9.sup.th aspect of "Medical Certificates": The method for
agricultural management according to any one of the 1.sup.st to
8.sup.th aspect of "Medical Certificates", wherein the external
interface can have an input terminal, wherein the input terminal is
embodied in such a way that a user and/or a machine and/or program
code can input an indication of demand in respect of one or more
products to be produced in the breeding and/or growing and/or
raising facility at the input terminal.
[1956] In this way, a need can be planned more precisely and
overproduction can be avoided. Moreover, a completion of the
production can be matched to the demand, and so storage times, and
losses and reductions in quality caused thereby, may be
reduced.
[1957] Inputting an indication of demand for ordering plant and/or
animal products can include a step for evaluating and/or monitoring
an active agent content of the products. Alternatively, this can be
a step for evaluating and/or monitoring an active agent
concentration, for instance in certain plant parts, or the like.
Here, an indication of demand can be an order or merely the
announcement of a demand in future, for example in order to plan a
corresponding utilization of the breeding and/or growing and/or
raising facility in timely fashion. Particularly in cases in which
the use of alternative light recipes for treatment purposes is
necessary owing to unforeseen events, such as pest infestation or
disease, it is possible to better ensure the observance of placed
boundary conditions. By way of example, such boundary conditions
may emerge from legal limits for plant contents or from
certification specifications. However, these may also arise on
account of other specifications, such as, for example, medical
recipes or formulations, for reasons of research or for test
purposes.
[1958] 10.sup.th aspect of "Medical Certificates": The method for
agricultural management according to the 8.sup.th or 9.sup.th
aspect of "Medical Certificates", wherein the input of an
indication of demand for ordering plant and/or animal products
includes a step for evaluating and/or monitoring an active agent
content of the products.
[1959] 11.sup.th aspect of "Medical Certificates": The method for
agricultural management according to any one of the 8.sup.th to
10.sup.th aspect of "Medical Certificates", wherein the method
includes a step for automatically triggering an indication of
demand of a plant and/or animal product depending on whether a
selected product has reached a predefined threshold, in particular
a predefined plant growth and/or a degree of maturity and/or a
nutrient content and/or a mineral content and/or an active agent
content or an active agent concentration.
[1960] This can allow a customer to indicate demand, for example on
a transfer platform, and production to be implemented, either on
the basis thereof or independently, such that the logged demand can
be automatically acquired as an order when the boundary conditions
and preconditions stored by the customer are reached and can be
processed further such that, in particular, harvesting and delivery
can be implemented if such a procedure was agreed in advance within
the scope of an order method. Alternatively, data in relation to
products that were produced in a breeding and/or growing and/or
raising facility could be made available here on a corresponding
transfer platform, said data including, for example, amounts, light
recipes, life-cycle assessments, residual illumination durations,
storability and storage requirements, active agent contents and
concentrations, and the like. The data can be provided once, at
regular intervals, when certain growth or maturity stages are
reached, or virtually in real time, depending on sensor data and
measurement intervals, for example. These data from one or more
breeding and/or growing and/or raising facilities can be compared
on the transfer platform to indications of demand by one or more
customers, in some embodiments/implementations a multiplicity of
customers. As soon as a predefined criterion, e.g., a criterion
predefined by a customer, has been reached, an automatic order can
be triggered on the transfer platform. Order data or product
requirements on the part of the customer, the light recipes
selected by a software program (app) and further growth information
items, and plants illuminated or grown therewith and optionally
provided with an identification code can be saved permanently as a
correlation data record by means of a blockchain method and thus
can also become comprehensible to the customer. This can ensure a
gap-free and non-falsifiable record of the entire growth and supply
chain. This can be particularly useful for operators and
customers.
[1961] 12.sup.th aspect of "Medical Certificates": An application
app for selecting and/or purchasing and/or licensing a light recipe
according to any one of the 1.sup.st to 11.sup.th aspect of
"Medical Certificates".
[1962] 13.sup.th aspect of "Medical Certificates": An application
app for coupling various light recipes.
[1963] 14.sup.th aspect of "Medical Certificates": An application
app for interactively designing light recipes.
[1964] 15.sup.th aspect of "Medical Certificates": A breeding
and/or growing and/or raising facility, in particular for plants
and/or animals (agricultural facility), comprising at least an
input device, a computing device and an output device, wherein the
computing device is designed to output output data to the output
device and wherein the output data contain at least information
items in relation to a degree of maturity, in particular an active
agent content and/or an active agent concentration of at least one
active ingredient, and wherein the output unit comprises a means
for outputting the output data to a user or a control device.
[1965] The output data can contain at least information items in
relation to an active agent, an active agent content and/or an
active agent concentration of one or more plants, in particular
medically active plants. Undertaking production of products within
the scope of predetermined boundary conditions can be facilitated
in such a breeding and/or growing and/or raising facility.
[1966] 16.sup.th aspect of "Medical Certificates": An agricultural
system, comprising:
[1967] a plurality of processing lines for growing plants of a
given plant type, wherein a first processing line in the plurality
of processing lines is configured to: [1968] move a first plurality
of plants through the agricultural system along a route; and [1969]
apply a first growth condition to the first plurality of plants to
satisfy a first active agent parameter for the first plurality of
plants.
[1970] An active agent can for instance be a pharmaceutical
ingredient or nutrient of the plant. For instance, in case of a
Cannabis-plant, it can be THC or CBD. Theine can for example be the
active agent of a tea plant, and a vitamin or mixture of vitamins
(vitamin complex) can for instance be the active agent of a fruit.
Further, also a plant-color like Anthocyanin can be an active agent
of a plant.
[1971] A processing line can for instance be designed as described
in "Aquaponics", "Horticulture Processing Line", "Resizable Growth
Area" and/or "Light Recipes and Workflow". The processing lines can
for example be arranged in an indoor farm, for instance an
agricultural facility.
[1972] 17.sup.th aspect of "Medical Certificates": The system of
the 16.sup.th aspect of "Medical Certificates", wherein each of the
plurality of processing lines is configured to apply a different
growth condition to their respective plants.
[1973] In general words, a "growth condition" can for example be a
condition relevant for the growth of the plant, modifying the
growth condition will typically alter the growth of the plants, or
the ripening/flowering or the like. A growth condition can for
instance be determined by the illumination (in particular light
recipe), temperature, humidity, CO2-content in the air, and/or
fertilizers, etc. A growth condition can for example be defined in
a growth recipe. By applying different growth conditions, the
active agent parameter of the plant can be influenced.
[1974] 18.sup.th aspect of "Medical Certificates": The system of
the 16.sup.th or 17.sup.th aspect of "Medical Certificates",
wherein the first active agent parameter comprises an amount and/or
concentration of an active agent.
[1975] The active agent parameter can for instance be the content
of an active agent in the plant, and it can be provided in absolute
mass units (e.g. milligrams) or in relation to a reference (e.g.
milligrams per kilogram or milligrams per liter). It is not
necessarily measured by a molecular analysis of the plant, but
could also be evaluated indirectly (i.e. when the active agent
affects the growth or appearance of the plant). In other words, the
active agent is not necessarily measured directly, instead the
influence on the morphology/form and/or color of the plant could be
taken as a reference.
[1976] 19.sup.th aspect of "Medical Certificates": The system of
any of the 16.sup.th to 18.sup.th aspects of "Medical
Certificates", wherein the active agent is a biological or chemical
component that provides a nutritional and/or health-related benefit
to the first plurality of plants.
[1977] 20.sup.th aspect of "Medical Certificates": The system of
any of the 16.sup.th to 19.sup.th aspects of "Medical
Certificates", wherein the first processing line comprises a
conveyor belt or an autonomous vehicle.
[1978] 21.sup.st aspect of "Medical Certificates": The system of
any of the 16.sup.th to 20.sup.th aspects of "Medical
Certificates", the system further comprising a memory configured to
store data about the first plurality of plants.
[1979] 22.sup.nd aspect of "Medical Certificates": The system of
the 21.sup.st aspect of "Medical Certificates", wherein the data
comprises at least one of a location in the agricultural system of
the first plurality of plants at a corresponding time, amount of
time that the first growth condition has been applied to the first
plurality of plants, the first active agent parameter, growth data
of at least one of the first plurality of plants, the first growth
condition, and an identifier for each plant in the first plurality
of plants.
[1980] 23.sup.rd aspect of "Medical Certificates": The system of
the 21.sup.st or 22.sup.nd aspect of "Medical Certificates", the
system further comprising at least one sensor configured to collect
at least a portion of the data about at least one of the first
plurality of plants as it is moved along the route.
[1981] 24.sup.th aspect of "Medical Certificates": The system of
any of the 21.sup.st to 23.sup.rd aspects of "Medical
Certificates", wherein at least a portion of the data is stored in
a blockchain.
[1982] A blockchain can for example be a digital record that stores
a list of transactions (called "blocks") backed by a cryptographic
value. Each block can contain a link to the previous block, a
timestamp, and data about the transactions that it represents.
Blocks are immutable, meaning that they can't easily be modified
once they're created. And the data of a blockchain are stored
non-locally, i.e. on different computers. These computers could be
the computer of the producer and the computer of the customer.
[1983] The data collected by the sensors can contain information
about the parameters applied to the plants (like temperature and
illumination) and the growth status of the plants until harvesting.
Using a blockchain that is shared between at least the customer and
the farmer, the customer can be assured that the data collected in
the blockchain are correct, as it is almost impossible to modify a
blockchain once it has been created, i.e. a modification of data by
the farmer afterwards (e.g. to hide problems during production) is
impossible.
[1984] 25.sup.th aspect of "Medical Certificates": The system of
any of the 16.sup.th to 24.sup.th aspects of "Medical
Certificates", wherein the route is segmented into a plurality of
growth zones, and in each growth zone the first processing line is
configured to apply a different growth condition to the first
plurality of plants.
[1985] 26.sup.th aspect of "Medical Certificates": The system of
the 25.sup.th aspect of "Medical Certificates", wherein the
plurality of growth zones comprises at least one of a germination
zone, a maturation zone, and a flowering/fructification zone.
[1986] 27.sup.th aspect of "Medical Certificates": The system of
the 25.sup.th or 26.sup.th aspect of "Medical Certificates",
wherein a route for each of the plurality of processing lines is
segmented into the plurality of growth zones.
[1987] In general the different growth conditions can for instance
differ in at least one of a light recipe, a temperature, and a
carbon dioxide concentration.
[1988] 28.sup.th aspect of "Medical Certificates": The system of
any of the 25.sup.th to 27.sup.th aspects, wherein each of the
different growth conditions is based on growth data received from
one or more users.
[1989] The plurality of users can for instance be at least 10, 50,
100, 500 or 1000 different users (possible upper limits can for
example be 1.times.10.sup.7 or 1.times.10.sup.6 different users).
Defining the growth conditions this way can be advantageous as, for
instance, a wide range of requirements can be collected or mapped,
which goes beyond an experimental data base or matrix drafted by a
single individual. The data generated respectively can allow for
revealing correlations, for instance by artificial intelligence
analysis, which are not accessible by conventional techniques.
[1990] 29.sup.th aspect of "Medical Certificates": The system of
any of the 16.sup.th to 28.sup.th aspects of "Medical
Certificates", wherein the first growth condition is defined by a
user that owns the plants.
[1991] 30.sup.th aspect of "Medical Certificates": The system of
any of the 16.sup.th to 29.sup.th aspects of "Medical
Certificates", wherein the first growth condition is constructed by
applying machine learning on growth data received from one or more
users.
[1992] 31.sup.st aspect of "Medical Certificates": The system of
any of the 16.sup.th to 30.sup.th aspects of "Medical
Certificates", wherein the first growth condition comprises a
plurality of parameters relevant for growth of the first plurality
of plants; and applying the first growth condition to the plurality
of plants comprises adjusting one or more of the parameters in the
first processing line.
[1993] 32.sup.nd aspect of "Medical Certificates": The system of
the 31.sup.st aspect of "Medical Certificates", wherein the
plurality of parameters comprises at least one of an illumination
level, one or more illumination wavelengths, a temperature, a
humidity, a concentration of one or more gases in the air, and a
fertilizer amount or concentration.
[1994] 33.sup.rd aspect of "Medical Certificates": A method of
operating an agricultural system, comprising:
[1995] defining a plurality of growth zones for a plurality of
plants of a given plant type; and
[1996] applying, in each of the plurality of growth zones, a
different growth condition to the plurality of plants, wherein a
first growth condition applied in a first growth zone of the
plurality of growth zones causes the plurality of plants to satisfy
a first active agent parameter.
[1997] 34.sup.th aspect of "Medical Certificates": The method of
the 33.sup.rd aspect of "Medical Certificates", wherein the first
active agent parameter comprises an amount and/or concentration of
an active agent.
[1998] 35.sup.th aspect of "Medical Certificates": The method of
the 33.sup.rd or 34.sup.th aspect of "Medical Certificates",
wherein the active agent is a biological or chemical component that
provides a nutritional and/or health-related benefit to the
plurality of plants.
[1999] 36.sup.th aspect of "Medical Certificates": The method of
any of the 33.sup.rd to 35.sup.th aspects of "Medical
Certificates", wherein the plurality of growth zones comprises at
least one of a germination zone, a maturation zone, and a
flowering/fructification zone.
[2000] 37.sup.th aspect of "Medical Certificates": The method of
any of the 33.sup.rd to 36.sup.th aspects of "Medical
Certificates", further comprising:
[2001] receiving the first growth condition from a user that owns
the plurality of plants.
[2002] 38.sup.th aspect of "Medical Certificates": The method of
any of the 33.sup.rd to 37.sup.th aspects of "Medical
Certificates", further comprising:
[2003] determining each of the different growth conditions based on
growth data of one or more users.
[2004] 39.sup.th aspect of "Medical Certificates": The method of
any of the 33.sup.rd to 38.sup.th aspects of "Medical
Certificates", wherein the first growth condition is constructed by
applying machine learning on growth data received from one or more
users.
[2005] 40.sup.th aspect of "Medical Certificates": The method of
any of the 33.sup.rd to 39.sup.th aspects of "Medical
Certificates", further comprising:
[2006] storing data about the plurality of plants.
[2007] 41.sup.st aspect of "Medical Certificates": The method of
the 40.sup.th aspect of "Medical Certificates", wherein the data
comprises at least one of a location in the agricultural system of
the plurality of plants at a corresponding time, amount of time
that the first growth condition has been applied to the plurality
of plants, the first active agent parameter, growth data of at
least one of the plurality of plants, the first growth condition,
and an identifier for each plant in the plurality of plants.
[2008] 42.sup.nd aspect of "Medical Certificates": The method of
the 40.sup.th or 41.sup.st aspect of "Medical Certificates",
further comprising:
[2009] collecting, by one or more sensors, at least a portion of
the data about the plurality of plants.
[2010] 43.sup.rd aspect of "Medical Certificates": The method of
any of the 40.sup.th to 42.sup.nd aspects of "Medical
Certificates", wherein at least a portion of the data is stored in
a blockchain.
[2011] 44.sup.th aspect of "Medical Certificates": The method of
any of the 33.sup.rd to 43.sup.rd aspects of "Medical
Certificates", further comprising:
[2012] moving the plurality of plants between the plurality of
growth zones using a processing line.
[2013] 45.sup.th aspect of "Medical Certificates": The method of
any of the 33.sup.rd to 44.sup.th aspects of "Medical
Certificates", wherein
[2014] the first growth condition comprises a plurality of
parameters relevant for growth of the first plurality of plants;
and
[2015] the first growth condition is applied in the first growth
zone by adjusting one or more of the parameters in the first growth
zone.
[2016] 46.sup.th aspect of "Medical Certificates": The method of
the 45.sup.th aspect of "Medical Certificates", wherein the
plurality of parameters comprises at least one of an illumination
level, one or more illumination wavelengths, a temperature, a
humidity, a concentration of one or more gases in the air, and a
fertilizer amount or concentration.
[2017] 47.sup.th aspect of "Medical Certificates": The method of
any of the 33.sup.rd to 46.sup.th aspects of "Medical
Certificates", for operating the agricultural system of any of the
16.sup.th to 32.sup.nd aspects of "Medical Certificates".
[2018] Individualized Light Recipes and Growth Recipes
[2019] "Medical Certificate" allows the application by a user of
their own light recipe. Such a light recipe program can also
specify further growth variables, such as, for example,
fertilization, watering, ambient temperature, location of a plant
in relation to a light source, time of the light-induced transition
from the growth stage to the flowering stage, storage conditions
after the harvest, transport conditions and the like. These
non-light-related or not exclusively light-related specifications
can be stored in a growth recipe. Here, a growth recipe should be
understood to be a database, lookup table or other data source or
collection of data, which defines the aforementioned parameters
and/or which contains data that are relevant to the growing,
growth, breeding, treatment, harvest and the like of plants and/or
animals. A growth recipe can also be configured as a dynamic growth
recipe. The latter can specify, select and, by way of the actuators
such as light fixtures, food supply devices, etc., set in the
growth recipe, carry out growth-specific light recipes. By way of
example, growth-specific light recipes can be defined as a function
of a plant-specific growth variable, such as the Leaf Area Index,
for example.
[2020] A light recipe within the meaning of "Medical Certificate"
should be primarily understood to be an illumination concept,
although it may also contain control data of a growth recipe or
contain control commands for a growth recipe, for example when
water or fertilizer should be applied, as these may be coupled to a
light function. Provided it is specified for a greenhouse, a light
recipe can also be specified depending on the geographic location
and/or the (statistical) weather conditions, and consequently also
include the presence of natural daylight. Growth recipes and light
recipes can thus interact or cover parameter spaces and
specifications for breeding and/or growing and/or raising plants
and, optionally, animals as well which at least intersect with one
another or are in part common to one another.
[2021] Specified light recipes may comprise all stages of the plant
growth and the storage and delivery process, i.e. seeds, seedlings,
growth, flowering, maturity, harvest, storage and transport.
[2022] As mentioned at the outset, although growth- and
maturity-promoting illumination concepts are known per se, they
should be established exactly in each case for specific
applications and customer requirements. This also applies to
illumination concepts that should form or accumulate a
predetermined or predefined concentration of certain active agents,
also referred to as phytochemical active agents. By way of example,
phytochemical active agents can include: vincristine, vinblastine,
taxanes, paclitaxel, docetaxel, baccatin, cephalomannine, xylosyl,
tetrahydrocannabinol (THC) and cannabidiol (CBD) from cannabis
plants such as Cannabis sativa, Cannabis indica and Cannabis
ruderalis, eucalyptol, genistein, daidzein, codeine, morphine,
quinine, alkannin, cimicifuga, and more. Cannabis products can have
more than 85 different phytochemical active agents, inter alia
cannabinol (CNB), biphenyl and biphenyl-like and tricyclic
cannabinoid active agents. Further illumination methods can promote
or prevent the production of certain plant ingredients. Thus, it is
possible to choose an illumination that can promote the formation
of anthocyanins in plants or fruits, which gives certain fruit
types a red, violet or blue color.
[2023] Luminous energy, i.e., photon fluxes, can be specified as
micromol/(m.sup.2s) values (also expressed as .mu.mol/(m.sup.2s) or
.mu.E/(m.sup.2s)). By way of example, a light source can be
configured in such a way that it emits a photon flux of 2000
.mu.mol/(m.sup.2s) in the spectral range of 420-700 nm and a photon
flux of 600 .mu.mol/(m.sup.2s) in the spectral range of 650-700 nm.
These variables are adjustable within large boundaries depending on
the design of the light sources.
[2024] According to a development of the present disclosure, an
operator, customer or other user of a breeding and/or growing
and/or raising facility or a user of the growing and/or breeding
and/or raising method can store, for example by means of an input
means, a product specification in a database or transfer platform.
On the basis thereof, a control unit or a computing device of the
breeding and/or growing and/or raising facility can determine a
light recipe meeting the chosen requirements or select one or more
suitable light recipes from a plurality of light recipes stored in
a database. Moreover, there can also be an automatic adaptation of
the respective requirements to the light recipe by way of an input
means on the basis of a preselection of a product specification and
measurement data in relation to the products, for example by
sensors.
[2025] Consequently, it is of a great advantage if customers are
able to choose between various light recipes, in some
embodiments/implementations certified light recipes, for the
product to be obtained.
[2026] According to the disclosure, a method for creating a light
recipe (illumination code), which comprises the entire lifecycle of
a growing product, is also provided, as well as such a light
recipe. Such a light recipe may contain executable program codes
and executing program codes of a growth recipe and/or may interact
with such program code; thus, a light recipe may contain program
code which selects (or prompts the generation of) a growth recipe
fitting to the current situation via a database or by way of a
currently employed deep learning analysis (AI) and which applies
said growth recipe. What may occur here is that a growth recipe is
selected and, as a consequence thereof, the light recipe needs to
be reconfigured, i.e., its program code has to be modified, and
said light recipe interacts with the program code of the growth
recipe in this manner.
[2027] Moreover, the present disclosure also relates to a method
for the application of a coupled light recipe to different growing
products. A coupled light recipe or growth recipe is intended to be
that a light recipe (or growth recipe) can be configured in such a
way that the respective program, for example on the basis of a
camera input, recognizes a new product (e.g., during a conveyor
belt illumination process or when replacing a growth shelf) and
then applies a light recipe related to this plant type. Thus, the
light recipe (software in the database) can be configured to select
and apply a light recipe assigned to the plant for each plant type,
i.e., to couple said light recipe to the plant. In the case of a
pass-type process, the light recipes are coupled to one another in
time.
[2028] App, Certification and Obtaining a License
[2029] To this end, users, in particular customers, can be provided
with control or regulating software, for example. The present
disclosure also relates to such software and a data storage medium
having such software. The software can be installed as an
executable version on a data storage medium, for example an
interchangeable data storage medium or a mobile data storage
medium, or on a computing device and it is intended also to be
referred to as an app below. Here, computing devices can be:
computers, mobile appliances such as tablet computers and
telephones, servers with and without remote access options, for
example Internet-based input masks, and other components that have
a display, processing, output or other option for accessing the app
and/or the breeding and/or growing and/or raising facility.
[2030] In particular, the software can also be software for
controlling the breeding and/or growing and/or raising facility or
parts of the breeding and/or growing and/or raising facility.
[2031] Users are able to install or activate the app on a system
provided therefor. Different light recipes can be displayed in the
app for the tested or specified plant types, in particular for
plants with applications in medicine.
[2032] According to "Medical Certificate", the application app can
be embodied for selecting and/or purchasing and/or licensing a
light recipe, as described herein. To this end, the app can be
coupled to a communications interface of the computing device in
order to facilitate one-way or two-way (reciprocal) communication
with data storage media, databases, control units, other computing
units, servers or other internal or external components.
[2033] The app can also be embodied to couple various light
recipes. This means that an APP is configured in such a way that it
recognizes whether or when a chosen light recipe no longer leads to
success as a result of modified boundary conditions, or whether or
when another and possibly new light recipe, which achieves the
desired result more efficiently, quicker or with a better
life-cycle assessment, is present. Consequently, coupling light
recipes also means stringing together best-suited light recipes for
a pre-determinable result. In this way, there can be a change of
the applied light recipe to an alternative or better light recipe
according to the respective circumstances if need be. In turn, this
can be implemented within the chosen specifications or boundary
conditions. Here, the app can be embodied in such a way that a
selection of the suitable light recipes is implemented
automatically. If light recipes that should only be applied to a
certain or pre-determinable interval, for example a growth stage or
flowering stage, are selected, automatic coupling of light recipes
for different growing stages can be implemented accordingly.
[2034] In particular, the app can be embodied for the interactive
design of light recipes. This can allow a user to manipulate or
adapt a control, in particular a light application. Here, it is
conceivable for the app or the input data for controlling the
breeding and/or growing and/or raising facility to provide the user
with a restricted parameter space, within which variations of the
light recipes are facilitated. In this way, a predetermined
specification, for example a permitted maximum active agent content
or a maximum active agent concentration can be observed in
medically active plants despite the option of a manual, interactive
design of light recipes. Then, interactively created light recipes
can be made available, for example as output data from the app, or
from the app via the control device as output data in an internal
and external database, or they may be merely stored. In this way,
other users may also access light recipes created in this manner.
Then, other users may be provided with rights for using and/or
processing the light recipes, possibly once again within a
restricted variable or parameter space.
[2035] Certification and Purchase of Specific Light Recipes
[2036] Light recipes can be selected by a user within the app or,
in the case of an Internet-based access to databases, using a
browser-based access mask. The user can or must be registered,
depending on a selection of the light recipes. Moreover, it is
possible for the light recipes to be purchased or for licenses for
use thereof to be obtained such that the user is put into the
position where they are able to apply light recipes relevant to
them for the purposes of growing and/or breeding corresponding
plants. Here, a licensing may for example be unrestricted, or
restricted to a certain time period or to a pre-determinable number
of growth cycles or maturity cycles. Corresponding apps or
additional modules of such apps can be provided by, for example, an
operator of a breeding and/or growing and/or raising facility, by a
distribution partner or by a certification body such as the
department of health. The light recipes stored for the respective
application or plant types can be labeled as certified or
non-certified and/or can be classified as permitted or not for
certain groups of people. In this way, it is possible to obtain
access control within the app and a restriction of the group of
people using the light recipes.
[2037] The app can be provided interactively. This means that a
user can specify personal requirements and optionally adapt or
match the light recipe and also, optionally, the growth concept to
these requirements. Such light recipes may be certified, but need
not be certified, by an official body.
[2038] Official light recipes are certified and reveal the active
ingredients that are obtainable by the illumination and the growth
conditions for the respective plant types, with possible ranges of
variation. It is also conceivable here that a light recipe can be
varied only in certain areas or only in respect of predetermined
parameters by a user so that it is possible to ensure that a
product remains within predetermined limits, for example certified
limits.
[2039] Furthermore, light recipes that can be tailored to certain
groups of people may be offered. Here, it is possible to take
account of, for example, body size, age, disease, sex, skin type,
previous diseases, addiction treatment, co-medicaments, allergies
and the like when selecting, assigning and determining one or more
light recipes.
[2040] Thus, the apps can specify the active ingredients or the
concentrations thereof that result over the irradiation time within
the scope of a chosen light recipe for different breeding and/or
growing and/or raising products and different requirements or
groups of people. Dark stages may also be included therein.
[2041] The apps can specify/have certified breeding and/or growing
and/or raising facilities, which are able to carry out the chosen
light recipes for the chosen products, i.e., which comprise
suitable illumination devices.
[2042] Thus, customers purchase or license a light recipe and then,
provided a selection exists, select a suitable breeding and/or
growing and/or raising facility, which is as local as possible, and
order their product. Once an order has been implemented, it can
naturally also be triggered again in future.
[2043] The control device or another component of a breeding and/or
growing and/or raising facility according to the disclosure may
comprise a communications device for communicating the measured
data to the respective customers. In this way, access, in
particular remote access, to the measured data and optional further
information items relating to the intended and/or actual state of
the breeding and/or growing and/or raising facility or specific
growth data of growing products can be facilitated for a user. In
particular, the communications device can be configured to
communicate with a certification body or with a communications
device and/or database of a certification body. A method for
controlling a breeding and/or growing and/or raising facility can
accordingly include a step for communicating with a certification
body.
[2044] Breeding and/or Growing and/or Raising Logistics
[2045] The selected light recipe is available as a digital software
program or as program code and/or as a collection of parameters, is
identified and, in conjunction with the order process, transmitted
to a selected producer or operator or the selected producer or
operator of a breeding and/or growing and/or raising facility
authorized to this end, said producer or operator then growing and
accordingly illuminating the product or making a product that is
already complete and that meets the requirements ready for delivery
(or collection). To this end, the operator of the breeding and/or
growing and/or raising facility must ensure that the ordered plant
also experiences the ordered light recipe. Therefore, it is
expedient to provide a plant container or a tray of plants with a
corresponding unique code, which ideally also contains the order
data.
[2046] Should a customer order a plurality of plant types with
different light recipes, an app can calculate or set a respective
start date, proceeding from the desired delivery date, in such a
way that the growing products are finished simultaneously.
[2047] In the case of a growing product that still has to grow, the
current and/or integral exposure data (spectra, exposure time
durations, modes of operation, dark stages, spectral photon fluxes)
and calculated or measured concentrations of active ingredients can
be communicated to a customer (via the app, email, etc.).
Naturally, the concentrations must be determined in situ or at a
certified testing body.
[2048] Active agent concentrations can be determined by means of
suitable measurement methods. The use of luminescent or fluorescent
markers in cannabis plants and illumination of the plants with UV
light, visible red light or infrared light is known. Then, medical
cannabis can be differentiated from other cannabis types on the
basis of the spectral data.
[2049] The customer is informed when the specified substance values
are reached, and delivery is triggered or self-collection is
implemented. What light recipe is suitable for storage or for
keeping the active ingredients can be communicated to the customer
upon collection. If the customers have a similar illumination
scenario at home, they can store the substances therein under
recommended conditions.
[2050] Customers are able to report their experiences and, where
applicable, their privately determined measured values of the
active ingredients by way of a forum or via their physician. These
can then be assessed by an expert team and, if need be, a new light
recipe is thereupon created, certified and then also made
available.
[2051] Furthermore, customers can (following payment) download
light recipes (apps) onto their smartphone or other communications
devices, for example, and operate their private plant illumination
therewith. To this end, the private plant illumination should be
compatible with (or even certified for) the light recipe (and also
the growth recipe).
[2052] Using portable appliances, customers are able, for example,
to measure the UV absorption of a (dissolved) cannabis product and
thus determine the THC concentration.
[2053] Plant Illumination
[2054] Plant-growth-promoting illumination by way of artificial
light sources has been known for a relatively long time, firstly as
an additional illumination in greenhouses, and then for plant
illumination in spaces that are largely or even completely shielded
from natural ambient light.
[2055] Light Sources
[2056] Characteristics of Light Sources
[2057] Reference is made to the respective paragraph of "Eco
Certificate" with the same title name.
[2058] Operating Mode of Light Sources
[2059] Reference is made to the respective paragraph of "Eco
Certificate" with the same title name.
[2060] Parameters of Light Sources/Sensors
[2061] Reference is made to the respective paragraph of "Eco
Certificate" with the same title name.
[2062] Plant
[2063] Reference is made to the respective paragraph of "Eco
Certificate" with the same title name.
[2064] Characteristics of Illumination for Light Recipes
[2065] Reference is made to the respective paragraph of "Eco
Certificate" with the same title name.
[2066] Light Recipes
[2067] Reference is made to the respective paragraph of "Eco
Certificate" with the same title name.
[2068] By way of example, light recipes can be created and selected
taking account of both ecological points of view and customer use
points of view. These include inter alia: preference for taste,
consistency, look, color, smell, ingredients of a product (plant,
animal). For plants that are applicable in a medical or therapeutic
context, further properties may increase the customer usefulness:
vitamin C content, nutrients, minerals, medical active ingredients
such as cannabidiol, THC, cancer-fighting substances, pain reducing
active agents, cramp releasing active agents, etc., but also the
concentration of toxic and consequently damaging plant
ingredients.
[2069] Different groups of people have different requirements or
metering needs, for example on account of body size, age, disease,
sex, skin type, previous diseases, addiction treatment,
co-medicaments, allergies, etc.
[2070] Therefore, a customer is interested in obtaining or actively
co-designing the optimal product for their requirements (on account
of the personal well-being or on account of examinations by a
physician). Since light recipes decisively cause and influence
product growth and quality, it would be advantageous if a customer
knows these variables or is made aware of these variables and if
said customer could trigger an order on the basis thereof.
Moreover, it would be advantageous if a customer could co-design a
light recipe. This can achieve a maximization of use. These usage
factors are referred to here as effect values WW.
[2071] To this end, the customer must know the applied light
recipes or the administered light variables (see below) or the
effect values WW for the product to be ordered or the ordered
product, and optionally also other growth and maturity parameters
and correlation factors K. It is conceivable that a customer or
user is likewise able to influence these correlation factors.
[2072] Matching the Wavelength to Fields of Application
[2073] Reference is made to the respective paragraph of "Eco
Certificate" with the same title name.
[2074] Spectral Compositions
[2075] Reference is made to the respective paragraph of "Eco
Certificate" with the same title name.
[2076] Dependence on Leaf Area Parameters
[2077] Reference is made to the respective paragraph of "Eco
Certificate" with the same title name.
[2078] Irradiation Sequences
[2079] Reference is made to the respective paragraph of "Eco
Certificate" with the same title name.
[2080] Further Irradiation Effects
[2081] Reference is made to the respective paragraph of "Eco
Certificate" with the same title name.
[2082] Illumination/Imaging
[2083] Reference is made to the respective paragraph of "Eco
Certificate" with the same title name.
[2084] Examples of Light Recipes
[2085] Reference is made to the respective paragraph of "Eco
Certificate" with the same title name.
[2086] Phytoremediation/Phytomining
[2087] A light recipe which regulates the photon flux of a light
source in such a way that the production of an active ingredient is
promoted or a light recipe which regulates depending on an active
ingredient or active ingredient concentration.
[2088] Sensors
[2089] Reference is made to the respective paragraph of "Eco
Certificate" with the same title name.
[2090] Data Analysis and Database
[2091] Controlling Growth
[2092] Reference is made to the respective paragraph of "Eco
Certificate" with the same title name.
[2093] Database
[2094] Reference is made to the respective paragraph of "Eco
Certificate" with the same title name.
[2095] Fields of Application
[2096] Reference is made to the respective paragraph of "Eco
Certificate" with the same title name.
[2097] Urban Farming
[2098] Reference is made to the respective paragraph of "Eco
Certificate" with the same title name.
[2099] Cluster Farming
[2100] Reference is made to the respective paragraph of "Eco
Certificate" with the same title name.
[2101] Life-Cycle Assessment
[2102] Reference is made to the respective paragraph of "Eco
Certificate" with the same title name.
[2103] Furthermore, the customers may automatically be informed if
concentrations of the amounts of a predetermined active agent is
achieved.
[2104] In addition to achieving a certain life-cycle assessment,
other parameters or the attainment of such another parameter may be
a triggering event for subsequent steps in a method as described
here, in particular in an automated method. In particular, such a
parameter can also be an active ingredient concentration in a
plant.
[2105] Database
[2106] Reference is made to the respective paragraph of "Eco
Certificate" with the same title name.
[2107] Transfer Platform
[2108] Reference is made to the respective paragraph of "Eco
Certificate" with the same title name.
[2109] Such certificates also can be issued for medical plants and
optionally can be traded, for example in respect of production
volume, plant type or plant constituents and, in particular, active
agent content and active agent concentration. The explanations
above and also the explanations below in this case describe methods
for revealing different characterizing records, using the example
of life-cycle assessments. By way of example, a certification of
products which has been implemented within predetermined
specifications according to documentation can be obtained here in
an analogous or similar manner. The products can then be named,
labeled and traded accordingly.
[2110] Data Storage Medium
[2111] Reference is made to the respective paragraph of "Eco
Certificate" with the same title name.
[2112] Irradiation Unit
[2113] Reference is made to the respective paragraph of "Eco
Certificate" with the same title name.
[2114] Agricultural Facility
[2115] Reference is made to the respective paragraph of "Eco
Certificate" with the same title name.
[2116] Building
[2117] Reference is made to the respective paragraph of "Eco
Certificate" with the same title name.
[2118] Light as a Service (LaaS)
[2119] In a further embodiment of the disclosure the illumination
in the agricultural facility, particularly the illumination for
plants, is provided as a service. Such Light as a Service (LaaS)
means that the grower does not need to buy agricultural or
horticultural light fixtures, but just an illumination quantity or
alternatively a harvest yield. For example, the grower may rent the
light fixtures and just pays for the illumination quantity he or
she needs. To this end, a grower may give the service provider
specifications about the agricultural facility, e.g. production
area, and the requested result. Based on these specifications the
provider leases the appropriate light fixtures and provides the
illumination quantity according to the applied light recipe. Based
on the requested result the service provider may also provide an
appropriate light recipe.
[2120] For this purpose, the controlled agricultural system
comprises sensors for monitoring the operation of the light
fixtures. The monitoring may include operating durations and
illumination intensity during the operation durations. Therefore,
the sensors may comprise, for example, light sensors, sensors for
current measurements, clocks, etc. The operating data of the light
fixtures are stored, e.g. in the data storage device of the
agricultural system, and can be accessed by the service provider,
for example, via the control unit. Furthermore, the agricultural
system may be configured to bill the grower based on the operating
data and the fee rate agreed with the service provider.
Alternatively, the grower may be billed based on a flat rate.
[2121] 1.sup.st aspect of "LaaS": A controlled agricultural system,
comprising at least one light fixture and at least one sensor that
is able to monitor the operation of the light fixture, particularly
the illumination quantity.
[2122] 2.sup.nd aspect of "LaaS": A method for agricultural
management, wherein the illumination in an agricultural facility,
particularly the illumination for plants, is provided as a service
(LaaS).
[2123] 3.sup.rd aspect of "LaaS": The method for agricultural
management according to the 2.sup.nd aspect, wherein the applied
illumination quantity is monitored with a controlled agricultural
system according to the 1.sup.st aspect of "LaaS".
[2124] The aspects regarding Light as a Service (LaaS) mentioned
above can also unfold their beneficial effects when they are used
in combination with each of the above-mentioned elements of the
disclosure. For instance, LaaS may benefit from "Failure Detection"
in order to be able to detect failures of the light fixtures as
soon as possible. Furthermore, the failure may soon be corrected
with the help of "Failure Compensation", in order to safeguard the
illumination rented by the grower. The elements "Adaptive
Spectrum", "Temperature Dependent Illumination" and "Extended Light
Recipes" may help to reduce the operational cost for the service
provider. Elements described in the group "Plant Health and Growth"
may contribute to achieve the targeted yield.
[2125] As described in "Success Score" the customer can interact
with the grower via interfaces of the controlled agricultural
system and order customized plants. The customer can choose between
different growth recipes, e.g. according to "Medical Certificates",
and/or define his/her general requirements, which are then
translated into the correct growth recipe by the system, e.g.
according to "Customer Requirements".
[2126] Furthermore, the controlled agricultural system may be
configure according to elements of the group "Light and growth
Recipes", particularly "Flexible Growth", to adjust the growth
recipe. Using the farm setup the production is planned and started
according to elements of the group "Plant Health and Growth",
especially "Yield Prediction" to forecast the yield. The weather
forecast may also be taken into consideration. Furthermore,
feedback may be provided to the customer like eco-balance ("Eco
Certificates") and success score ("Success Score"), in case the
precise growth recipe for the specific farm is not available.
[2127] The elements "Smart Grid" and "Adaptive Spectrum" can also
be taken into consideration when planning the production and the
energy costs associated with it.
[2128] Using different farms (some of them greenhouses, i.e.
exposed to the weather) the production can be distributed among the
farms taking into account the local weather forecast to reach the
production target.
[2129] The customer can also interact with the controlled
agricultural system using a smartphone-app as described in "Picture
Taking & Evaluation", i.e. controlling the growth and health of
plants and providing this information to the platform. The data
obtained with the help of "Picture Taking & Evaluation" can
also be taken to improve prediction accuracy of "Yield Prediction"
and "Customer Requirements".
[2130] The controlled agricultural system can also give a feedback
about the plant growth. Customers can react to the feedback from
the platform. If changes are requested, they can be implemented
using growth recipe (see the group "Light and Growth recipe,
especially "Flexible Growth").
Further Aspects of the Disclosure
[2131] Agricultural Lighting as a Service (ALaaS)
[2132] Lighting as a Service (LaaS) is a value added service
delivery model in which a light service, in particular the
availability of an agreed upon illumination quantity and quality at
a specific location and at a specific time, is charged on a
subscription or use basis rather than via a one-time payment. Such
a business model has become known in commercial and citywide
installations of LED lights, specifically in retrofitting buildings
and outdoor facilities, with the aim of reducing installation
costs.
[2133] An Agricultural Lighting as a Service (ALaaS) delivery model
refers to a Controlled Agricultural System that employs Agriculture
Light Fixtures, Sensors and Actuators, as well as to a related
business model, wherein the installation of light emitting
elements, like light fixtures, their use and their performance are
monitored, locally or remotely, and counter measures are being
selected and executed in order to compensate for light degradation,
to repair a light emitting device or to provide repair
instructions, furthermore to trigger the exchange or refurbishment
of an Agricultural System or one of its components, and to select
adjusted growth conditions (i.e. to provide agreed-upon light or
growth recipes) in order to fulfill the agreed upon service
contract (ALaaS) as best as possible. Such an Agricultural Lighting
Service (ALaaS) can be assisted with smart contracts for example
based on blockchain technologies.
[2134] In order to provide such ALaaS services, several elements of
the disclosure need to be combined and jointly executed in order to
meet the contractual service obligations. In a preferred
implementation, a synergistic operating and control management is
intended that manages and employs favorable combinations of the
elements "Yield Prediction", "Resizable Growth Area", "Horticulture
Processing Line", "Failure Compensation", "Failure Detection", and
other as described below.
[2135] Agricultural Lighting as a Service (ALaaS) also means that a
provider of such services may need to ensure proper operation of an
Agricultural System or at least of some of its components, such as
light fixtures that provide illumination to the plants. Therefore,
in a preferred implementation it is provided to install and
activate a failure detection control system as described in the
element "Failure Detection" of the disclosure, aiming at the
detection, localization, repair, replacement or any other suited
countermeasures.
[2136] One of the possible countermeasures is described in the
element "Failure Compensation" of the disclosure wherein a
controlled agricultural system with a light fixture is proposed
that is configured to be able to compensate a failing light source,
namely a reduced light emission or even a total failure, at least
temporarily, until the failed light source, affected module, or the
light fixture as a whole, is replaced or repaired.
[2137] Using the element "Failure Compensation", the agreed-upon
light quantity and light quality can be maintained at least for a
short period of time after the detection of a failure using
"Failure Detection", until a proper repair of the defect light
source can be made. Thus, it is technically possible to reach the
targets defined in the ALaaS-agreement.
[2138] The customer may be supported in defining the right light
quantity and quality by using the element "Customer Requirements"
which helps to define the light and growth recipe based on the
requirements the customer has with respect to the quality of the
plants and produce (vitamin-content, color of the plants, etc.).
Based on this requirements, a proposal for a light quality may be
provided to the customer.
[2139] The element "Customer Requirements" relies mainly on
available data (i.e. which light or growth recipe provides which
results for a plant). These data might not always be available,
i.e. the element "Success Score" might be used to calculate the
success probability for an unknown combination of plants and/or
requirements.
[2140] Once the light quality and light quantity has been defined
by or for the customer, the eco-balance may be calculated using the
element "Eco Certificates".
[2141] The provider of ALaaS may use the aspects described in the
element "Smart Grid" to reduce his costs of providing the light,
like reducing light intensity when the costs are high. This might
result in adaptions of the light recipe as described in the
elements "Adaptive Spectrum", "Extended Light Recipes" and/or
"Flexible Growth". Modifications of the light spectrum might make
it necessary to recalculate the eco-balance as described in "Eco
Certificates".
[2142] While the light recipes defined in the ALaaS-contract are
applied, the growth of health of the plants may be monitored to
provide a feedback to the customer if the desired growth, yield and
quality targets can be reached. To achieve this, aspects described
in the elements "Disease & Pest Control", "Prophylaxis",
"Discolored Spot Detection", "LiDAR Plant Surveillance", "Stress
Detection" and/or "Yield Prediction" might be used. The status of
the plant growth might be provided using a UI which shows the
status and deviations between the actual growth and expected growth
status.
[2143] The elements to monitor the growth and health of plants need
sensors that are distributed within the agricultural farm. To
obtain an optimized distribution of sensors (i.e. a minimum number
of sensors with a maximum coverage) the aspects described in the
element "Measuring Patterns" can be used.
[2144] If deviations to the expected growth and yield results are
observed, the system may propose counter-measures. These might be
measures against disease or pest as described in the elements
"Disease & Pest Control", "Prophylaxis" and/or "Fungi Growth
Inhibition". If the projected yield is lower than expected, as e.g.
the estimations described in the element "Success Score" were not
completely correctly, the system might propose an updated light
recipe (or growth recipe) which can replace the originally
agreed-upon light recipe.
[2145] In other words, the described ALaaS service approach makes
use of several or all of the above-described elements that are
combined and jointly executed in a favorable way thus enabling
fulfillment of the contractual obligations to the benefit of the
growers and customers.
[2146] Agricultural Platform as a Service (APaaS)
[2147] A Platform as a Service (PaaS) or Application Platform as a
Service (aPaaS) or platform-based service is a category of cloud
computing services that provides a platform allowing customers to
develop, run, and manage applications without the complexity of
building and maintaining an infrastructure typically associated
with developing and launching an app or program. An Agricultural
Platform as a Service (APaaS) enables, for example, growers and
customers, as well as soft- and hardware developer, to create
better or more suited plant lighting recipes, plant growth and pest
control programs, stress detection and stress avoiding algorithms,
in form of computer implemented codes (Software, App), leading to
better biomass yield, a higher quality with respect to the
nutrients of the produce, a more reliable operation, a quicker time
to market, and a higher system reliability.
[2148] In particular, an Agricultural System may use a Data
Processing Center comprising a Software as a Service (SaaS)
input/output system configured to implement an agricultural product
decision-making and resource planning process by using an
Application Program Interface (API) provided by an SaaS platform,
and to request analysis from a Platform as a Service (PaaS)
analysis system, and to receive a result of the analysis from the
PaaS system, and output the analysis result to a User Interface
(UI).
[2149] An Agricultural Platform as a Service (PaaS) provides the
computing and data management resources and infrastructure to
collect and analyze data. Data may be general information about the
agricultural farm, for instance the functionality of the light
sources (see the element "Failure Detection"), the growth and
health data of the plants (see for instance the elements "LiDAR
Plant Surveillance", "Sensor Retrofit". "Stress Detection",
"Disease & Pest Control", Discolored Spots Detection", "Picture
Taking & Evaluation" and/or "Prophylaxis"), and the status of
the agricultural farm in general like humidity, temperature,
CO.sub.2 etc.
[2150] These data can be provided to customers, the provider of the
agricultural system or third parties for further analysis. The
analysis may contain yield prediction (see the element "Yield
Prediction"), the calculation of "Medical Certificates" or "Eco
Certificates" (see the respective elements), the evaluation of a
"Success Score" (see the element), the probability of an infection
(see "Disease & Pest Control"), and/or the risk of an infection
taking place (see "Prophylaxis").
[2151] The analysis may be displayed and/or used to control
actuators, e.g. to modify growth parameters as described in the
elements "Adaptive Spectrum", "Extended Light Recipes", Flexible
Growth", "Temperature Dependent Illumination", "Temperature
Control", and/or "Plant Movement", and/or to take measures against
pest or disease as described in the elements "Disease & Pest
Control", "Prophylaxis" and/or "Fungi Growth Inhibition". The
control parameters might be provided by third parties which us the
Agricultural Software Platform and the data provided by it.
[2152] Internet of Things
[2153] The Internet of Things is a network of devices such as light
fixtures, sensors and actuators. The devices may communicate among
each other using wire-bound or wireless communication. Wireless
communication may comprise Bluetooth, WLAN or OWC.
[2154] Optical Wireless Communications (OWC) is a form of optical
communication in which guided or unguided visible, infrared (IR),
or ultraviolet (UV) light is used to carry a signal. Visible light
communication (VLC) is a data communications variant which uses
visible light between 400 and 800 nm. VLC is a subset of optical
wireless communication technologies.
[2155] The agricultural system comprises several elements that can
communicate wireless with each other, especially using OWC, as
light fixtures are available throughout the agricultural system.
For instance, the "Failure Detection" may be communicated
wirelessly to a central computing device and/or computer system,
and the "Failure Compensation may be triggered in the same way.
Also the sensors may communicate in this way among each other, with
the light fixtures and with a central computing device and/or
computer system, for instance sensors as described in "Sensor
Retrofit" or "Measuring Patterns". Also the disease and growth
control may be done wirelessly, as well as the whole control of the
system (as described in "Aquaponics", "Resizable Growth Area"
and/or "Horticulture Processing Line").
[2156] However, when using light fixtures to communicate with the
sensors or actuators in the system, it has to be considered that
the light modulation may affect the intensity of the light fixtures
(either overall or at specific wavelengths). A way to deal with
this is described in the element "Light Recipe and VLC".
[2157] The control of such use of various OWC techniques may be
facilitated by a Software as a System (SaaS) system and method, a
Light as a Service (LaaS) system and method, and a Platform as a
Service (PaaS) system and method.
BRIEF DESCRIPTION OF THE DRAWINGS
[2158] FIG. 1 illustrates schematically a Controlled Agricultural
System.
[2159] FIG. 2 illustrates schematically a first embodiment of a
Controlled Agricultural System.
[2160] FIG. 3 shows a schematic block diagram of a controlled
agricultural system according to the disclosure.
[2161] FIGS. 4a, 4b show a first embodiment of a growth area.
[2162] FIG. 5 shows another embodiment of a growth area.
[2163] FIGS. 6a, 6b illustrate an adaption of the illumination to
the growth area changing its size.
[2164] FIG. 7 shows an alternative to the embodiment of FIGS. 6a,
6b.
[2165] FIG. 8 shows a schematic block diagram of a controlled
agricultural system according to the disclosure.
[2166] FIG. 9 schematically shows a grow field according to an
embodiment of the disclosure.
[2167] FIG. 10 schematically shows a grow field according to an
embodiment of the disclosure.
[2168] FIG. 11 schematically shows the steps of the method for
agricultural management according to the disclosure.
[2169] FIG. 12 schematically shows a controlled agricultural system
according to the disclosure.
[2170] FIG. 13 shows a vertical setup of growth zones in a vertical
farm.
[2171] FIG. 14 shows a schematic block diagram of a controlled
agricultural system for a plant growing facility, according to the
disclosure.
[2172] FIG. 15 schematically shows the steps of a method for
agricultural management according to the disclosure.
[2173] FIG. 16 schematically shows an example for a setting of
sensors in a greenhouse.
[2174] FIG. 17 shows a schematic block diagram of a controlled
agricultural system, according to the disclosure.
[2175] FIG. 18 schematically shows an exemplary illumination setup,
according to the disclosure.
[2176] FIG. 19 shows a schematic block diagram of an agricultural
facility according to an embodiment of a controlled agricultural
system.
[2177] FIG. 20 schematically shows the steps of a method for
agricultural management according to the disclosure.
[2178] FIG. 21 shows a block diagram of a controlled agricultural
system according to "Prophylaxis".
[2179] FIG. 22 shows a schematic flow chart of the method for
agriculture according to "Prophylaxis".
[2180] FIG. 23 shows a schematic block diagram of a controlled
agricultural system according to "Stress Detection".
[2181] FIG. 24 shows changes in leaf orientation due to changes of
environmental conditions.
[2182] FIG. 25 shows a schematic block diagram of a controlled
agricultural system according to an embodiment of "Discolored Spots
Detection".
[2183] FIG. 26 schematically shows the steps of the method for
agricultural management according to an embodiment of "Discolored
Spots Detection".
[2184] FIG. 27 shows a color ring.
[2185] FIG. 28 shows a plant leave with mottling and
discolorations.
[2186] FIG. 29 shows a block diagram of a controlled agricultural
system according to "Disease & Pest Control".
[2187] FIG. 30 shows a schematic flow chart of the method for
agriculture according to "Disease & Pest Control".
[2188] FIG. 31 shows a schematic block diagram of a controlled
agricultural system according to "Yield Prediction".
[2189] FIG. 32 shows a schematic flow chart of a method for
agricultural management according to "Yield Prediction".
[2190] FIG. 33 shows a schematic flow chart of an alternative
method for agricultural management according to "Yield
Prediction".
[2191] FIG. 34 shows a detail of a cultivated area within a
greenhouse.
[2192] FIG. 35 shows a schematic block diagram of a controlled
agricultural system according to "Growth Inhibition".
[2193] FIG. 36 shows a schematic block diagram of a controlled
agricultural system according to "Sensor Retrofit".
[2194] FIG. 37 shows an irrigation device equipped with sensor
devices.
[2195] FIG. 38 shows a first mounting option.
[2196] FIG. 39 shows a further mounting option.
[2197] FIG. 40 shows a schematic block diagram of a controlled
agricultural system according to "LiDAR Plant Surveillance".
[2198] FIG. 41 shows a schematic view of a greenhouse with a
distance measuring device mounted at the ceiling.
[2199] FIG. 42 shows a greenhouse with a plurality of distance
measuring devices mounted at the ceiling.
[2200] FIG. 43 shows a schematic block diagram of a controlled
agricultural system, according to the disclosure.
[2201] FIG. 44 shows the process or method in a schematic block
diagram.
[2202] FIG. 45 shows a block diagram of an exemplary embodiment of
a controlled agricultural system with adaptive additional
light.
[2203] FIG. 46 shows a schematic flow chart of the method for
agriculture according to the disclosure.
[2204] FIG. 47 shows a CIE diagram.
[2205] FIG. 48 shows an illustration of the color temperatures of
the sunlight.
[2206] FIG. 49 shows an illustration of the solar spectrum.
[2207] FIG. 50 shows an illustration of a target spectrum.
[2208] FIG. 51 shows a calculated difference spectrum.
[2209] FIG. 52 shows a schematic flow chart 5200 of an exemplary
embodiment of the method for agriculture according to the
disclosure.
[2210] FIG. 53 schematically shows an agricultural light fixture
according to an embodiment of the disclosure.
[2211] FIG. 54 shows a schematic block diagram of a controlled
agricultural system, according to the disclosure.
[2212] FIG. 55 schematically shows the steps of a method for
agricultural management according to the disclosure.
[2213] FIG. 56a, 56b schematically show intensities of LEDs.
[2214] FIG. 57 shows a schematic comparison of spectra.
[2215] FIG. 58 shows the schematic design of a controlled
agricultural system according to the disclosure.
[2216] FIG. 59 schematically shows a first illumination
configuration of an embodiment according to the disclosure.
[2217] FIG. 60 schematically shows a second illumination
configuration of the embodiment shown in FIG. 59.
[2218] FIG. 61 schematically shows a third illumination
configuration of the embodiment shown in FIG. 59.
[2219] FIG. 62 shows a schematic block diagram of a controlled
agricultural system according to the disclosure.
[2220] FIG. 63 shows a schematic block diagram of a controlled
agricultural system, according to the disclosure.
[2221] FIG. 64 shows a schematic block diagram of a light
fixture.
[2222] FIG. 65 illustrates a monitoring of the reduced
lighting.
[2223] FIG. 66 shows a schematic block diagram of a controlled
agricultural system for an agricultural facility, according to the
disclosure.
[2224] FIG. 67 schematically shows the steps of a method for
agricultural management according to the disclosure.
[2225] FIG. 68 schematically shows a set of optional steps.
[2226] FIG. 69 shows a lighting fixture with a light module
according to an embodiment of "Light Guides";
[2227] FIG. 70 shows another embodiment of "Light Guides";
[2228] FIG. 71 shows another embodiment of "Light Guides";
[2229] FIG. 72 shows a schematic drawing of an agricultural
lighting fixture according to an embodiment of "Light Guides";
[2230] FIG. 73 shows a schematic drawing of an agricultural
lighting fixture according to another embodiment of "Light
Guides".
[2231] FIG. 74 shows a schematic block diagram of a controlled
agricultural system according to "Failure Detection" and "Failure
Compensation".
[2232] FIG. 75 shows a schematic block diagram of a controlled
agricultural system with an integrated failure detection.
[2233] FIG. 76 shows a light fixture with a lens to which a light
sensor is coupled.
[2234] FIG. 77 shows a light fixture with a plurality of light
sources and illustrates a possibility for a failure
localization.
[2235] FIG. 79 shows a schematic block diagram of a controlled
agricultural system according to "Failure Compensation" (same as
"Failure Detection").
[2236] FIG. 78 shows a light fixture in a schematic view, a
compensation being achieved by increasing the emission of other
light sources.
[2237] FIG. 79 shows a light fixture with redundant light sources
for compensation.
[2238] FIG. 80 schematically shows an agricultural light fixture
with a heat reflector according to an embodiment of "Heat
Reflector".
[2239] FIG. 81 schematically shows an agricultural light fixture
according to another embodiment of "Heat Reflector".
[2240] FIG. 82 schematically shows an agricultural light fixture
according to a third embodiment of "Heat Reflector".
[2241] FIG. 83 shows a schematic block diagram of a controlled
agricultural system according to "Heat Reflector".
[2242] FIG. 84 shows a schematic design of a vertical farm with a
controlled agricultural system according to "Smart Grid", which is
connected to a smart grid power supply.
[2243] FIGS. 85A-85B show a schematic curve of electricity price
and light intensity of the light fixture of the controlled
agricultural system adapted thereto.
[2244] FIGS. 86A-86B show a further schematic curve of electricity
price and light intensity of the light fixture adapted thereto.
[2245] FIG. 87 shows a schematic flow chart of an exemplary
embodiment of the method for agriculture according to "Customer
Requirements".
[2246] FIG. 88 shows a schematic block diagram of a controlled
agricultural system according to "Success Score".
[2247] FIG. 89 schematically shows the steps of a method for
agricultural management according to "Success Score".
[2248] FIG. 90 schematically shows the steps of another method for
agricultural management according to "Success Score".
[2249] FIG. 91 schematically shows the steps of yet another method
for agricultural management according to "Success Score".
[2250] FIG. 92 schematically shows a digital model and a
corresponding real plant.
[2251] FIG. 93 schematically shows the steps of a method for
agricultural management according to "Picture Taking &
Evaluation".
[2252] FIG. 94 schematically shows an example of an image of a
growing cabinet in a viewfinder.
[2253] FIG. 95 shows a different view of the example of FIG.
94.
[2254] FIG. 96 shows a standard view of the example of FIG. 94.
[2255] FIG. 97 shows an example of a result of an analysis of the
standardized picture captured in FIG. 96.
[2256] FIG. 98 shows another example of a result of an analysis of
a standardized picture.
[2257] FIG. 99 shows a schematic block diagram of a controlled
agricultural system for an agricultural facility.
[2258] FIG. 100 shows a representation of a control unit of a
breeding and/or growing and/or raising facility according to an
embodiment of "Eco Certificate" as well as "Medical
Certificates".
[2259] FIG. 101 shows a flowchart of a breeding and/or growing
and/or raising facility according to an embodiment of "Eco
Certificate".
[2260] FIG. 102 shows a representation of a building complex for a
breeding and/or growing and/or raising facility according to an
embodiment of "Eco Certificate".
[2261] FIG. 103 shows a schematic illustration of a measurement and
control device for a breeding and/or growing and/or raising
facility according to an embodiment of "Eco Certificate".
[2262] FIG. 104 shows a flowchart of a breeding and/or growing
and/or raising facility according to an embodiment of "Medical
Certificate".
[2263] FIG. 105 shows a schematic illustration of a measurement and
control device for a breeding and/or growing and/or raising
facility according to an embodiment of "Medical Certificate".
[2264] FIG. 106 shows a schematic overview of tasks and steps for
operating the Controlled Agricultural System according to the
disclosure.
DETAILED DESCRIPTION
[2265] The detailed description is described with reference to the
accompanying figures. In the context of this description, the terms
"connected" and "coupled" are used to describe both a direct and an
indirect connection and a direct or indirect coupling.
[2266] System Setup
[2267] FIG. 1 illustrates schematically a Controlled Agricultural
System 100 according to various embodiments.
[2268] An agricultural light fixture 110 is connected to an
intelligent driver unit 120. The intelligent driver unit 120 is
configured to transmit a first signal 102 to the agricultural light
fixture 110. The connection between the agricultural light fixture
110 and the intelligent driver unit 120 may be a wired connection
or a wireless connection. The transmitting signal 102 may conform
to a common communication protocol. The intelligent driver unit 120
is connected to a light control unit 130. The light control unit
130 is configured to transmit a second signal 104 to the
intelligent driver unit 120. The first signal 102 is based on the
second signal 104. The light control unit 130 is connected to a
computing device 140, e.g. a computer system. Furthermore, the
computing device 140 is connected to a first sensor 150, e.g. an
optical sensor for measuring plant growth and plant health, and a
second sensor 160, e.g. a sensor for measuring environmental
parameters like temperature, humidity, etc. The computing device
140 is configured to compute a third signal 106 based on the
signals 108, 112 transmitted from the sensors 150, 160. The
computing device 140 is connected to a data storage device 170,
which may be based locally (on-site), in a network or in the cloud
(cloud computer network).
[2269] In various embodiments, the Controlled Agricultural System
100 may further comprise one or more actuators for adjusting the
growing conditions for the plants, for instance, for adjusting the
temperature, humidity, lighting, air, ventilation in the proximity
of the light fixture or for applying growth supporting components,
such as water, nutrients and/or pesticides to the seeds or
plants.
[2270] In various embodiments, the computing device may be
configured to perform an agriculture management software. The
agriculture management software may be configured to manage the
Controlled Agricultural System 100.
[2271] FIG. 2 illustrates schematically a first embodiment of a
Controlled Agricultural System 200.
[2272] An agricultural light fixture 110 is connected via a gateway
120, e.g. based on a local area network (LAN) 222 or wireless LAN
(WLAN) 224 or any other wired or wireless connection, to a light
control unit 130. The agricultural light fixture 110 comprises
light modules 212 and sensors, e.g. temperatures sensors for
monitoring the temperature of the light modules 212. Supplemental
sensors 150 for measuring plant growth and plant health, e.g. image
sensors 252, PAR sensors 254, and sensors 160 for measuring
environmental parameters, e.g. humidity sensors 262, temperature
sensors 264, are also connected via the gateway 120 to the light
control unit 130. Via the gateway 120 the light control unit 130 is
also connected to the computing device 140, e.g. a desktop computer
242, a laptop computer 244, a mobile device like a tablet 246 or
mobile phone 248 and/or to any graphical user interface (GUI). The
computing device 140 is configured to run an agriculture management
software. The light control unit 130 and the computing device 140
may also be connected to a data storage device 170 (cloud computer
network). The data storage device 170 (cloud computer network) may
be accessed via a website 272 and provide data storage 274, data
management 275, data analytics 276 and algorithms and computations
based on artificial intelligence (AI) 278.
[2273] In various embodiments, the data storage device 170 (cloud
computer network) may further comprise plant health definitions,
analytical reporting and growth strategies. The data storage device
170 (cloud computer network) may even comprise the functions of the
computing device 140.
[2274] The detailed description is described with reference to the
accompanying figures.
[2275] FIG. 3 shows a schematic block diagram of a controlled
agricultural system 100, according to the disclosure. The
controlled agricultural system 100 comprises a computing device
140, a data storage device 170, coupled to the computing device
140, an actuator device 310, coupled to the computing device 140
via a control unit 320 and a growth area 350 (see also FIG. 4).
[2276] The data storage device 170 comprises a database with data
of control parameters for controlling the growth area 350. Based on
the data stored in the data storage device 170, the control
parameters may be adjusted by means of the actuator device 310. To
this end, the computing device 140 is configured to adjust the size
of the growth area 350 and the size of an illuminated area, too,
see the Figures below. Furthermore, the computing device 140 is
configured to control grow parameters like nutrient concentration
or the lighting conditions. Therefore, the actuator device 310 may
comprise various actuators for adjusting the various parameters, in
particular the size of the growth area 350. Further, the
Agricultural System 100 may comprise one or more light fixtures
110, as shown in FIG. 1/2 (not shown in FIG. 3).
[2277] The controlled agricultural system 100 further comprises a
sensor device 150, for sensing the status of the growth of the
plants (coupled to the computing device 140 e.g. via a control unit
340). The sensor device 150 may particularly comprise a camera for
imaging the growth area 350 and the plants grown there. The
information about the growth status of the plants or the status of
the growth area 350 may be delivered to the user or customer by a
user interface (UI) 401, e.g. a control terminal coupled to the
computing device or a mobile device such as a smartphone or tablet
including a dedicated application (i.e. app for mobile
devices).
[2278] FIGS. 4a, 4b show a first possibility to design a growth
area 350 adjustable in size in a top view. It is assembled from a
plurality of bars 400, 401 parallel in groups, forming a
criss-cross pattern. The bars 400, 401 are interconnected with each
other in joints 402. The joints 402 are connected operatively with
each other, forming a scissors mechanism.
[2279] At the joints 402, the growth locations 404 can be arranged,
for instance pots for growing the plants. At the beginning of the
growth cycle, the growth locations 404 can be arranged close to
each other, as shown in FIG. 4a. When the plants grow, the size of
the growth area 350 can be adjusted, as shown in FIG. 4b. As shown
below, the light fixtures/the illuminated area can be adapted
accordingly.
[2280] FIG. 5 shows another possibility for providing a growth area
350 adjustable in size. The carrier is also assembled from a
plurality of bars 500 interconnected in joints 501. The bars 500
form a Hoberman-ring enabling a more or less rotationally
symmetrical size adjustment. In an early stage, the growth
locations 404 can be arranged closer to each other, the ring can be
extended at a later growth stage.
[2281] FIGS. 6a, 6b illustrate an adaption of the illumination to
the growth area changing its size. In FIG. 6a, the growth area 350
is small and can be fully illuminated by three light fixtures 110.
Accordingly, only the light fixtures 110 in the center are switched
on (cross hatched), those at the left and at the right are switched
off. The illumination area 601 is small.
[2282] In a later stage, shown in FIG. 6b, the growth area 350 is
larger since the plants are bigger. Accordingly, the illumination
is adapted, the light fixtures 110 on the left being switched on in
addition. The illumination area 602 is larger. Later on, when the
growth area 350 is larger again, the light fixtures 110 on the
right can be switched on in addition.
[2283] FIG. 7 shows an alternative to the embodiment of FIGS. 6a,
6b where the growth area 350 stays at the same location over the
growth cycle. In FIG. 7, the growth area 350 is moved through the
farm 700 during a growth cycle. At a first location 701, the
illumination setup is adapted to a small growth area 350. When the
plants grow and the size of the growth area 350 is adapted
accordingly, the growth area 350 is moved to the next location 702
equipped with more light fixtures 110.
[2284] FIG. 8 shows a schematic block diagram of a controlled
agricultural system 100 according to the disclosure. The controlled
agricultural system 100 comprises a computing device 140, a data
storage device 170, coupled to the computing device 140, an
actuator device 310, coupled to the computing device 140 via a
control unit 320 and a hydroponic arrangement 800 (see also FIG.
10). The data storage device 170 or even the computing device 140
may be based locally (on-site), in a network or the cloud.
[2285] The data storage device 170 comprises a database with data
of control parameters for controlling the hydroponic arrangement
800. Based on the data stored in the data storage device 170, the
control parameters may be adjusted by means of the actuator device
310. To this end, the computing device 140 is configured to control
the water flow in the waterway of the hydroponic arrangement 800
(see also FIG. 10). Furthermore, the computing device 140 is
configured to control grow parameters like nutrient concentration
and illumination. Therefore, the actuator device 310 may comprise
various actuators for adjusting the various parameters, e.g., water
inlet, water sink, water grid, nutrient dosing feeder, light
fixture, etc.
[2286] Optionally, the controlled agricultural system 100 further
comprises a sensor device 150, coupled to the computing device 140
via a second control unit 810 (encircled with dotted line), for
sensing control parameters of the hydroponic arrangement 800,
and/or monitoring the status of the growth of the plants 902 (see
also FIG. 9). Therefore, the sensor device 150 may comprise various
sensors for, e.g., the flow speed, the temperature, the light, the
color of the plants, or cameras for imaging methods, etc.
Furthermore, the computing device 140 may (re)adjust parameters of
the hydroponic arrangement 800 based on the data of the sensor
device 150. For example, the computing device 140 may adjust the
water inlets 1030 and/or the grids 370, 371 and/or the illumination
based on the growth status detected by the sensor device 150.
[2287] Furthermore, the information about the growth status of the
plants 902 or the status of the hydroponic arrangement 800 may be
delivered to the user or customer by a user interface (UI) 401,
e.g. a control terminal coupled to the computing device or a mobile
device such as a smartphone or tablet including a dedicated
application (i.e. app for mobile devices).
[2288] FIG. 9 schematically shows a grow field 900 according to an
embodiment of the disclosure. The grow field 900 comprises a
carrier 901 and plants 902 (four plants per grow field in this
example). The sides 903 of the carrier 901 are grid-like in order
to let in water and hold back the grow material (not shown). As
shown in FIG. 9 (and FIG. 10) the carrier 901 of the grow field 900
is formed like a raft for floating on the water without tilting
over.
[2289] In an alternative embodiment, the grow field may resemble
the form of a tray (or trolley) with wheels, configured for rolling
on the bottom of the water tank (not shown). The tray may have
grid-like sides in order to let in water and hold back the grow
material.
[2290] FIG. 10 schematically shows a hydroponic arrangement 800
according to an embodiment of the disclosure. In addition to FIG.
9, reference is made to FIG. 10 for the following description. The
hydroponic arrangement 800 comprises a water tank 1010, which
provides the waterway, grow fields 900 and agricultural light
fixtures 110.1-110.3. The water tank 1010 further comprises water
inlets 1030 for establishing a flow on the surface 1040 of the
water. The direction of the flow is indicated by the arrow F. The
flow direction F defines a start 1050 and an end 1060 for the grow
fields 900 floating on the surface 1040 of the water inside the
water tank 1010. Furthermore, the water tank 1010 comprises grids
1070, 1071 that are able to stop the grow fields 900 from further
floating with the flow of the water, without stopping the flow of
the water itself. Furthermore, the grids 1070, 1071 may be arranged
on the water surface 1040 in order to define two or more separate
grow areas 1080-1082. Dedicated light fixtures 110.1-110.3, which
may emit light with different spectra and/or intensity, may be
arranged above each of the grow areas 1080-1082 supporting
dedicated growth cycles. At the end of a growth cycle, the grids
1070, 1071 may be removed from the surface, for instance upwards or
downwards, to enable floating of the grow fields 900 to the next
grow area and eventually to the final position, e.g. end 1060, for
harvesting.
[2291] The hydroponic arrangement may also comprise a sink for
removing the water added by the inlets (not shown).
[2292] FIG. 11 schematically shows the steps 1100 of the method for
agricultural management according to the disclosure. For the
following description, in addition to FIG. 11, reference is made to
FIGS. 8 to 10. The method comprises the following steps: [2293]
Step 1110: Planting plants in the grow fields 900; [2294] Step
1120: Putting the grow fields 900 at a first position 1050 on the
water surface of the waterway 1010 of the hydroponic arrangement
1000; [2295] Step 1130: Adjusting the control parameters of the
hydroponic arrangement by means of the actuator device 310 and
based on respective data of the parameters retrieved from the data
storage device 170, with the goal that the plants are ready for
harvest when they arrive at the end 1060; [2296] Step 1140: Moving
the grow fields 900 on the water surface from the first position
1050 downstream to the end 1060 of the waterway 1010; [2297] Step
1150: removing the grow fields 900 from the water surface at the
end 1060 of the waterway 1010.
[2298] In step 1120, the first position and the end position may be
the start or end of the waterway (as indicated in FIG. 10),
respectively, or any other two locations in between separated from
each other by a distance suitable for the growth and/or ripening
time of the plants. In some embodiments/implementations, the
distance and/or moving speed of the grow fields may be adapted to
respective plant species.
[2299] In step 1130, control parameters of the hydroponic
arrangement may comprise, for example, water flow, illumination
(intensity, spectrum), controlling of the grids, concentration of
nutrients in the water of the waterway, temperature of the water
and/or ambient air.
[2300] In step 1140, moving of the grow fields 900 may be performed
by floating on the water due to water flow or any other means that
enable moving on the water surface, e.g. rolling along the ground
of the waterway by means of a trolley carrying the grow fields. The
grow fields 900 may continuously float from the start (first
position) to the final position. The grow fields 900 may also be
stopped at least once for some time, e.g. until a growth cycle is
finished. During a growth cycle the grow parameter, e.g. plant
illumination, nutrient concentration, temperature, may be
specifically adapted.
[2301] In step 1150, the grow fields may be removed automatically
from the water when they arrive at the final position by means of a
suitable actuator. Furthermore, fruits may also be harvested
automatically. Finally, the computing system may be configured to
inform the user of the controlled agricultural system and/or a
third party about the finished growth of the plants or ripening of
the fruits.
[2302] Optionally, the method may comprise the additional step 1160
(marked with dotted line): [2303] Sensing the growth status of the
plants by means of the sensor device 150. Furthermore, the
parameters of the hydroponic arrangement 800 may be readjusted
according to the sensed growth parameter.
[2304] The growth parameters sensed may comprise the size, shape
and color of the plants including their flowers, buds or
fruits.
[2305] Furthermore, the computing system may be configured to
inform the user of the controlled agricultural system and/or a
third party about the sensed growth status.
[2306] FIG. 12 shows a controlled agricultural system 100 according
to the disclosure. It comprises a plurality of growth zones 1200
connected with each other along a processing line 1210. Trays 1220
can be fed to the processing line 1210, beginning with the first
growth zone 1200.1 thereof. As the trays 1220 pass the growth zones
1200.1-1200.5 one after the other, plants 902 grown in the trays
1220 grow successively. In each growth zone 1200.1-1200.5, the
growth conditions are adapted to a specific growth stage, for
instance in terms of temperature, nutrition, humidity or the
like.
[2307] In particular, a specific lighting can be applied at each of
the growth zones 1200, namely a specific light recipe. Each growth
zone 1200 is equipped with a light fixture 110, each of them having
a plurality of LED light sources (not shown). Each of the light
fixtures 110 is equipped with a sensor device 150, in this case a
camera imaging the respective tray 1220. Further, each tray 1220 is
equipped with a sensor device 160, comprising a light sensor and a
temperature sensor in this case. With this setup, growth data of
the plants 902 can be captured.
[2308] Additionally, the agricultural system 100 comprises a
treatment location 1230. Some of the trays 1220 moved along the
processing line 1210 are unloaded from the processing line 1210 to
the treatment location 1230. For instance, the sensor devices 150,
160 can detect a deviation from a target value, for example
regarding the size of the plants 902 or any other parameter, see
the description above in detail. The trays 1220.1 unloaded to the
treatment location, namely the plants 902.1 growing in these trays
1220.1, can be subjected to a specific treatment, for instance in
term of lighting, temperature, gas absorption or the like, see the
description above.
[2309] In the example shown here, the treatment location 1230 is
divided into two subregions 1230.1, 1230.2. In the subregions
1230.1, 1230.2, different treatment conditions can be applied. Each
subregion 1230.1, 1230.2 is equipped with a light fixture 1231
comparable to the growth zones 1200.
[2310] After unloading the trays 1220.1 from the processing line
1210 and treating the plants 902.1 in the treatment location 1230,
the trays 1220.1 can be reloaded to the processing line 1210,
either to the first growth zone 1200.1 (hatched line to the left)
or to the growth zone 1200.3 (hatched line in the middle).
[2311] FIG. 13 shows a vertical setup, the growth zones
1200.1-1200.4 are arranged one above the other in a vertical farm.
For moving the trays 1220 from one growth zone 1200 to the
following one, an elevator 1340 is provided. Further, a treatment
location 1230 is provided above the growth zones 1200. In case that
a deviation is detected by the sensor devices 150, 160, the
respective tray 1220 is unloaded from the processing line 1210 to
the treatment location 1230, see the description above.
[2312] FIG. 14 shows a schematic block diagram of a controlled
agricultural system 100 for a plant growing facility (not shown),
according to the disclosure. The controlled agricultural system 100
comprises a user interface 401 for exchanging information between a
user and the controlled agricultural system 100, a computing device
140, a data storage device 170, coupled to the computing device 140
and a first sensor device 150, coupled to the computing device 140
via a first control unit 810, and a second sensor device 160,
coupled to the computing device 140 via a second control unit 1400.
The numeral 1430 designates the plants equipment.
[2313] Each of the sensor devices 150, 160 may comprise a group of
specific sensors that may be positioned at various locations of the
plant growing facility. Two sensor devices 150, 160 are shown in
FIG. 16 for exemplary reasons only. The controlled agricultural
system 100 may also comprise only one sensor device or more than
two sensor devices, i.e. three or many (sensor device system).
[2314] The sensor devices may comprise ambient sensors measuring
temperature, humidity, leaf temperature, VPD (vapor pressure
deficit), substrate moisture, substrate temperature, EC and
pH-value, air and water velocity, PAR but also camera imaging
solutions, including hyper-imaging solutions, sensors for chemical
analysis, sensors for spectroscopy and reflectivity of
electromagnetic radiation, Doppler (sound and ultrasound) sensors
for plant movement measurement, Lidar sensors for measurement of
plant morphology, sensors for measuring photoacoustic effects
inside a plant leaf. For instance, each sensor of one group of
sensors (e.g. sensor device 150) may be able to measure temperature
and humidity. The sensors of another group of sensors (e.g. sensor
device 160) may be cameras for taking images of the plants.
[2315] In an advantageous refinement of the disclosure, the
controlled agricultural system 100 further comprises an actuator
device 310, coupled to the computing device 140 via a dedicated
control unit 320 (encircled with dotted line).
[2316] The data storage device 170 or even the computing device 140
may be based locally (on-site), in a (centralized) network or the
cloud. Furthermore, the data storage device 170 may also be
integrated into the computing device 140 or network/cloud based.
The data storage device 170 may include a (digital/online-)
platform, e.g. located in the cloud. The platform may also be
accessible by mobile devices, e.g. laptop PC, tablet PC or
smartphones via dedicated apps. Therefore, a user (grower/operator
of the controlled agricultural system) may access the platform via
the computing device 140 or a separate device (not shown).
Furthermore, the platform may comprise dashboards customized to
various user groups such as growers and customers.
[2317] In the data storage device 170, data about the plant growing
facility (e.g. layout, size, placement of lighting fixtures,
actuators, etc.) and the sensor devices 150, 160 (e.g. types of
sensors in the groups, number of sensors per group, etc.) are
stored. The data may be entered via the user interface 401 or
uploaded otherwise.
[2318] The computing device 140 is configured to access and control
the sensor device system 150, 160 and the data storage
device/platform 170.
[2319] Furthermore, the computing device, is configured to manage
the positioning and re-positioning of the sensors of the sensor
devices 150, 160 for monitoring the plant growth and, optionally,
the status of the plant growth facility (e.g. for the maintenance
of the equipment used in the plant growth facility) based on the
data stored in the data storage device/platform 170. Managing the
(re-)positioning of the sensors may comprise suggesting a pattern
for positioning the sensors.
[2320] FIG. 15 schematically shows the steps 1500 of a method for
agricultural management according to the disclosure. The method
aims to evaluate and suggest the positioning of sensors for
monitoring the growth status of plants in a plant growing facility.
For the following description, in addition to FIG. 15, reference is
made to FIG. 14. The method comprises the following steps:
[2321] Initial/Reconfiguration Setup Phase 1501 [2322] Step 1510:
Uploading the layout of the plant growth facility into the data
storage device 170; [2323] Step 1520: Entering data of the
available sensors of the sensor device system 150, 160 into the
data storage device 170; the data including type, position and
orientation of the individual sensors, [2324] Step 1530: Rendering
a digital model of the plant growing facility (digital facility
twin) including indicating the positions and orientations of the
available sensors by means of the computing device 140 based on the
data input of steps 1510 and 1520; [2325] Step 1540: Positioning
the sensors in the real plant growing facility according to the
positioning (and orientation) suggested in the model; [2326] Step
1550: Measuring and collecting data by means of the sensors; [2327]
Step 1560: Analyzing the data measured and collected during step
1550 and suggesting an operating phase setup for the sensors by
means of the computing device 140;
[2328] Operating Setup Phase 1502 [2329] Step 1570: (Re-)
Positioning the sensors according to the operating phase setup
suggested in step 1560; [2330] Step 1580: Measuring and collecting
data by means of the sensors.
[2331] The steps 1510 to 1560 of the initial/reconfiguration setup
phase 1501 may be repeated, at least in part, in case of changes to
the plant growing facility (reconfiguration), e.g. resizing of
growing space, changing the equipment, level of plant maturity,
and/or in case of changes to the cultivated plant variety.
[2332] The step 1520 may comprise the number and types of the
available sensors. The data may be entered via a user interface
401, e.g. a dashboard, or automatically, e.g. wirelessly.
[2333] As an alternative to the steps 1530 and 1540, the sensors
may be positioned according to similar facility setups stored in
the data storage device 170 (database/platform).
[2334] The steps 1530 to 1560 may be conducted section-wise if the
number of available sensors is insufficient to adequately cover the
whole facility in only one measurement run.
[2335] In the steps 1560 to 1570, the setup/positioning of the
sensors for the operating phase may be the same as for the
initial/reconfiguration phase or modified. The step 1560 may
comprise different sensor setups for different seasons. It may also
comprise the supplemental steps of indicating missing sensors or
how additional sensors could help to accelerate, improve, or
optimize the growth process. Furthermore, it may comprise guidance
for correctly installing and using different sensors.
[2336] In the step 1570, the sensors may be installed permanently,
at least for the duration of a growth phase. However, the sensors
may as well be adapted to changing conditions, e.g. the position
and/or orientation of a sensor may be adapted to the growing
plants. The step 1570 may comprise using mobile devices like
drones, robots or humans equipped with sensors for temporary
measurements. For example, a mobile device equipped with a camera
may help to clarify whether the measured high humidity has already
caused fungi growth in the area affected by high humidity. Such
timely clarification may help to prevent the spread of diseases or
pests.
[2337] The step 1580 may comprise a visual/graphical representation
of the measured and collected sensor data for monitoring the growth
status of the plants and/or the equipment of the facility, e.g. by
using the digital model of the facility according to step 1580.
[2338] FIG. 16 schematically shows an example 1600 for a setting of
sensors 1610 in a greenhouse 1620 (plant growing facility, e.g.
tomato greenhouse). The pattern for positioning the sensors 150
correlates with relevant measuring points for measuring the leaf
temperature of tomato plants.
[2339] FIG. 17 shows a schematic block diagram of a controlled
agricultural system 100, according to the disclosure. The
controlled agricultural system 100 comprises a computing device
140, a data storage device 170, coupled to the computing device
140, three groups of agricultural light fixtures 110.1-110.3
coupled to the computing device 140 via respective control units
120.1-120.3 a sensor device 150, coupled to the computing device
140 via a control unit 140 and an actuator device 310, coupled to
the computing device 140 via another control unit 320. The numerals
902.1-902.3 designate plants in different phases or growth
stages.
[2340] The data storage device 170 or even the computing device 140
may be based locally (on-site) or in a (centralized) network or the
cloud. Furthermore, the data storage device 170 may also be
integrated into the computing device 140. The data storage device
170 may include a (digital/online-) platform, e.g. located in the
cloud. The platform may also be accessible by mobile devices, e.g.
laptop PC, tablet PC or smartphones via dedicated apps. For a user,
a user interface 401 to access the platform via the computing
device 140 or a separate device (not shown) is provided.
Furthermore, the platform may comprise dashboards customized to
various user groups such as growers and customers.
[2341] The data storage device 170 comprises a database in which
growth settings, including light recipes, for various plants
species, growth stages, dwell times, On-Off-cycle, and the like,
are stored. The database may also comprise the specifications and
features of various agricultural lighting fixtures, including
lighting fixture-related and lighting fixture-plant related data
sets. Furthermore, the database may comprise data documenting
previous plant projects, e.g. from other growers using the same
platform. The data storage device 170 may also comprise software
programs, particularly the light recipe design tool (LRDT), which
can be uploaded into and executed by the computing device 140.
[2342] The sensor device 150 may comprise sensors for monitoring
and detecting the growth status of the plants, e.g. one or more
cameras, or one or more thermos sensors.
[2343] The actuator device 310 may comprise means for moving the
plants inside the agricultural facility according to the workflow,
for example a motor driving a conveyor belt.
[2344] The computing device 140 is configured to control the groups
of agricultural light fixtures 110.1, 110.2, 110.3 and the actuator
device 310 based on the data stored in the data storage device
170.
[2345] Furthermore, the computing device 140 is configured to
analyze the data from the sensor device 150, thereby monitoring the
growth status of the plants, and, particularly, detecting various
growth phases.
[2346] In some embodiments/implementations, the computing device
140 is configured by uploading and executing the LRDT software
program.
[2347] In an exemplary embodiment of the disclosure, each of the
three groups of agricultural light fixtures 110.1, 110.2, 110.3 is
dedicated to a different growth phase 1712, 1722, 1732. In other
words, the first group 110.1 is dedicated to the first growth phase
1712, the second group 110.2 is dedicated to the second growth
phase 1722, and the third group 110.3 is dedicated to the third
growth phase 1722. The controlled agricultural system 100 may
comprise less than three groups of dedicated agricultural light
fixtures or more than three groups, depending on the number of
dedicated growth phases. For more details of the present
embodiment, reference is now made to FIG. 18.
[2348] FIG. 18 schematically shows an exemplary illumination setup
1800, according to the disclosure. A first group 1820 of
agricultural light fixtures comprises the luminaire type SPYDR (LED
Grow Light) of the company Fluence Bioengineering, Inc. This type
delivers a light intensity of up to 250 .mu.mol/m.sup.2/s and a
specific spectrum (PhysioSpec). A second group 1830 of agricultural
light fixtures comprises the luminaire type VYPR (LED Grow Light;
Fluence Bioengineering, Inc.). This type delivers a light intensity
of up to 300 .mu.mol/m.sup.2/s and a specific spectrum (PhysioSpec
Indoor), too. A third group 1840 of agricultural light fixtures
comprises the luminaire type VYPR.times.Plus (LED Grow Light;
Fluence Bioengineering, Inc.). This type delivers a light intensity
of up to 320 .mu.mol/m.sup.2/s and another specific spectrum
(AnthoSpec). The fixture-related data sets as well as the dynamic
light recipes for controlling each group 1820, 1830, 1840 of
agricultural light fixtures are stored in the data storage device
170. Each group 1820, 1830, 1840 is arranged above a dedicated
cultivating zone. Each zone corresponds to a different growth
phase.
To summarize the conditions in the zones: Zone 1 (group 1820):
[2349] Luminaire Type: SPYDR
[2350] Intensity: 250 .mu.mol/m.sup.2/s
[2351] Spectrum: PhysioSpec
[2352] Dwell Time: 21 days
Zone 2 (group 1830):
[2353] Luminaire Type: VYPR
[2354] Intensity: 300 .mu.mol/m.sup.2/s
[2355] Spectrum: PhysioSpec Indoor
[2356] Dwell Time: 21 days
Zone 3 (group 1840):
[2357] Luminaire Type: VYPR.times.Plus
[2358] Intensity: 320 .mu.mol/m.sup.2/s
[2359] Spectrum: AntoSpec
[2360] Dwell Time: 21 days
For more details of the setup of the agricultural facility and the
workflow, reference is now made to FIG. 19.
[2361] FIG. 19 shows a schematic block diagram of an agricultural
facility 1900 according to an embodiment of a controlled
agricultural system. The cultivated area 1910 of the agricultural
facility 1900 comprises three rows 1911, 1912, 1913 (plant
production lines) of plant units 1920. The plant units 1920
comprise plants and a carrier (not shown), in which the plants are
arranged. The carriers may be movable trays, tables, trolleys, etc.
The plant units 1920 are moved along the plant production lines
1911, 1912, 1913, e.g. by means such as a conveyor belt, from start
1960 (day 1) to end 1970 (e.g. day 63), i.e. in FIG. 19 from left
to right (see arrows 1950), during the growth of the plants,
thereby defining the direction 1950 of the workflow/crop (plant)
flow.
[2362] The three rows 1911, 1912, 1913 are separated by two main
corridors 1940, which are accessible via entrance doors 1930.
Furthermore, each row 1911, 1912, 1913 is grouped into three zone
Z1, Z2, Z3 along the workflow 1950. In the first zone Z1 the plants
are illuminated with agricultural light fixtures of the first group
1820. In the second zone Z2 the plants are illuminated with
agricultural light fixtures of the second group 1830. In the third
zone Z3 the plants are illuminated with agricultural light fixtures
of the third group 1840. The dwell time for the plants in each zone
is 21 days, which sums up to a total of 63 days from start 1960 to
end 1970.
[2363] In some embodiments/implementations, the setup of the
agricultural facility 1900 is designed by means of the method for
agricultural management according to the disclosure, in some
embodiments/implementations aided by the computing device 140
executing the LRDT software program.
[2364] FIG. 20 schematically shows the steps 2000 of a method for
agricultural management according to the disclosure. The method
aims to evaluate and suggest the setup of an
agricultural/horticultural facility 1900 (or a part of such a
facility), based on the plant species and the layout of the
facility 1900. For the following description, in addition to FIG.
20, reference is made to FIGS. 17 to 19. The method comprises the
following steps:
[2365] Initial/Reconfiguration Setup Phase 2001 [2366] Step 2010:
Uploading the layout of the agricultural facility 2000 and the
workflow into the data storage device 170; [2367] Step 2020:
Entering data of user demand (e.g. plant species) into the data
storage device 170; [2368] Step 2030: Fetching a light recipe
appropriate for the user demand, including the lighting
fixture-related and lighting fixture-plant related data sets from
the database stored on the data storage device 170; [2369] Step
2040: Rendering a light recipe design (LRD) by proposing a setup of
the facility 1900 including its equipment (lighting fixtures,
actuators, sensors, etc.), which setup is adapted to the fetched
light recipe and the workflow, by means of the computing device 140
based on the data of steps 2010 to 2030;
[2370] Operating Setup Phase 2002 [2371] Step 2045: Implementing
the light recipe design (LRD) in the facility 1900; Step 2050:
Measuring and collecting data by means of the sensor device 150;
[2372] Step 2060: Controlling the workflow in the facility 1900 by
means of the actuator device 310 and the computing device 140 based
on the LRD and the data of step 2050.
[2373] In the steps 2010 to 2040, the computing device 140 is
configured by uploading and running the light recipe design tool
(LRDT).
[2374] The step 2010 may comprise upload of layouts or pictures,
grouping of zones/production stages, insert of dwell (delay or
rest)) times, available equipment like sensors, actuators, lighting
fixtures, etc.
[2375] In the step 2020, the user demand may comprise bio-mass,
post-harvesting treatment, environmental conditions, etc.
[2376] In the step 2030, the LRD may cover the entire plant
treatment time for the grower's facility, taking into account the
size of the facility, the size of the plants in each growth stage
(growth phase), the time the plants remain in each grow stage, the
number of grow stages and the like.
[2377] The step 2040 may comprise indicating the space required for
each grow stage and where to put lighting fixtures, which types of
lighting fixtures and the respective configuration (spectrum,
intensity), as well as the appropriate velocity (or stand-still
time) of plants.
[2378] Step 2045 may comprise setting up the facility 1900
according to the LRD, including allocating the space required for
each grow stage/phase, arranging the lighting fixtures with proper
configuration (spectrum, intensity, On-Off-cycles), respectively,
dwell times of the plants in the respective zones, etc.
[2379] Step 2050 may comprise detecting the growth status of the
plants, which may be used to adapt the timing for moving the plants
1920. Particularly, a change in the growth phase, which may trigger
moving the respective plants to the next zone or eventually
harvesting. Alternatively, the plants may be moved according to a
fixed, pre-defined schedule, which may obviate the need for sensing
the growth status of the plants and, hence, step 2050. The schedule
for moving the plant units 1920 may be stored in the data storage
device 170.
[2380] Step 2060 may comprise moving plants along the workflow,
i.e. within a zone or even from one zone into the next zone. Step
2060 may further comprise controlling the lighting fixtures 110.1,
110.2, 110.3 according to the respective light recipe design (LRD).
Step 2060 may further comprise additional measures, particularly
for influencing environmental/growth parameters such as
temperature, irrigation, ventilation, fertilization, etc.
[2381] Plant Health/Growth
[2382] FIG. 21 shows a block diagram of an exemplary embodiment of
a controlled agricultural system 100 for prevention of diseases and
pests. It comprises a computing device 140, a data storage device
170, a control unit 130, a first sensor device 150.1, a second
sensor device 150.2, an actuator device 310 and a bus system 180.
The aforementioned components interchange data and signals via the
bus system 180. In an alternative computer architecture, the sensor
devices, the data storage device and the control unit for the
actuator device are directly connected to the computing unit (not
illustrated). The first sensor device 150.1 is configured to
measure environmental parameters (environmental data), for example
air temperature and humidity, and it may comprise a plurality of
different sensors. The second sensor device 150.2 is configured to
acquire the state of the plants (plant data). To this end, it may
comprise a plurality of different sensors, for example also imaging
sensors such as cameras. The sensor data are stored in the data
storage device 170 and analyzed by the computing device 140 as to
whether there is an (elevated) risk of the plants being afflicted
by disease or becoming infested by pests. If this is the case, the
computing device 140 introduces suitable countermeasures. The
control unit 130 converts the commands of the computing device 140
into control signals that are suitable for the actuator device 310.
The actuator device 310 is configured to carry out the
countermeasures for removing or at least reducing an elevated risk.
To this end, the actuator device 310 may comprise a plurality of
different actuators, for example a plant light fixture with
different light sources, UV radiation sources, ventilators,
heating/cooling, apparatuses for fighting pests, apparatuses for
releasing useful creatures for plants, or else apparatuses for
applying pesticides, fertilizers, water, etc., and any combination
of the actuators. The computing device 140 is configured to
establish the effects of the countermeasures on the plants by
analyzing the data from the second sensor device 150.2 (plant
data).
[2383] FIG. 22 shows a schematic flow chart 2200 of the method for
agriculture according to the disclosure. Reference is also made to
FIG. 21 below. Relevant environmental parameters are measured using
the first sensor device 150.1 (step 2201) and stored in the data
storage device 170. From there, the measurement data (environmental
data) are read by the computing device 140 and an analysis is
carried out as to whether a critical situation is present (step
2202), for example if the dew point is undershot in the vicinity of
the plants. If so, suitable countermeasures are proposed to the
user or else directly introduced in automated fashion (step 2203);
for example, dry air is supplied or the air temperature is
increased (if countermeasures are introduced automatically, the
user can then be informed about this). Further countermeasures may
include, for example, a change in the light recipe for the plants,
UV or (N)IR irradiation, supply of pesticide, fertilizer, etc. The
effects of the countermeasures on the plants are checked on the
basis of the measurement data of the second sensor device 150.2
(plant data) (step 2204). If (negative) effects can be seen (step
2205, YES), the countermeasures are reduced or stopped entirely
(step 2206). If not (step 2205, NO), the environmental parameters
are checked again (step 2207), i.e., in the aforementioned example,
there is a check whether the dew point is still undershot or else
whether it has been exceeded again. If the situation is no longer
critical (step 2208; NO), the countermeasures are stopped (step
2209). If the situation continues to be critical (step 2208; YES),
the countermeasures are continued (step 2210) and there is a return
to step 2204 (checking the effects of the countermeasures on the
plants).
[2384] FIG. 23 shows a schematic block diagram of a controlled
agricultural system 100, according to the disclosure. The
controlled agricultural system 100 comprises a computing device
140, a data storage device 170, coupled to the computing device 140
and a sensor device 150, coupled to the computing device 140 via a
first control unit 130.1. In an advantageous refinement of the
disclosure, the controlled agricultural system 100 further
comprises an actuator device 310, coupled to the computing device
140 via a second control unit 130.2 (encircled with dotted line).
The data storage device 170 or even the computing device 140 may be
based locally (on-site), in a network or the cloud. The sensor
device 150 may comprise an imaging system, e.g. a still or video
camera, in some embodiments/implementations a TOF camera or stereo
camera, a lidar system, environmental sensors, e.g. for measuring
the temperature, humidity and/or chemical composition of the air or
soil, sensors for detecting color changes of the plant,
particularly of the leaves, sensors for detecting specific gases
exhaled by the plants, sensors for detecting the fluorescence
emitted by the plants after activation with dedicated radiation.
The computing device 140 compares the data measured by the sensor
device 150 with respective reference data stored in the data
storage device 170.
[2385] The comparison and analysis of the data may involve picture
recognition algorithms, e.g. deep learning, to detect changes in
the morphology or other characteristics of the plants. Artificial
Intelligence may be used to identify the cause of the changes, for
instance, environmental induced stress, plant diseases or pests.
Measured data from a multitude of various sensors may be compared
and analyzed to improve the reliability of the result of the
analysis. For example, possible causes for changes in the
morphology of the plants may be further pinpointed by supplemental
environmental data of the air and/or soil. The result of the
analysis is delivered to the user of the system (e.g. farmer). The
delivered result may comprise different levels of warning to the
user depending on the stress level, disease, pest or other critical
condition detected. The result may be delivered to the user by a
user interface 101, e.g. a control terminal coupled to the
computing device or a mobile device such as a smartphone or tablet
including a dedicated application (i.e. app for mobile
devices).
[2386] Optionally, the measurements may be triggered only after
reference conditions for a specific plant variety have been
established, particularly regarding the illumination of the plants,
because different illuminations (color or intensity) may affect the
leaf morphology and also the measured data differently, causing
inconsistent results. Furthermore, dedicated illumination scenarios
may be used for detecting stress of the plants by measuring the
reaction of the plants to specific illumination. For the purpose of
illumination, the actuator device 310 comprises at least one light
fixture with at least one light source. In some
embodiments/implementations, the light fixture comprises several,
different light sources configured to enable various light recipes.
The light fixture may also comprise sources for emitting radiation
that activates the plants to emit fluorescence radiation. In
particular, changes in the chlorophyll-fluorescence may indicate
plant diseases or detrimental ambient conditions, because they
influence photosynthesis of the affected plants.
[2387] Furthermore, controlled agricultural system 100 may be
configured to automatically counteract by means of the actuator
device 310, if the analysis of the measured data by means of the
computing device 140 results in the identification of stress,
disease, pest or any other critical condition of the plants. For
this purpose, the actuator device 310 may comprise, for instance,
agricultural lighting devices configured to enable various light
recipes, particularly light recipes that ease plant stress,
radiation sources able to emit ultraviolet (UV) radiation, e.g. 250
to 300 nm, irrigation systems, ventilation systems, heating/cooling
systems, feeders for dosing fertilizers, pesticides etc.
[2388] FIG. 24 shows changes in leaf orientation and morphology due
to changes of environmental conditions. For instance, leafs of
rhododendrons 2400 uncurl and move from pendulant (hanging
downwards) to horizontal with rising temperatures (2401:
-30.degree. C., leaf curled, pendulant; 2402: -0.5.degree. C., leaf
less curled, moved upwards to diagonal inclination; 2403:
10.degree. C., leaf uncurled, almost horizontal orientation)
(source:
https://scholar.lib.vt.edu/ejournals/JARS/v40n1/v40n1-nilsen.htm).
[2389] FIG. 25 shows a schematic block diagram of a controlled
agricultural system 100, according to an embodiment of the
disclosure. The controlled agricultural system 100 comprises a
computing device 140, a data storage device 170, coupled to the
computing device 140, an illumination device (light fixture) 110,
coupled to the computing device 140 via a control unit 130.1 and a
sensor device 150, coupled to the computing device 140 via a second
control unit 130.2. The data storage device 170 or even the
computing device 140 may be based locally (on-site), in a
(centralized) network or the cloud. Furthermore, the data storage
device 170 may also be integrated into the computing device
140.
[2390] The data storage device 170 comprises a database with a
mapping of plant diseases, diseases-typical discolorations of the
plants 102 (for every growth stage), and the respective
complementary light (Complementary Color Spectrum CCSi). The
computing device 140 is configured to control the illumination
device 110 based on the data stored in the data storage device
170.
[2391] The illumination device 110 is configured to be able to emit
the respective complementary light (Complementary Color Spectrum
CCSi) according to the data stored in the data storage device 170.
Furthermore, the controlled agricultural system 100 is configured
to control the illumination device 110 based on the data of the
database. The illumination device 110 may comprise light sources,
which emit light of at least three different colors, in some
embodiments/implementations red, green and blue to be able to cover
the RGB color-space. Furthermore, the illumination device 110 may
be configured to be able to emit white light or any illumination
needed in an agriculture system to support plant growth. The
illumination device 110 may also be integrated into an agricultural
lighting system.
[2392] The sensor device 150 is configured to be able to detect the
light reflected by the plants 102. The sensor device 150 may
comprise camera or other sensor systems (Photodiode, CCD chips with
filters etc.). Furthermore, the controlled agricultural system 100
is configured to analyze the data from the sensor device 150 and
detect dark areas. The dark areas may correspond with discolored
areas (or spots) on the plants 102, which may be caused by a plant
disease. The dark areas may also correspond, for example, with
fruits that have changed their color due to ripening.
[2393] Furthermore, the controlled agricultural system 100 may
further comprise a user interface 101 for informing the user about
the measurement results. Via the interface 101 the user may also
schedule the measurements. Alternatively, the measurements schedule
may follow an automatic routine, e.g. once a day, week, month.
[2394] FIG. 26 schematically shows the steps 2600 of the method for
an agricultural management according to an embodiment of the
disclosure. More precisely, FIG. 26 shows a method for
detecting/verifying discolored spots of plants based on
complementary illumination, particularly for disease detection. For
the following description, in addition to FIG. 26, reference is
made to FIG. 25. The method comprises the following steps: [2395]
Step 2610: Starting the detect mode of the controlled agricultural
system 100; [2396] Step 2620: Illuminating the plants 102 with
complementary light by means of the illumination device 110; [2397]
Step 2630: Taking pictures of the plants 102 by means of the camera
150; [2398] Step 2640: Analyzing the pictures and identifying dark
spots by means of the computing device 140; [2399] If no dark spots
have been identified: [2400] Step 2650: No further action; [2401]
If dark spots have been identified: [2402] Step 2660: Identifying
the disease that caused the discolored spots by means of the
computing device 140 based on the data stored on the data storage
device 170; [2403] Step 2670: Informing the user by means of the
user interface 101 that discolored spots have been identified and
about the diagnosed disease; [2404] Alternatively or optionally in
addition to step 2670 (encircled with dashed line): [2405] Step
2680: Initiating countermeasures; [2406] Optionally, before step
2620 or after step 2630 (encircled with dashed line): [2407] Step
2611: Illuminating the plants with non-complementary, e.g. white
light, by means of an appropriate illumination device; [2408] Step
2612: Taking pictures of the plants by means of the camera 150;
furthermore, comparing in step 2640 the pictures of step 2612
(dashed arrow) with respective pictures of step 2630 for enhanced
contrast. This additional measure is particularly beneficial if the
discolored spots are (still) small.
[2409] In step 2610, other light sources, such as agricultural
lighting fixtures may be switched off to facilitate the
visualization of the dark spots when illuminating the plants with
the complementary light. If the detection is performed in a
greenhouse, shutters or blinds may be drawn down.
[2410] In step 2620, in order to probe for a specific
discoloration, the plants are illuminated with the respective
complementary light. For instance, to probe for red discolorations
(with an RGB-code of e.g. #FF0000) the plants are illuminated with
a cyan color with the RGB-code of #00FFFF. Therefore, any red spot
will appear dark. Furthermore, the complementary light may comprise
various Complementary Color Spectra CCSi for probing various
discolored spots and associated diseases. The various CCSi may be
applied consecutively, and respective pictures of the plants are
taken with each CCSi.
[2411] In step 2630, instead of taking pictures with a camera,
alternative sensors for visually detecting dark spots may be
employed, e.g. a photodiode or CCD chips with filters.
[2412] In step 2640, the data from the camera or other sensors are
analyzed by means of the computing device 140. Based on the data,
the analysis enables to verify dark spots visualized by the
complementary illumination.
[2413] In step 2660, diseases are identified by means of the
mapping of plant diseases, diseases-typical discolorations of the
plants, and the respective complementary light (Complementary Color
Spectrum CCSi). Therefore, if dark spots are detected under a
specific complementary light CCS, the corresponding disease-typical
discoloration and disease of the plants can be identified from the
mapping.
[2414] In step 2680, the countermeasures may comprise treating the
affected plant(s) with e.g. UV-light, nutrition, medication,
fungicides, pesticides, etc.
[2415] Instead of detecting discolored spots on plants for
verifying diseases, the illumination with complementary light may
be used for detecting (dis)colored areas of the plants that have
other causes, for example, discoloring due to ripening of fruits or
plant stress or pests.
[2416] FIG. 27 schematically shows a color ring 2700 (source:
https://de.wikipedia.org/wiki/Komplement%C3%A4rfarbe). The
complementary colors of the primary colors red (r), green (g), blue
(b) are cyan (C), magenta (M) and yellow (Y), respectively. On the
color ring 2700, the complementary color of any color is
diametrically opposed. For instance, the complementary color of
yellow (Y) can be determined by locating the opposite end of the
diameter 2710, i.e. the color blue (b).
[2417] FIG. 28 schematically shows typical mottling and
discolorations 2810 caused by the Tobacco mosaic virus on the
leaves 2800 of orchids (source:
https://en.wikipedia.org/wiki/File:Tobacco_mosaic_virus_symptoms-
_orchid.jpg).
[2418] FIG. 29 shows a block diagram of an exemplary embodiment of
a controlled agricultural system 100 for identifying and reacting
to diseases and pests. An agricultural light fixture 110 is
connected to an intelligent driver unit 120. The intelligent driver
unit 120 is configured to transmit a signal 102 to the agricultural
light fixture 110. The signal can contain operational parameters to
operate the individual light sources of the agricultural light
fixture 110 or it can enable a fixture-stored lighting program. The
connection between the agricultural light fixture 110 and the
intelligent driver unit 120 may be a wired connection or a wireless
connection. The transmitting signal 102 may conform to a common
communication protocol. The intelligent driver unit 120 is
connected to a control unit 130. The control unit 130 is configured
to transmit a signal 104 to the intelligent driver unit 120. The
signal 102 is based on the signal 104. Optionally, an actuator
device 310 is connected to the control unit 130. The actuator
device 310 may comprise a variety of actuators, e.g. for adjusting
environmental conditions like temperature, humidity, ventilation or
for dosing fertilizer, pesticides etc. The control unit 130 is
connected to a computing device 140, e.g. a computer system.
Furthermore, the computing device 140 is connected to a sensor
device 150. The sensor device 150 comprises a variety of sensors,
e.g. for measuring environmental conditions like temperature,
humidity, ventilation and for detecting the health of the plants,
e.g. an imaging system. Furthermore, the computing device 140 is
connected to a data storage 170. The computing device 140 may also
be connected to a cloud computer network. In the data storage 170
the nominal values of the plant data are stored (reference data).
The computing device 140 is configured to compute a control command
106 based on the comparison of the signal 112 transmitted from the
sensor device 150 and the nominal values stored in the data storage
170.
[2419] FIG. 30 shows a schematic flow chart 3000 of the method for
agriculture according to the disclosure. Below, reference is also
made to FIG. 29. The growing plants and, optionally, the
surroundings thereof (target area) as well are monitored on the
basis of the sensor data from the sensor device 150 (step 3001).
The sensor data, i.e., plant data, for example plant color, plant
form, etc., and optionally data of the ambient conditions, e.g.,
air temperature, air composition, ground composition, etc., are
compared to corresponding intended data (reference values) (step
3002) and possible deviations are detected (step 3003). The
probability for the presence of a disease or the presence of a pest
is established with the aid of the computing device 140 on the
basis of the detected deviations (step 3004). There is a case
discrimination for the further procedure. If the established
probability lies below a first threshold (step 3010), no further
measures are taken up (step 3011). If the established probability
lies between the first threshold and a second threshold (step
3020), an information item is output, for example on a terminal or
mobile appliance, for example a smartphone with an associated app,
to the effect that a disease or infestation by pests may be present
and/or a further analysis is proposed in order to be able to
determine the disease or the infestation with pests more accurately
(step 3021). If the established probability lies above the second
threshold (step 3030), corresponding countermeasures are proposed
(step 3031). Alternatively, the countermeasures are independently
introduced by the computing device 140 by way of the actuator
device 310 and/or suitable actuation of the light fixture 110 (step
3032).
[2420] FIG. 31 shows a schematic block diagram of a controlled
agricultural system 100, according to the disclosure. The
controlled agricultural system 100 comprises a computing device
140, a data storage device 170, coupled to the computing device 140
and a sensor device 150, coupled to the computing device 140 via a
control unit 130. The data storage device 170 or even the computing
device 140 may be based locally (on-site), in a network or the
cloud. The sensor device 150 may comprise various sensors, in some
embodiments/implementations an imaging system, e.g. a still or
video camera, in some embodiments/implementations a TOF camera or
stereo camera, a LIDAR system, environmental sensors, e.g. for
measuring the temperature, humidity and/or chemical composition of
the air or soil or nutrient solvents, sensors for detecting the
color changes of the plant, particularly of the leaves, flowers and
fruits.
[2421] The computing device 140 is configured to identify and count
the flowers and/or buds of the plants in the cultivated area by
means of the data measured by the sensor device 150. The analysis
of the data, particularly the identifying of the flowers or buds,
may involve picture recognition algorithms, e.g. deep learning.
Additionally or alternatively, the computing device 140 is
configured to identify the flowers directly based on the color of
the flowers (e.g. yellow for tomatoes) and the typical size derived
from the pictures, either as an absolute value or relative to the
size of other parts of the plant (e.g. leaves).
[2422] Furthermore, the computing device 140 is configured to
calculate a prediction for the yield of the plants in the
cultivated area by means of the number of flowers and the
respective conversion rate for flowers to fruits. The respective
conversion rates are retrievable from a database stored on the data
storage device 170. Optionally, the computing device 140 is also
configured to calculate a prediction for the harvesting time of the
fruits based on the currently detected status of growth of the
plants and the typical time left until ripening of the fruits.
Typical time schedules for ripening of the fruits may be stored in
the data storage device 170.
[2423] The calculated results, i.e. the forecast of the yield and,
optionally, harvesting time, are delivered to the user of the
system (e.g. farmer) or a customer. The delivered results may
comprise a set of data, including the forecasted yield and
harvesting time, images (shot by still or video camera) or other
graphical representation such as virtual or augmented reality of
the plants. The result may be delivered to the user by a user
interface (UI) 101, e.g. a control terminal coupled to the
computing device or a mobile device such as a smartphone or tablet
including a dedicated application (i.e. app for mobile
devices).
[2424] FIG. 32 shows a schematic flow chart 3200 of the method for
agricultural management according to the disclosure. In addition to
FIG. 2, reference is made to FIG. 1. The method comprises the
following steps: [2425] Step 3210: Detecting the flowers (or buds)
of the plants in the cultivated area by means of the sensor device
150 and the computing device 140; [2426] Step 3220: Assessing the
number of flowers/buds by means of the computing device 140 and
based on the data measured by the sensor device 150; [2427] Step
3230; Predicting the yield by retrieving the respective conversion
rate of the plant species from the data storage device 170 and
weighing the number of flowers assessed in step 3220 above with the
conversion rate by means of the computing device 140; [2428] Step
3240; Delivering the result of the prediction to the user, e.g. a
farmer or a customer who ordered the fruits from the farmer by
means of the user interface 101; [2429] Optionally, the method may
comprise the additional [2430] Step 3250: Predicting the harvesting
time by retrieving the average harvesting time for the respective
fruit (time schedule of ripening) from the data storage device 170
and comparing it with the current state of the ripeness by means of
the computing device 140; the current state of the ripeness is
identified by analyzing the data measured by the sensor device 150
with regard to, e.g., the development of the flowers, the withering
of the flowers, the creation of the fruits, and the different state
of its ripening.
[2431] The accuracy of the prediction of step 3230, and optionally
step 3250, may be improved by measuring and considering additional
environmental data like the temperature, humidity, etc.
[2432] FIG. 33 shows a schematic flow chart 3300 of an alternative
method for agricultural management according to the disclosure. The
method comprises the step 3310 of measuring the biomass by means of
the of the sensor device 150. Based on the measured biomass and
current and/or future environmental data (temperature, humidity,
light intensity, light spectrum . . . ) the yield is predicted by
means of the computing device 140 (step 3320). The result of the
prediction is delivered to the user similar to step 3240 in FIG. 32
(step 3330).
[2433] FIG. 34 shows an image 3400 depicting a detail of a
cultivated area within a greenhouse. Particularly, it shows plants
3410 with yellow flowers 3420 and a bumble-bee 3430 close to a
flower. If the detection system relies only on the color of the
flower to detect a flower, it could mistake a bumble-bee for a
flower. Therefore, it is necessary to also consider the relative or
absolute size of the colored spot in the picture to reduce the risk
of wrong identifications.
[2434] FIG. 35 shows a schematic block diagram of a controlled
agricultural system 100, according to the disclosure. The
controlled agricultural system 100 comprises a computing device
140, and a light fixture 110 coupled to the computing device 140
via a control unit 130 and a driver unit 120. The data storage
device 170 or even the computing device 140 may be based locally
(on-site), in a network or the cloud.
[2435] The data storage device 170 comprises a database with data
of control parameters for controlling the illumination. Based on
the data stored in the data storage device 170, the control
parameters may be adjusted by means of the control unit 130.
Furthermore, the computing device 140 is configured to control grow
parameters like nutrient concentration, via the actuator unit
310.
[2436] The controlled agricultural system 100 further comprises a
sensor device 150, coupled to the computing device 140, for sensing
a fungi infection of the plants. This can for instance be achieved
by a camera in combination with a picture recognition. In case of
downy mildew, the pattern of the damage at infestation can be pale
green or pale yellow spots (chloroses) on the upper surface of the
leaves, often starting from the midrib of the leaf. As the
infection progresses, chlorosis spreads and the first brown spots
appear. At high humidity conditions, on the underside of leaves a
greyish-violet-brown spore lawn is developing. It then comes to
rapid propagation in the plant population, and the leaves die
quickly. In the case of red-leaved varieties the infestation
symptoms are often late to recognize. In small-leaved varieties,
downy mildew usually does not show the typical chlorosis on the
leaf top.
[2437] In another embodiment, chlorophyll fluorescence could be
measured locally on the leaves with a camera. If the fluorescence
is not in the optimum range at a certain location on the leaves,
this might indicate an infection with a fungus. If this is the
case, the treatment with the fungi prevention illumination can be
initiated.
[2438] In another embodiment or additionally to the above, a
thermal camera is used. Areas of the leaves infected by mildew or
other fungi show a temperature that is different from the rest of
the leaf (i.e. the healthy tissue). Usually, the temperature is
elevated by some 0.1 degrees Celsius. Thus it is possible to detect
an infection even before the typical marks of the infection can be
seen on the plants. As soon as leaves show spots of different
temperature, the treatment with the fungi prevention illumination
can be initiated.
[2439] From a biological point of view, the fungus forms oospores,
which release sporangia after germination. These can be spread by
wind, air movements and water splashes (possibly also over the
seeds of the plants). The plants are mainly infected when the
temperatures are between 15 and 25.degree. C. and the air is
sufficiently humid. The spores enter the plant via the stomata and
form a mycelium there. There, the conidiophores (holder of the
conidia) emerge, which grow out of the stomata again and can be
seen as a dark spore lawn on the underside of the leaf. These
conidia are used to distribute the germs in the plantation. Conidia
can germinate even at low temperatures of 5 to 10.degree. C. Other
host plants for downy mildew are sage, savory and other species of
the mint family.
[2440] According to the disclosure, the development or germination
of spores is prevented by illuminating the plants with a fungi
prevention light source 200 during a night phase. It is a part of
the light fixture 110 and emits red light. Additionally, a UV light
source 201 is provided.
[2441] In an exemplary embodiment, the red light at 660 nm is
switched on 2 hours after the night phase has started. Thus, there
is a dark period at the beginning of the night phase. After this
dark period, the red light is switched on at an intensity of 60
.mu.mol/m.sup.2/s for 4 hours. For example, in a day phase/night
phase rhythm of 16/8 hours, the normal light treatment could last
from 06:00-22:00. At 22:00 the 2 hour dark period starts (no
light), and at midnight the fungi prevention time starts and lasts
until 4:00, before a second dark period follows until 06:00 (no
light). This cycle is repeated daily. The fungus requires a certain
dark period duration to trigger the germination/sporulation, which
is interrupted by the fungi prevention illumination.
[2442] In case that the sensor device 150 detects an infection,
nevertheless, an additional UV treatment can be applied with the UV
light source 201. The information about the infection may be
delivered to the user or customer by a user interface (UI), e.g. a
control terminal coupled to the computing device or a mobile device
such as a smartphone or tablet including a dedicated application
(i.e. app for mobile devices).
[2443] FIG. 36 shows a schematic block diagram of a controlled
agricultural system 100, according to the disclosure. The
controlled agricultural system 100 comprises a computing device
140, and a light fixture 110 coupled to the computing device 140
via a control unit 130. The data storage device 170 or even the
computing device 140 may be based locally (on-site), in a network
or the cloud.
[2444] The data storage device 170 comprises a database with data
of control parameters for controlling the illumination. Based on
the data stored in the data storage device 170, the control
parameters may be adjusted by means of the control unit 130.
Furthermore, the computing device 140 is connected to an actuator
unit 310, namely an irrigation device.
[2445] The controlled agricultural system 100 further comprises a
sensor device 150 mounted at the irrigation device, see FIG. 2 in
detail. The sensor device 150 is coupled to the computing device
140. Any information measured by the sensor device 150, for
instance about the growth status of the plants, may be delivered to
the user or customer by a user interface (UI), e.g. a control
terminal coupled to the computing device or a mobile device such as
a smartphone or tablet including a dedicated application (i.e. app
for mobile devices).
[2446] FIG. 37 shows an irrigation device 3700. It comprises a rail
3701 at which a plurality of sensors 3702 are provided. Each sensor
3702, in this case a camera, has a certain field-of-view 3703 onto
a growth area 3704. In this case, the fields-of-view of the
respective sensors are partially overlapping, allowing a
3D-reconstruction of the growth area.
[2447] The irrigation device 3700 is mounted movable at a ceiling
3705, it hangs at a rod 3706 hanging from the ceiling 3705. Via a
rail system (see FIG. 37), the irrigation device 3700 is movable
forth and back over the growth area 3704, namely forward out of the
drawing plane and backward behind the drawing plane. Such an
irrigation device 3700 is known as such. A power supply or data
cable line 3710 connects the sensors 3702 with the control box 3711
of the irrigation device 3700. In particular, the irrigation device
3700 and the sensor device 3702 can share a common power supply
3712.
[2448] FIG. 38 illustrates a possibility for mounting a plurality
of sensor devices 150, namely cameras 3800. The cameras 3800 are
provided at a rail 3801, which extends perpendicularly to the
drawing plane (behind and in front of the drawing plane, further
cameras 3800 are provided at rail 3801). The rail 3801 with the
cameras 3800 is mounted at the rail 3701 with the nozzles 3702.
FIG. 38 shows a sectional plane perpendicular to FIG. 37. For the
mounting, a support bar 3805 with a clamp 3805.1 is clamped over
the rail 3701. In addition, a crossbar 3806 is provided for
stabilization. The power or data line 3710 is led to the cameras
3800 along the bar 3805. Furthermore, a splash guard could be
installed between the cameras 3800 and the nozzles 3702 (not
shown).
[2449] The whole setup is movable over the growth area by an engine
3810, which is guided at a rail 3811. The rail 3811 is mounted at
the ceiling 3705 via a plurality of rods 3706.
[2450] FIG. 39 shows a further possibility for combining an
irrigation and a sensor device. In this case, a profile rail 3900
is provided. At its opposite sides, the profile rail 3900 is formed
with respective recesses 3901.1-3901.4. In the recess 3901.1 at the
upper side, the rod 3706 for the mounting at the ceiling (not
shown) is provided. In the recess 3901.2 on the left, the rail 3801
with the cameras 3800 is mounted. In the recess 3901.3 on the
right, the bar 3701 with the nozzles 3702 is mounted. For the
mounting, a respective transversal bar 3910.1, 3910.2 is placed in
the respective recess 3901.1, 3901.3. In the recess 3901.4 at the
lower side, a light source 3920 can be mounted optionally.
[2451] FIG. 40 shows a schematic block diagram of a controlled
agricultural system 100, according to the disclosure. The
controlled agricultural system 100 comprises a computing device
140, and a light fixture 110 coupled to the computing device 140
via a control unit 130 and a driver unit 120. The data storage
device 170 or even the computing device 140 may be based locally
(on-site), in a network or the cloud.
[2452] The data storage device 170 comprises a database with data
of control parameters for controlling the illumination. Based on
the data stored in the data storage device 170, the control
parameters may be adjusted by means of the control unit 130 (and
the driver unit 120). Furthermore, the computing device 140 is
configured to control grow parameters like nutrient concentration,
via the actuator unit 310.
[2453] The controlled agricultural system 100 further comprises a
sensor device 150 coupled to the computing device 140. According to
the element "LiDAR Plant Surveillance" of the disclosure, the
sensor device 150 is a LiDAR system, see FIG. 41, 42. It is
provided for a morphological measurement of the plants grown on a
growth area.
[2454] The information about the morphology of the plants may be
delivered to the user or customer by a user interface (UI), e.g. a
control terminal coupled to the computing device or a mobile device
such as a smartphone or tablet including a dedicated application
(i.e. app for mobile devices).
[2455] FIG. 41 shows an embodiment with a LiDAR system, namely a
distance measuring device 4100. It is mounted in a greenhouse 4101,
namely at the ceiling 4102 thereof. The distance measuring device
4100 is arranged above a growth area 4103 of the greenhouse 4101,
on which plants 4104 are grown.
[2456] The distance measuring device 4100 is oriented towards the
growth area 4103 so that the plants 4104 lie within the detection
field 4105 of the distance measuring device 4100. In detail, the
growth area 4103 lies within an inner region 4105.1 of the
detection field 4105, in an outer region 4105.2 the distance to the
wall 4106 of the greenhouse 4101 is measured. On the one hand, the
wall 4106 can be used as a reference point, for instance for
aligning a plurality of distance measuring devices 4100 (see FIG.
42). On the other hand, it is possible to adapt the area scanned by
the distance measuring device 4100 such that only the inner region
4105.1 of the detection field 4105 is measured. This can for
instance reduce the measurement and computing effort.
[2457] The distance measuring device 4100 used here is a LiDAR
system which emits infrared laser pulses. Those pulses are
reflected at the plants 4104 (or at any other object in the
detection field 4105). The LiDAR system detects the reflected
pulses (echo pulses), and the distance can be calculated from the
time delay (time of flight) between emission and detection. The
LiDAR system used here has a spatial resolution so that a
three-dimensional distance picture is taken (a three-dimensional
point cloud of distance values). Regarding possibilities for a
technical implementation of the spatial resolution, reference is
made to the description above.
[2458] By the spatially resolved distance measurement, the
morphological structure of the plants 4104 can be evaluated. This
gives information on the plant growth, enabling for instance a
control whether the plants are growing as expected. Depending on
this measurement, external parameters like the lighting,
temperature nutrition and so on can be adjusted.
[2459] FIG. 42 shows a further embodiment, namely also a greenhouse
4101 with a growth area 4103 for growing plants (not shown). At the
ceiling 4102, a plurality of distance measuring devices
4100.1-4100.6 are mounted. With each distance measuring device
4100.1-4100.6, a different section of the growth area 4103 is
measured, and it is measured from different angles. To align the
images taken by the different distance measuring systems
4100.1-4100.6, a reference point 4200 is provided above the growth
area 4103. By aligning the reference point 4200 amongst the
different images taken, one single three-dimensional image of the
growth area 4103 and the plants grown there can be obtained.
[2460] Light/Growth Recipes
[2461] FIG. 43 shows a schematic block diagram of a controlled
agricultural system 100, according to the disclosure. The
controlled agricultural system 100 comprises a computing device 140
and light fixtures 110.1,110.2. In use, the light fixtures
110.1,110.2 illuminate different locations 4305,4306. Each lighting
fixture 110.1,110.2 is provided with a sensor device 150.1,150.2
for measuring a temperature value at the respective location
4305,4306. The sensors device 150.1,150.2 are coupled to the
computing device 140 (in between control units can be provided,
which are not shown). The computing device 140 and a data storage
device 170 assigned may be based locally (on-site), in a network or
in the cloud.
[2462] A different temperature at the different locations 4305,4306
leads to a different growth, in particular to a different Time to
Flower. An object can be to synchronize the growth (simplified
harvesting), namely achieve the same Time to Flower even though the
temperature differs. In particular in vertical farms, a
homogenization of the temperatures would be difficult. Therefore,
the approach of the present disclosure is to compensate the
different temperatures by a different lighting. For this purpose,
the computing device 140 compares the temperature values measured
by the sensor devices 150.1,150.2 with a reference data set stored
in the data storage device 170.
[2463] A corresponding data set can for instance be derived when a
plurality of plants are grown and are, in groups, subjected to a
different temperature and illumination. As a growth parameter, the
Time to Flower (days) can be measured (see the description above
regarding further examples). The following Table shows an
evaluation matrix for Petunia Coral Pink.
TABLE-US-00006 DLI [mol/m.sup.2d] T [.degree. C.] 5 10 15 20 14 80
65 50 42 17 48 40 35 30 20 35 30 28 25 23 30 28 23 20
[2464] Four different DLI values (5, 10, 15, 20 [mol/m.sup.2d]) and
four different temperatures (14, 17, 20, 23 [.degree. C.]) have
been applied, 16 groups having been investigated in total. For
instance, Time to Flower at 23.degree. C. and 5 mol/m.sup.2d is
about 30 days which is comparable to the Time to Flower at
20.degree. C. at 10 mol/m.sup.2d (.about.30 days). This means that
in order to have the same growth rate at 23.degree. C. and
20.degree. C., the DLI ratio must be 1:2.
[2465] Time to flower at 20.degree. C. at 10 mol/m.sup.2d (ca. 30
days) equals same as time to flower at 17.degree. C.: at 20
mol/m.sup.2d: ca. 30 days. This means that in order to have the
same growth rate at 20.degree. C. and 17.degree. C., the DLI ratio
must be 1:2.
[2466] Time to flower at 20.degree. C. at 5 mol/m.sup.2d (gives 35
days) is same as 17.degree. C. at 15 mol/m.sup.2d gives 35 days.
This means that in order to have the same growth rate at 20.degree.
C. and 17.degree. C., the DLI ratio must be 1:3.
[2467] Time to flower at 17.degree. C. at 5 mol/m.sup.2d (gives 48
days) is almost the same as at 14.degree. C. at 15 mol/m.sup.2d
(gives 50 days). This means that in order to have the same growth
rate at 14.degree. C. and 17.degree. C., the DLI ratio must be
1:3.
[2468] These examples illustrate how a different temperature can be
compensated by applying a different DLI in order to achieve the
same Time to Flower. Further, also a spectral adaption of the
illumination is possible, see the description above in detail.
[2469] FIG. 44 shows the process or method in a schematic block
diagram. The measuring 4400 of the temperature values delivers a
temperature profile. The calculation 4401 of the required
illumination (DLI and/or spectrum) is done with a reference data
set as described above. The application 4402 of the different
illumination on that basis can lead to change in temperature again,
which can be considered in a feedback-loop more or less in
real-time. However, on the other hand, the temperature profile may
also be measured only after quite long time intervals like hours,
or only once per day.
[2470] FIG. 45 shows a block diagram of an exemplary embodiment of
a controlled agricultural system 100 with adaptive additional
light. An agricultural light fixture 110 is connected to an
intelligent driver unit 120. The intelligent driver unit 120 is
configured to transmit a signal 102 to the agricultural light
fixture 110. The signal can contain operational parameters to
operate the individual light sources of the agricultural light
fixture 110 or it can enable a fixture-stored lighting program. The
connection between the agricultural light fixture 110 and the
intelligent driver unit 120 may be a wired connection or a wireless
connection. The transmitting signal 102 may conform to a common
communication protocol. The intelligent driver unit 120 is
connected to a light control unit 130. The light control unit 130
is configured to transmit a signal 104 to the intelligent driver
unit 120. The signal 102 is based on the signal 104. The light
control unit 130 is connected to a computing device 140, e.g. a
computer system. Furthermore, the computing device 140 is connected
to a first sensor 150 for measuring and analyzing the light
spectrum of the ambient light (second light). Optionally, the
computing device 140 is connected to a second sensor 160 for
measuring and analyzing the light spectrum of the agricultural
light fixture 110 (first light). The computing device 140 is
configured to compute a signal 106 based on the signals 108, 112
transmitted from the sensor 150.1 (and optionally sensor 150.2) and
the spectrum of the target light. The computing device 140 can be
connected to a cloud computer network 170.
[2471] FIG. 46 shows a schematic flow chart 4600 of the method for
agriculture according to the disclosure. Below, reference is also
made to FIG. 45. In the first step 4601, the spectrum of the
ambient light (second light) in the region to be irradiated is
measured with the aid of the sensor 150. In the next step 4602, the
spectrum of the second light is compared to the target spectrum
(third light) in the computing device 140 on the basis of the
measurement values. From this, the difference spectrum between the
spectrum of the ambient light and the spectrum of the target light
(third light) is established in the computing device 140 in the
next step 4603. In the next step 4604, the light fixture 110 is
actuated according to the previously established difference
spectrum by way of the control unit 130 and the additional light
(first light) with the difference spectrum is produced thus.
Thereupon, the additional light with the difference spectrum is
added to the ambient light (second light) in the region to be
irradiated (target area) (step 4605). Optionally, the difference
spectrum between the second and third light is measured, either
continuously or at intervals, with the aid of the second sensor
4660 in the next step 4606 and, where necessary, the spectrum of
the first light is appropriately corrected 4610 by returning to
step 4604. Otherwise, there is a return (step 4607) to the first
step 4501 after a pre-determinable time duration x.
[2472] FIG. 47 shows a CIE diagram 4700. The area of the
displayable light colors is delimited by the spectral line 4710 and
the purple line 4730. Moreover, the blackbody curve 4720 is also
plotted.
[2473] FIG. 48 shows an illustration 4800 of the color temperatures
of the sunlight. In the column 4810, color temperatures from 10 000
K (top; clear blue sky daylight) to 1000 K (bottom; candle flame)
are presented in 1000 K steps.
[2474] FIG. 49 shows an illustration 4900 of the solar
spectrum.
[2475] FIG. 50 shows an illustration 5000 of a target spectrum for
an application in the horticultural sector.
[2476] FIG. 51 shows a calculated difference spectrum 5100 (as a
basis for the actuation of the LEDs of the first light source
(additional light), subdivided into discrete regions as a rule)
between the solar light spectrum (FIG. 49) and the target spectrum
(FIG. 50).
[2477] Proposed are a controlled agricultural system comprising a
light fixture for spectral complementation of the ambient light and
a method for agriculture for spectrally matching an additional
light to an ambient light with the goal of obtaining a mixed light
in a target area (e.g., plants) by way of the superposition of
ambient light and target light, the spectrum of said mixed light at
least approximately corresponding to that of a target spectrum
(e.g., light recipe for the irradiation of the plants). To this
end, the spectrum of the ambient light is measured (possibly only
in portions) and this is used to establish the difference spectrum
in relation to the target spectrum. Light fixtures designed to this
end are actuated in such a way that the produced additional light
at least approximately has the previously established difference
spectrum. Optionally, the spectrum of the additional light is
measured and compared to the difference spectrum, and the actuation
of the light fixtures is corrected accordingly if required. Using
this, it is possible to take account of changes in the sunlight due
to weather, even in anticipatory fashion, for example.
[2478] FIG. 52 shows a schematic flow chart 5200 of an exemplary
embodiment of the method for agriculture according to the
disclosure using the controlled agricultural system according to
the disclosure (the latter is not shown).
[2479] The sequence of the method starts with the reception of the
change in the delivery date for product of a plant (step 5210).
This is followed by the identification of the affected plants (step
5220), e.g., with the aid of the control unit of the controlled
agricultural system. To this end, the plants or plant units may be
provided with machine-readable identification. This is followed by
the growth status of the identified plants being determined (step
5230). The growth status and profile can be logged in a growth log,
for example, and can be stored on a storage device of the
controlled agricultural system. With the aid of the computing
device of the controlled agricultural system and on the basis of
the growth data obtained above, the modified parameters are
established in the next step 5240 in such a way that this makes the
desired product with the provided quality available at the amended
delivery date. The quality of the product may relate to, for
example, the growth phase of the plants, the degree of maturity of
possible fruit, look, taste, etc. To this end, the computing device
can access a database, which stores appropriate information items
in respect of changing the growth (maturing) of the respective
plant. By way of example, what may be stored there is that the
change of the parameter x for a plant z leads to a delay or
acceleration of the growth (the maturing) by y hours. From this,
the computing device establishes the suitable parameter changes.
Finally, the modified parameters are applied to the corresponding
actuators by the control unit for the established time duration
(step 5250) in order to influence the growth of the affected plants
in targeted fashion. By way of example, these actuators can relate
to the irradiation, i.e., for instance, change the spectrum or the
intensity of a plant light fixture, the ambient temperature, the
water and nutrient supply, etc.
[2480] Proposed are a controlled agricultural system and a method
for agriculture for making the plant growth flexible. If there is a
change in a delivery date for a product of a plant, the affected
plants are initially identified and their growth statuses are
established. From this, the computing device of the controlled
agricultural system calculates modified control parameters for
actuators which influence the plant growth in such a way that it is
optionally delayed or accelerated such that the desired product is
available with the sought-after quality at the amended delivery
date.
[2481] FIG. 53 schematically shows an agricultural light fixture
110 according to an embodiment of the disclosure. The agricultural
light fixture 110 comprises six light modules 5310, e.g. LED
modules, denoted by M1, M2 . . . M6. Each light module 5310 may
comprise one or more light sources (not shown) connected to
respective drivers (not shown). The agricultural light fixture 110
is elongated in shape, and the light modules 5310 are arranged in a
row. The agricultural light fixture 110 may be positioned above a
row of plants or any other arrangement of plants. The light modules
5310 can be controlled individually and are able to emit light with
three different intensities I.sub.3>I.sub.2>I.sub.1.
[2482] Below the agricultural light fixture 110 a first schematic
diagram is shown, which indicates the light intensities I.sub.1,
I.sub.2, I.sub.3 allocated at a time t=t.sub.1 to the respective
light modules 5310. Specifically, at t=t.sub.1 each one of the
modules M1, M5 and M6 is controlled to emit light with the
intensity I.sub.1, modules M2 and M4 are controlled to each emit
light with the intensity I.sub.2, and module M3 is controlled to
emit light with the maximum intensity I.sub.3.
[2483] A second schematic diagram, depicted below the first
schematic diagram, indicates the light intensities I.sub.1,
I.sub.2, I.sub.3 allocated at a later time t=t.sub.2 to the
respective light modules 5310. Now, at t=t.sub.2 the module M4 is
controlled to emit light with the maximum intensity I.sub.1.
Furthermore, modules M3 and M5 are controlled to each emit light
with the intensity I.sub.2, and modules M1, M2 and M6 are
controlled to each emit light with the intensity I.sub.1.
[2484] The two different controlling schemes shown in the two
schematic diagrams of FIG. 1 result in two different intensity
distributions along the agricultural light fixture 110.
Particularly, the maximum light intensity I.sub.3 is moved one
module forward from left to right, i.e. from module M3 to module
M4.
[2485] The controlling scheme may continue in similar manner as
described above until one lighting cycle is complete, i.e. the
modules are controlled such that the maximum intensity I.sub.3 next
moves to modules M5, M6, M1, M2 and, finally, to module M3 again.
Then, the lighting cycle may be repeated. Alternatively, the
lighting cycle may be reversed, i.e. moving the maximum intensity
I.sub.3 from right to left. Furthermore, the lighting cycles of two
or more agricultural light fixture 110 may be synchronized in phase
or out of phase.
[2486] In another embodiment (not shown), the intensity of module
M1 can, once the maximum intensity has moved to the right, be
lowered below its previous value in order to maximize the
phototropic effect.
[2487] In addition or alternatively, as described in the main part
of the description, any light module M1 to M6 may have its own
specific light color temperature that can be changed as a function
of a circadian time schedule and/or light intensity (photoactive
radiation PAR).
[2488] Furthermore, the controlling schemes may be combined with
specific light recipes for respective plant species.
[2489] FIG. 54 shows a schematic block diagram of a controlled
agricultural system 100, according to the disclosure. The
controlled agricultural system 100 comprises a computing device
140, a data storage device 170, coupled to the computing device
140, and the horticultural light fixture 110 according to FIG. 53.
The horticultural light fixture 110 is coupled to the computing
device 140 via a control unit 130, whereby each one of the six
light modules M1 to M6 can be controlled individually.
[2490] Optionally, the controlled agricultural system may further
comprise a sensor device (not shown), coupled to the computing
device via a dedicated control unit and/or an actuator device (not
shown), coupled to the computing device via another dedicated
control unit. The sensor device may comprise sensors for monitoring
and detecting the growth status of the plants, e.g. one or more
cameras, or one or more thermo sensors, etc. The actuator device
may comprise means for irrigation, air-conditioning, fertilization,
etc.
[2491] The data storage device 170 or even the computing device 140
may be based locally (on-site) or in a (centralized) network or the
cloud. Furthermore, the data storage device 170 may also be
integrated into the computing device 140. The data storage device
170 may include a (digital/online-) platform, e.g. located in the
cloud. The platform may also be accessible by mobile devices, e.g.
laptop PC, tablet PC or smartphones via dedicated apps. Therefore,
a user may access the platform via the computing device 140 or a
separate device (not shown). Furthermore, the platform may comprise
dashboards customized to various user groups such as growers and
customers.
[2492] The data storage device 170 comprises a database in which
the controlling schemes for the light modules M1 to M6 are stored.
Furthermore, growth settings, including light recipes, for various
plants species, growth stages, On-Off-cycle, and the like, may be
stored. Furthermore, the database may comprise data of controlling
schemes from previous plant projects, e.g. from other growers using
the same platform.
[2493] The computing device 140 is configured to control the light
modules 110 of the horticultural light fixture 110 via the control
unit 130, based on the data of the controlling schemes stored in
the data storage device 170. Furthermore, as the case may be, the
computing device 140 is configured to control the optional sensor
device and/or actuator device.
[2494] FIG. 55 schematically shows the steps 5500 of a method for
agricultural management according to the disclosure. The method
aims to induce movements in the plants by moving a light intensity
distribution comprising a maximum light intensity across a target
area that is cultivated with plants (one or more). Particularly,
the method may be performed by means of the controlled agricultural
system 100 showed in FIG. 54. The method comprises the following
steps: [2495] Step 5510: Providing multiple light modules, which
can be controlled individually or in groups; [2496] Step 5520:
Arranging the multiple light modules above the plants and
illuminating the target area; [2497] Step 5530: Controlling the
light modules to emit light on the target area having an intensity
distribution that comprises a maximum light intensity for a
selected light spectrum or wavelength range; [2498] Step 5540:
Moving the maximum light intensity within the target area.
[2499] In step 5510, controlling the light modules may mean, for
instance, switching the light modules on and off, changing the
intensity and/or spectrum of the light emitted by the light modules
gradually, continuously or erratically.
[2500] In step 5520, the light modules may be arranged in a row
along an elongated cultivating area.
[2501] In step 5530, at least one light module or at most a subset
of the multiple light modules of the light fixture has to be
controlled such that its light intensity is higher than the light
intensity of at least one other light module illuminating the
target area. For instance, the multiple light modules may be
controlled such that only one light module emits light with the
maximum intensity, i.e. an intensity higher than the intensities of
the light emitted by any other light module of the respective light
fixture. The controlling scheme may than be designed for the
maximum light intensity to move from one light module to another
and so forth.
[2502] In step 5540, moving the maximum light intensity may be
performed by changing the controlling scheme of the light modules
as exemplarily described in the embodiment shown in FIG. 53.
[2503] A Controlled Agricultural System (100) is proposed,
comprising an agricultural light fixture (110) for inducing
movement of the illuminated plants. For this purpose, the
agricultural light fixture (110) comprises multiple light modules
(M1 to M6), which are controllable individually or in groups.
Furthermore, the Controlled Agricultural System (100) is configured
for controlling the light modules such that a light intensity
distribution comprising a maximum light intensity is emitted by the
agricultural light fixture (110), whereby the maximum light
intensity moves from one light module to another light module.
[2504] FIGS. 56a and 56b in each case schematically show, in
comparison for a light recipe, the intensities I of structurally
identical LEDs in different numbers n. In exemplary fashion, FIG.
56a corresponds to the conditions 5600 in a first light fixture
with three LEDs (n=3) of a certain type. Here, the respective
intensities of the three LEDs are set to the value I.sub.1. By
contrast, FIG. 56b corresponds, in exemplary fashion, to the
conditions 5620 in a second light fixture with five structurally
identical LEDs (n=5), i.e., LEDs of the same type but in greater
number. Here, the respective intensities of the five LEDs are set
to the lower value I.sub.2, i.e., I.sub.2<I.sub.1; in this case,
I.sub.2=3/5. As a result, the larger number of LEDs over FIG. 56a
(n=5 versus n=3) is compensated for in the light recipe. The
variant in which the respective intensities of the values I.sub.2
are different, but the overall value thereof corresponds to the
predetermined reduction factor, does not have a figure.
[2505] FIG. 57 shows a schematic comparison 5700 between a target
spectrum 5710 and the spectra 5720, 5722, 5724 of three LEDs with
maxima at 100 nm, 520 nm and 700 nm, said spectra being coarsely
approximated as triangles (in fact, they tend to be Gaussian-like).
Here, the target spectrum 5710 of the light recipe is available in
50 nm wide intensity steps (the tendency being to usually select
smaller ranges). For the approximation, the LEDs (to the extent
that they are available) are selected in such a way that the
deviation to the target spectrum is minimized over the entire curve
for the resultant LED spectra. (In this case, the selected LED
spectrum has an overshoot in the green range. It is possible to
prescribe the boundary condition that the LEDs may only have a
maximum intensity here).
[2506] FIG. 58 shows the schematic design of a controlled
agricultural system 100 according to the disclosure, reduced in
this case to the major components of acquisition unit 5810,
computing device 140, control unit 130 and a first light fixture
110.1 and a second light fixture 110.2. Instead of two light
fixtures, provision may also be made for only one light fixture or
for more than two light fixtures. The parameters of the light
fixtures 110.1 and 110.2, for example the number and type of the
LEDs installed in the respective light fixture, are acquired by way
of the acquisition unit 5810, in some embodiments/implementations
in automated fashion. It is likewise conceivable for the
acquisition unit to call up the light fixture data from a database.
The light recipe 5800 is likewise acquired, for example the light
recipe for the maturing process of a certain plant. On the basis of
the light recipe 5800 and the parameters of the light fixtures
110.1, 110.2, the computing device 140 establishes, for each light
fixture, a suitable selection of the light sources (e.g., LEDs; not
illustrated) and the actuation thereof (e.g., the light intensity)
in such a way that the light recipe 5800 is reproduced to the best
possible extent by both light fixtures 110.1 and 110.2 within the
scope of what is technically possible for the respective light
fixture. The data of the generic light recipe 5800, in each case
suitably transformed for the specific light fixtures 110.1, 110.2,
are transmitted from the computing device 140 to the control unit
130, which correspondingly actuates the light fixtures 110.1, 110.2
or the selected light sources situated therein.
[2507] FIG. 59 schematically shows a first illumination
configuration of an embodiment according to the disclosure. For
illustrative purpose, two horticultural light fixtures 110 of the
same type (downlights) are shown, which illuminate plants 902
arranged on a cultivated area 5930 below the horticultural light
fixtures 110. Each of the horticultural light fixtures 110 comprise
a light source device 5911 and an optical device 5912 attached
downstream to the light source device 5911.
[2508] The dashed lines 5913 schematically indicate a broad beam
angle of the light emitted by the horticultural light fixtures 110.
The reference sign H1 denotes the distance between the
horticultural light fixtures 110 and the cultivated area 5930. H1
is relatively large. The broad beam angle and the relatively large
distance between the horticultural light fixtures 110 and the
plants 902 result in a relatively low light intensity on the plants
902 during illumination.
[2509] FIG. 60 schematically shows a second illumination
configuration of the embodiment shown in FIG. 59. In this second
illumination configuration, the distance H2 between the
horticultural light fixtures 110 and the cultivated area 5930 has
been decreased, i.e. H2<H1. Consequently, the distance between
the horticultural light fixtures 110 and the plants 902 has also
been decreased. Due to this lowering of the horticultural light
fixtures 110 down closer to the plants 902, the light intensity on
the plants 902 during illumination has been increased without
increasing the current setting of the horticultural light fixtures
110, i.e. without increasing the power consumption.
[2510] On the other hand, power consumption of the horticultural
light fixtures 110 may even be reduced, if the light recipe
specifies a light intensity that is lower than the one achieved by
decreasing the distance between horticultural light fixtures 110
and plants 902. In this case, the brightness of the light source
devices 5911 will be reduced, respectively, such that the light
intensity at the plants matches with the light recipe.
[2511] FIG. 61 schematically shows a third illumination
configuration of the embodiment shown in FIG. 59. Compared to FIG.
59, the focal length of the optical devices 5912 has been adjusted
to focus the illumination more on the plants. Consequently, the
light intensity on the plants 902 during illumination has been
increased due to proper adjustment of the optical devices 5912.
This, again, can be counteracted by a respective reduction of the
brightness of the light source device 5911, depending on the
illumination specified by the light recipe.
[2512] FIG. 62 shows a schematic block diagram of a controlled
agricultural system 100 according to the disclosure. The controlled
agricultural system 100 comprises a computing device 140, a data
storage device 170, coupled to the computing device 140, an
agricultural light fixture 110 as shown in FIGS. 59 to 61, coupled
to the computing device 140 via a control unit 130 and an actuator
device 310, coupled to the computing device 140 via another control
unit 320. For illustrative purposes, only one agricultural light
fixture 110 is shown. In practice, agricultural facilities can
comprise a multitude of similar agricultural light fixtures.
[2513] The actuator device 310 is configured to be able to control
the position/alignment of the agricultural light fixture 110 and/or
the focal length of the optical device and/or the form and shape of
a reflective element of the optical device 5912.
[2514] The data storage device 170 or even the computing device 140
may be based locally (on-site) or in a (centralized) network or the
cloud. Furthermore, the data storage device 170 may also be
integrated into the computing device 140. The data storage device
170 may include a (digital/online-) platform, e.g. located in the
cloud. The platform may also be accessible by mobile devices, e.g.
laptop PC, tablet PC or smartphones via dedicated apps. Therefore,
a user 6201 may access the platform via the computing device 140 or
a separate device (not shown). Furthermore, the platform may
comprise dashboards customized to various user groups such as
growers and customers.
[2515] The data storage device 170 comprises a database in which
growth settings, including light recipes, for various plants
species are stored. Furthermore, the database may comprise data
documenting previous plant projects, e.g. from other growers using
the same platform. The data storage device 170 may also comprise
software programs, which can be uploaded into and executed by the
computing device 140, particularly for controlling the (at least
one) agricultural light fixture 130 according to the light recipe.
The data storage device 170 may also comprise information on how
mechanical and optical modifications of the agricultural light
fixture influence the illumination at the plants.
[2516] The computing device 140 is configured to control the
actuator device 310 and the agricultural light fixture 110 in order
to achieve an intensity of the illumination on the plants according
to the light recipe stored in the data storage device 170.
Particularly, the computing device 140 is configured to adjust the
alignment of the agricultural light fixture 110 and/or the focusing
of the optical device 5912 such that the intensity of the
illumination on the plants according to the light recipe is
achieved with lower current for the light sources compared to the
current necessary without supplemental adjustment.
[2517] Furthermore, a sensor (not shown) may be installed and
connected to the computing device via a suitable control device to
measure the light intensity at the plants. The horticultural light
fixture and/or the optical device may be controlled such that the
measurement results match with the light recipe.
[2518] A Controlled Agricultural System, particularly for breeding,
growing, cultivating and harvesting in an agricultural facility,
particularly a plant growing facility and/or an aquaponics
facility, comprises at least one horticulture light fixture
arranged above an area cultivated with plants for illuminating the
plants. The Controlled Agricultural System is configured to
effectuate the intensity of the illumination specified by a light
recipe by, for example, bringing the horticultural light fixture
closer to the plants, for example, by lowering the horticulture
light fixture down closer to the plants, in conjunction with
reducing the power settings (brightness) of the light sources,
compared to the otherwise necessary power settings. Alternatively
or additionally, in conjunction with a reduction of the power
settings of the light sources, the illumination is more focused on
parts of the cultivated area, on the plants or even on parts of the
plants by means of a suitably adjusted optical device.
[2519] FIG. 63 shows a schematic block diagram of a controlled
agricultural system 100, according to the disclosure. The
controlled agricultural system 100 comprises a computing device
140, a data storage device 170, coupled to the computing device 140
and an actuator device 310, coupled to the computing device 140 via
a control unit 130. The data storage device 170 or even the
computing device 140 may be based locally (on-site), in a network
or the cloud.
[2520] The data storage device 170 comprises a database with data
of control parameters for controlling the agricultural system 100.
Based on the data stored in the data storage device 170, the
control parameters may be adjusted by means of the actuator device
310. To this end, the computing device 140 can be configured to
adjust irrigation, manuring, heating/ventilation or the like.
Furthermore, the computing device 140 is configured to control
light fixtures 110 (via the control unit 130 and a driver unit 120)
to apply a defined illumination.
[2521] FIG. 64 shows a schematic block diagram of a light fixture
110.1 comprising a plurality of light sources 6401. The light
sources 6401 are of different types 6401.1, 6401.2 for providing
light with different spectral properties. Typically, more than two
different types will be provided, which is not shown for the sake
of simplicity. The light fixture 110.1 further comprises a light
control unit 6402 and a computing unit 6403 connected thereto.
These units could also be provided externally.
[2522] A control unit 6405 for modulating the emission is provided
as an external device. In FIG. 64, it is connected to the light
control unit 6402. The control unit 6405 triggers the light control
unit 6402 such that an emission of the light sources 6401 is
modulated. For instance, for the modulation, the light sources 6401
can be switched off and on again and/or PWM-modulated with a high
frequency. Accordingly, data can be coded in the emission, and the
modulated signal 6410 can be used for transmitting this data.
[2523] As a receiver, for instance a second light fixture 110.2
and/or an actuator device 6430 can be provided. Likewise, lighting
or actuation parameters can be transmitted. Regarding different
modes of operation being possible (modulation of one/all light
source types 6401.1, 6401.2 and so on) reference is made to the
description above.
[2524] The control unit 6405 can be connected to the computing
device 140 of the system shown in FIG. 63. In some
embodiments/implementations, the lighting/actuation parameters are
transmitted from the first light fixture 110.1 as a master 6450 to
the second light fixture 110.2 or the actuator device 6430 as a
slave 6460. As an alternative to the embodiment shown, the control
unit 6405 can also be connected to the computing unit 6403.
[2525] FIG. 65 illustrates a monitoring 6500 of the reduced
lighting resulting from the modulation. Upon a comparison 6501 with
a threshold value, no action 6502 is taken as long as a threshold
value is not reached. Upon reaching 6503 the threshold value, the
light recipe is adapted.
[2526] FIG. 66 shows a schematic block diagram of a controlled
agricultural system 100 for an agricultural facility 6630,
according to the disclosure. The controlled agricultural system 100
comprises a computing device 140, a data storage device 170,
coupled to the computing device 140, an actuator device 310,
coupled to the computing device 140 via a control unit 320 and a
sensor device 150, coupled to the computing device 140 via a second
control unit 340.
[2527] The data storage device 170 or even the computing device 140
may be based locally (on-site) or in a (centralized) network or the
cloud. Furthermore, the data storage device 170 may also be
integrated into the computing device 140. The data storage device
170 may include a (digital/online-) platform, e.g. located in the
cloud. The platform may also be accessible by mobile devices, e.g.
laptop PC, tablet PC or smartphones via dedicated apps. Therefore,
a user 6201 may access the platform via the computing device 140 or
a separate device (not shown). Furthermore, the platform may
comprise dashboards customized to various user groups such as
growers and customers.
[2528] The data storage device 170 comprises a database in which
growth settings, including light recipes and temperature profiles
(temporal and/or spatial), for various plants are stored. The
database may also comprise data documenting previous plant
projects, e.g. from other growers using the same platform.
[2529] The computing device 140 is configured to control the
actuator device 310 based on the data stored in the data storage
device 170, particularly for (re-) adjusting the temperature
according to the temperature profile of the respective plant
species. Therefore, the actuator device 310 may comprise various
actuators for controlling/adjusting the temperature, e.g. a heating
and cooling system like an HVAC (heating, ventilation and air
conditioning), a heating pipe, IR (infrared)-radiator, etc.
[2530] Furthermore, the computing device 140 is configured to
collect the data from the sensor device 150, particularly for
monitoring the environmental conditions in the agricultural
facility, particularly the (local) temperature, optionally also the
plant growth. Therefore, the sensor device 150 may comprise various
sensors for, e.g., the temperature, the illumination, the color of
the plants and fruits, or cameras for imaging methods, etc.
[2531] FIG. 67 schematically shows the steps 6700 of a method for
agricultural management according to the disclosure. The method
aims to adjust the temperature conditions in an agricultural
facility according to (temporal and/or spatial) temperature
profiles, which are part of the growth settings for a respective
plant species. For the following description, in addition to FIG.
67, reference is made to FIG. 66. The method comprises the
following steps: [2532] Step 6710: Choosing a plant species by the
user 6201 via a user interface; [2533] Step 6720: Picking from the
data storage device 170 a growth setting including the correlated
(temporal and/or spatial) temperature profile by the computing
device 140 or by the user via the user interface 6201; [2534] Step
6730: Measuring the temperature in the agricultural facility by
means of the sensor device 150 (temperature sensors); [2535] Step
6740: Checking by means of the computing device 140, whether the
measured temperature matches with the nominal value according to
the selected temperature profile; [2536] Step 6745: Deciding
whether the temperature is OK: [2537] If yes (Y): go to step 6740;
[2538] If no (N): continue with step 6750. [2539] Step 6750:
Changing the temperature according to the temperature profile by
means of the computing device 140 and the actuator device 310
(temperature influencing means); [2540] Go back to step 6730 to
start next measuring, checking/controlling cycle. The cycle may be
repeated until harvest of the plants.
[2541] Alternatively, the method may start with step 6720 by
picking a growth setting including the correlated temperature
profile by the user via the interface 6201.
[2542] Alternatively, the method may start with step 6720 by
picking a preset growth setting including the correlated
temperature profile by the computing device 140.
[2543] In step 6720, the temperature profile included in the growth
settings may be correlated to various environmental conditions,
e.g. day-night-shift, circadian rhythm of the plant, illumination
conditions, growth phases of the plants, etc. Particularly, step
6720 or step 6730 may include synchronizing the temperature profile
and the light recipe. Alternatively, the temperature profile and
the light recipe may be integrated in one single dataset, which
renders synchronization superfluous.
[2544] In step 6730, the temperature measurement may be conducted
on various similar locations, e.g. with various temperature sensors
each sensor being located in the same manner relative to a
respective plant. The data of these temperature sensors may be used
for calculating an average temperature for said similar locations
or to give an overview of the temperature distribution for these
various locations. Furthermore, the temperature measurement may be
conducted on various different locations for the purpose of
adjusting different temperature profiles, e.g. temperature sensors
may be positioned at different vertical heights of the plants or
even the agricultural facility. The sensor may be configured to
measure the temperature of the air, soil or of parts of the plants
(root, leaves, petal, etc.). Based on the data of these temperature
sensors vertically different temperature profiles may be adjusted
by means of the computing device 140 and the temperature
influencing means.
[2545] In step 6750, changing the temperature may be conducted by
heating (i.e. increasing the temperature) or cooling (i.e.
decreasing the temperature) of the air or irrigation in the
agricultural facility or by (local) IR-radiation.
[2546] FIG. 68 schematically shows a set of optional steps 6800.
These steps aim to account for different temperature profiles
correlating to different growth phases. For the following
description, in addition to FIG. 68, reference is also made to
FIGS. 66 and 67. The method starts from step 6730 of FIG. 67 and
comprises the following steps: [2547] Step 6810: Detecting the
growth phase of the plants by means of the sensor device 150;
[2548] Step 6820: Comparing the presently detected growth data with
the previously detected growth data or data stored in the database
170 and checking by means of the computing device 140 whether the
growth phase has changed; [2549] Step 6825: [2550] If yes (Y): go
to step 6720; [2551] If no (N): continue with step 6740.
[2552] Step 6810 may involve taking pictures from the plants,
determining the size, shape or color of the plants/flowers.
Furthermore, the computing device 140 may compare present images of
the plants with various images of the plants stored in the database
170 to determine the present growth phase. The growth phases may
comprise breeding, greening, flowering and harvest.
[2553] Temperature profiles that are correlated to various
parameters like natural circadian cycles, database stored cycles,
plant-specific cycles, customer-specified cycles, or freely
adjustable cycles, are applied to the various stages of plant
growth (e.g. measured by sensors). Temperature cycles can be
correlated to lighting conditions or to other environmental
conditions (CO2, Energy price) so that they can be applied in a
correlated way.
[2554] The present disclosure proposes a controlled agricultural
system (100), particularly for plant breeding, growing, cultivating
and harvesting in an agricultural facility, configured to
change/adjust the temperature conditions in the agricultural
facility (6630) according to a selected temporal and/or spatial
temperature profile. In some embodiments/implementations, the
temperature profile is dedicated to respective plant species and
may be correlated to various environmental conditions like
day-night-shift, circadian rhythm of the plant, illumination
conditions and/or the plant growth phase. Furthermore, the
temperature profile may be different in different locations of the
agricultural facility and/or plants and or plant parts. Changing
the temperature is conducted by temperature influencing means like
heating devices and cooling devices.
[2555] Luminaire
[2556] FIG. 69 shows an agricultural lighting fixture 110 according
to an embodiment of "Light Guides". The lighting fixture 110
comprises a light module 6910 according to a first embodiment of
"Light Guides". The light module 6910 comprises one or more light
emitting elements 6912.1, 6912.2, each having at least one light
guide (not shown in FIG. 69). According to the sectional view of
FIG. 69, the light emitting elements 6912.1, 6912.2 are located on
a common plane and the light guides (not shown) meander within this
plane over a target area 6902. The light emitting element 6912.1,
6912.2 and/or the light guides may also be provided in different
fashion, such as a spiraling fashion, stripe-like, or any other,
also arbitrary fashion. In the example according to FIG. 69, the
light emitting element 6912.1, 6912.2 is provided in one layer,
i.e. one plane. It is to be noted that the light module 6910 may
also comprise multiple light emitting elements 6912.1, 6912.2,
which may be controllable separately from one another, as well as
sensors and actuators, as described above. Accordingly, in some
embodiments of "Light Guides", the light module 6910 comprises one
light emitting element having interconnected sections 6912.1,
6912.2.
[2557] The light emitting element 6912.1, 6912.2 comprises at least
one light guide not explicitly shown in the figures. The light
emitting element 6912.1, 6912.2 may be integrally connected with
the light guide. Thus, according to some embodiments of "Light
Guides", the light emitting element or elements 6912.1, 6912.2 at
the same time represent the respective light guide. Accordingly, in
the figures, the light guide or light guides may be represented by
the light emitting element 6912.1, 6912.2.
[2558] On the target area 6902, plants 3 are grown. The plants 6903
are to be illuminated by the light module 6910. In order to
illuminate the target area 6902 and in particular the plants 6903
provided on or within the target area 6902, the light emitting
element is appropriately arranged. The light emitting element
6912.1, 6912.2 or the entire light module 6910 and or the attached
light guides may be movably mounted, in particular, in order to
alter the distance between the target area 6902 and the light
module 6910. This also implies that the distance between the plants
6903 and the light emitting element 6912.1, 6912.2 may be altered
and thus set to a predetermined distance. That may also allow to
influence the growth rate or ripening.
[2559] FIG. 70 shows another embodiment according to "Light
Guides". Same reference numbers are referring to same or similar
components, the description of which will not be repeated in the
following. The light module 6910 according to FIG. 70 comprises
multiple layers A, B, C, whereas a layer A, B, C here is defined by
light emitting elements or groups of light emitting elements
6912.1, 6912.2; 7014.1, 7014.2; 7016.1, 7016.2. In the Example
shown, this groups of light emitting elements 6912.1, 6912.2;
7014.1, 7014.2; 7016.1, 7016.2 have the same or similar distance to
the target area 6902. However, the light emitting elements 6912.1,
6912.2; 7014.1, 7014.2; 7016.1, 7016.2 of the light module 6910 may
also have altering distance to the target area 6902.
[2560] It is also possible, that one layer A, B, C comprises
multiple light emitting elements 6912.1, 6912.2; 7014.1, 7014.2;
7016.1, 7016.2, which are mounted and/or illuminated and/or
controllable independently from one another. In layer A, as shown
in FIG. 70, different brightness of the light emitted elements are
indicated by sun-symbols in different size as an example for
possible individual control. Arrows in layer B of FIG. 70 indicated
separate movability of light emitting elements or sections thereof.
Further, in FIG. 70 it is indicated in layer B and C how different
wavelengths may be emitted by different light emitting elements
7014.2, 7016.1, 7016.2.
[2561] As an example, according to an embodiment of the disclosure
as suggested in FIG. 70, the light module may be controlled to
deactivate light emission from layer A, as layer A is still too far
away from the plants 6903. In layer B, increased or maximum
intensity could be applied according to the applicable or required
light recipe. Layer C of the light module 6910 according to FIG. 70
may be operated with an increased blue light component, in order to
compensate shading effects by higher leaves. Of course, it may also
be possible to operate the light module to emit from other layers
or to emit different wavelengths, as needed or as required by a
light recipe.
[2562] Generally, the light module may be controlled to emit light
from different layers with different and varying spectral
composition and further parameters variable over time, e.g.
depending on the size, growth, morphology and/or further parameters
of the plants. Such parameters of the plants may be accessible by
sensors provided in the light module 6910 or in the control unit
7230, 7330 as exemplified in FIGS. 72 and 73.
[2563] FIG. 71 shows a further embodiment of "Light Guides",
wherein the lighting fixture 110 comprises a light module 7120,
which is located within a meshwork 7124. The meshwork 7124 may
comprise wires. The meshwork may be provided to support the plants,
or in order to provide a supporting structure for one or more light
emitting elements 7110 and/or the light guides. In the example
shown in FIG. 71, the light emitting element is provided at a
central part of the meshwork. The light emitting element may,
however, also be positioned at any other location of the light
module. Light guides may be provided along the meshwork or woven
into the meshwork. A holding part 7122 of the light module 7120 may
be provided in order to connect the light emitting element 7110
with further components of the light module 7120, such components
not being shown in FIG. 71, and in order to provide stability. The
meshwork 7124 may in particular be provided to form a cage- or
grid-like structure around one or more plants grown on the target
area 2.
[2564] It is further to be noted that in the embodiments described
above, light emitting elements or light guides may be individually
controllable, in particular with respect to their position relative
to the target area and thus to the plants, light parameters and/or
other features. The embodiments provided above are exemplary for
"Light Guides", while any combination of the given embodiments is
also possible.
[2565] FIG. 72 shows a schematic illustration of an embodiment of
"Light Guides". In this exemplary embodiment, an agricultural
lighting fixture 110 is shown comprising a light module 7210 and a
control unit 7230. The control unit 7230 comprises, in the
embodiment shown in FIG. 72, a computing unit 7232, a light
controller 7234, one or more actuators 7236, and one or more
sensors 7238. The computing unit 7232 may be used to manage,
calculate and control light recipes and parameters of the
agricultural system. Accordingly, the computing unit is connected
to the light controller 7234, in order to control lighting
parameters of one or more light modules 7210. In the example shown
in FIG. 72, the agricultural lighting fixture is provided with one
light module 7210. Further, the computing unit 7232 is connected
with actuators 7236. The actuators 7236 may be provided in order to
control e.g. the position of light emitting elements 6912.1 and/or
light guides 7217.
[2566] The computing unit 7232 may comprise computing means,
storage means and communication means for local and network
communication.
[2567] The light module 7210 according to the embodiment displayed
in FIG. 72 comprises one light emitting element 7212. In
alternative embodiments, the light module may also comprise
multiple light emitting devices. The light emitting element 7212
comprises, according to the embodiment shown, light sources 7218
for supplying light to two light guides 7217.1, 7217.2. As
indicated in the example of FIG. 72, the light guide 7217.1 is
provided to emit light of a shorter wavelengths, such as UV light,
or blue light. The light guided through the light guide 7217.1 is
coupled into the light guide from a light source 7218. Another
light guide 7217.2 may be provided with light of longer
wavelengths, such as yellow, red or infrared. Again, that light may
be coupled into the light guide from a light source 7218. "Light
source" in this context shall refer to any one or more light
emitters emitting light of the desired wavelengths or spectral
composition.
[2568] It is to be noted that the light guide 7217.1, 7217.2 may
also be provided such that the light coupling out of the light
guide 7217.1, 7217.2 is converted to the desired wavelength or
spectral composition only after traveling through the light guide
7217.1, 7217.2, being converted e.g. by means of a converter
provided at the position of emission. The light guides 7217.1,
7217.2 may thus be supplied with light originating from the same
light source or with light from separate light sources. A light
source 7218 may in particular also comprise more than one light
emitter, e.g. a group or an array of LEDs or laser diodes. Each of
such individual light emitters within the light source 7218 may
emit light of one or more wavelengths, which may differ from the
light emitted from other light emitters.
[2569] It should also be noted that the light guides 7217.1, 7217.2
may be freely arranged in space, independent of the schematic
drawing according to FIG. 72 and FIG. 73. In particular, the light
guides 7217.1, 7217.2 may be arranged within a vertical plane or a
plane parallel to the target area.
[2570] The light module 7210 may further comprise fixing means in
order to fix the light module to a supporting structure, and/or
further components that may be required to functionally arrange the
light module in an intended position relative to the target area 2.
Such additional components are not shown in the schematic drawing
of FIG. 72.
[2571] The at least one actuator 7236 of the control unit 7230 may
be provided in order to set and control the position of the light
guides 7217.1, 7217.2, the light emitting element 7212 and/or the
light module 7210 or other components thereof. In particular, the
at least one actuator 7236 may be provided in order to control the
vertical position of at least one light guide 7217.1, 7217.2.
[2572] FIG. 73 shows a further exemplary embodiment of "Light
Guides". Same or equally acting components are indicated with the
same reference numbers and the description thereof is not repeated.
In the following, differences of the embodiment according to FIG.
73 are described in comparison to the embodiment according to FIG.
72.
[2573] In the embodiment according to FIG. 73, the light module
7310 comprises the at least one actuator 7336 and the at least one
sensor 7338. It is also possible that both the control unit 7330
and the light module 7310 comprise actuators and/or sensors in
alternative embodiments. Further, in contrast to the embodiment
according to FIG. 72, it is shown in FIG. 73 that the light
emitting element 7312 comprises one light guide 7217. The light
guide 7217 is provided such that portions thereof may be arranged
on different vertical layers. Still, it may be possible to couple
light out of the light guide, which has a different wavelength or
spectral composition at different parts of the light guide. That
may be realized by providing conversion means, such as a phosphor,
within the light guide or at the location of emission.
[2574] In alternative embodiments, the light module may comprise
multiple light emission elements. Further, one light emission
element may comprise one light guide only. The light guide may also
be provided in one plane only. The embodiments as shown herein are
exemplary only and shall not limit the scope of protection, wherein
any combination of features is suitable. In particular, "Light
Guides" shall enclose such embodiments as well, according to which
the light module comprises at least some of the features shown as
part of the control unit and vice versa.
[2575] FIG. 74 shows a schematic block diagram of a controlled
agricultural system 100, according to "Failure Detection" as well
as "Failure Compensation". The controlled agricultural system 100
comprises a computing device 140, and a light fixture 110 coupled
to the computing device 140 via a control unit 130. The data
storage device 170 or even the computing device 140 may be based
locally (on-site), in a network or the cloud.
[2576] The data storage device 170 comprises a database with data
of control parameters for controlling the illumination. Based on
the data stored in the data storage device 170, the control
parameters may be adjusted by means of the control unit 130 (and
the driver unit 120). Furthermore, the computing device 140 is
configured to control grow parameters like nutrient concentration,
via the actuator unit 310.
[2577] The controlled agricultural system 100 further comprises a
sensor device 150, coupled to the computing device 140, for sensing
a reduced emission or total failure. For detecting a failing light
source (of the light fixture 110), the sensor device 150 is an
electrical current sensor in this case. Alternatively, a light
sensor 200 can be provided, see FIG. 75, 76.
[2578] The information about the failing light source or fixture
110 may be delivered to the user or customer by a user interface
(UI), e.g. a control terminal coupled to the computing device or a
mobile device such as a smartphone or tablet including a dedicated
software application (i.e. app for mobile devices).
[2579] FIG. 75 shows a schematic block diagram of an embodiment of
the disclosure. Therein, devices having the same function have the
same reference numeral as in FIG. 74. FIG. 75 illustrates that the
sensor device 150, 200 can be coupled either to the control unit
130 or to the computing device 140. In practice, the agricultural
system will comprise a large number of light fixtures 110, each
comprising a plurality of light sources. Respectively, a large
number of current sensors 150 and/or light sensors 200 can be
provided for a localization of the failing light source or fixture
110.
[2580] For allowing an individualization or localization of the
failing light source by a light sensor 200, a modulation can be
imposed on the emission of the light sources/fixtures. Each light
source or fixture 110 can be modulated with an individual pattern
enabling a linkage between the measured intensity and the
respective light source or fixture 110. When the pattern is imposed
on the emission by the control unit 130, the light sensor 200 is
switched on.
[2581] FIG. 76 shows a schematic sectional view of a light fixture
110. The light source 8100 is mounted on a board 8101. The light
fixture 110 comprises a lens 8102 which guides the light 8103 to a
growth area 8104. The light sensor 200 is arranged at an edge of
the lens 8102, which enables a detection of a part of the light,
which is guided in the lens 8102 by total internal reflection.
[2582] FIG. 77 shows a light fixture 110 with a plurality of light
sources 8100. Further, the light fixture comprises a plurality of
light sensors 200.1-200.8. In this figure, the growth area is
arranged in front of the drawing layer, the light sources 8100 and
the light sensors 200 are oriented towards the growth area. A
failing light source 8200 is indicated schematically (cross
hatched), its emission is reduced. The light sensors 200.6, 200.7
measure a reduced intensity. The same applies for the light sensors
200.2, 200.3, wherein these sensors measure only a minor intensity
drop compared to the light sensors 200.6, 200.7. The other light
sensors 200.1, 200.4, 200.5, 200.8 arranged at the corners of the
light fixture 110 measure no intensity drop at all. From comparing
the intensity drop measured by the individual light sensors 200, a
localization of the failing light source 8200 is possible. In
practice, different spectral properties of the light sources can
additionally be taken into account by providing light sensors with
different spectral sensitivities.
[2583] FIG. 78 shows a light fixture 110 in a schematic view, it
comprises a plurality of light sources 8301. In this case, red
light sources 8301.1 and blue light sources 8301.2 are shown,
further colours including UV and IR can be provided in practice.
One light source 8302 is failing, having a reduced or no emission
at all.
[2584] According to the disclosure, this is compensated by an
increased emission of other light sources 8303 arranged close to
the failing light source 8302. Therein, only those light sources
are used for the compensation, which have the same spectral
properties (red colour in this case) and are arranged close to the
failing light source 8302. Accordingly, the illumination properties
at the growth location with the plants can be kept rather constant
until the failing light source 8302 is repaired or replaced.
[2585] FIG. 79 also shows a light fixture in a schematic view,
comprising red light sources 8301.1 and blue light sources 8301.2.
In contrast to FIG. 78, redundant light sources 8401 are provided
in addition, namely red ones 8401.1 and blue ones 8401.2. In normal
operation the redundant light sources 8401 are switched off. After
the detection of the failing light source 8302, the redundant light
source 8403 is switched on for the compensation. As in the
embodiment of FIG. 75, the redundant light source 8403 is chosen
based on the spectral match and the spatial proximity.
[2586] FIG. 80 schematically shows a side view of an embodiment
8500 of the horticultural apparatus according to the disclosure,
comprising an elongated agricultural light fixture 110 and a plane
reflector 8520 arranged above and parallel to the top side 8515 of
the agricultural light fixture 110. The agricultural light fixture
110 comprises LED modules (not shown) and two ventilators 8530. The
ventilators 8530 are arranged on the top side 8515 of the
agricultural light fixture 110 in order to force the hot air from
the LED modules towards the reflector 8520, i.e. by means of forced
convection (indicated by arrow C). The bottom side 8521 of the
reflector 8520, which may be a foil equipped with infrared (IR)
reflecting properties, reflects the IR radiation back to the plants
8540 arranged on a cultivated area (plant bed) 8550 below the
agricultural light fixture 110.
[2587] FIG. 81 schematically shows a cross section of another
embodiment 8600 of the horticultural apparatus according to the
disclosure, comprising an elongated agricultural light fixture 110
and a reflector 8620 arranged above the top side of the
agricultural light fixture 110. The heat reflecting bottom side
8621 of the reflector 8620, i.e. the side facing the top side of
the agricultural light fixture 110, is shaped such that the heat
emanating from the top side of the agricultural light fixture 110
is first reflected sideways and then downwards, i.e. around the
agricultural light fixture 110 towards the plants 8540. In a
cross-sectional view, the reflector 8620 is shaped like two
mirror-image obtuse angles. Alternatively, the bottom side of the
reflector 8620 may be formed to resemble the shape shown in FIG.
81, but with a smooth surface, i.e. without abutting edges from the
plane parts, similar to the stylized shadow of a flying bird.
[2588] FIG. 82 schematically shows a cross section of a third
embodiment 8700 of the horticultural apparatus according to the
disclosure. The shape of the reflector 8720 is similar to the one
shown in FIG. 81. Furthermore, the two mirror-image parts 8720a,
8720b can be moved apart (indicated by the bold double arrow). This
enables to reduce the amount of heat that is reflected back to the
plants, because when moved apart, some of the heat or hot air can
flow through the aperture between the two parts 8720a, 8720b.
Furthermore, the angle between the two surfaces of each part parts
8720a, 8720b can be adjusted (indicated by the bended arrows) in
order to adjust the direction of the reflected heat. Of course, if
the heating conditions change, the reflector parts can be moved
back to their original position.
[2589] FIG. 83 shows a schematic block diagram of a controlled
agricultural system 8800 according to "Heat Reflector". The
controlled agricultural system 8800 comprises a computing device
140, a data storage device 170, coupled to the computing device
140, an actuator device 310, coupled to the computing device 140
via a control unit 130.1, a heat reflector 8812, e.g. as shown in
FIGS. 85 to 87, coupled to the actuator device 310, and an
agricultural light fixture 110, e.g. as shown in FIGS. 85 to 87,
coupled to the computing device 140 via another control unit 130.2.
For illustrative purposes, only one agricultural light fixture 110
is shown. In practice, agricultural facilities can comprise a
multitude of similar agricultural light fixtures.
[2590] The actuator device 310 is configured to be able to control
the position/alignment of the heat reflector 8812 and/or--as the
case may be--the shape by adjusting the movable parts of the heat
reflector 8812 (see also FIG. 82).
[2591] The data storage device 170 comprises a database in which
growth settings, including light recipes and correlated temperature
values, for example measured at plant level, for various plants
species are stored.
[2592] Furthermore, if knowing the reflector shape and distance to
the fixture, the respective heat map at the reflector can be
calculated (or measured). Alternatively, if a camera is around and
measures the distance between fixture and plant, and measures the
position and shape of a reflector, a computer can calculate the
actual heat irradiation towards the plants and at the pants
level--and thus allows controlling the entire setting.
[2593] The computing device 140 is configured to control the
actuator device 310, including the heat reflector 8812, and the
agricultural light fixture 110, including--as the case may
be--ventilators and/or supplemental heat sources arranged at the
agricultural light fixture 110, according to the growth recipe
stored on the data storage device 170.
[2594] The information about the failing light source or fixture
110 may be delivered to the user or customer by a user interface
(UI), e.g. a control terminal coupled to the computing device or a
mobile device such as a smartphone or tablet including a dedicated
software application (i.e. app for mobile devices).
[2595] Furthermore, one or more sensors (not shown) may be
installed and connected to the computing device via a suitable
control unit to measure the temperature, in some
embodiments/implementations at various locations close to the
plants.
[2596] Smart Grid
[2597] FIG. 84 shows a schematic design of a vertical farm 8900
having a controlled agricultural system according to the
disclosure. The controlled agricultural system comprises an
acquisition unit 8910, which is connected to a smart grid power
supply (smart grid) 8920, a computing device 140 connected to the
acquisition unit 8910, a control unit 130 connected to the
computing device 140 and a light fixture 110 connected to the
control unit 130.
[2598] By way of example, the acquisition unit can be configured as
a central platform, which is accessed by various customers. Current
information items in relation to the smart grid 8920, e.g., current
electricity prices and predictions of the electricity price
development, are supplied to the computing device 140 via the
acquisition unit 8910. Using information items in relation to the
smart grid 8920 and further information items in relation to the
plants, the computing device 140 calculates the optimal light
recipe and adapts the latter to changes in the information items
where necessary. The calculated light recipe is output to the
control device 130, which actuates the light fixture 110 in such a
way that the light intensity currently corresponding to the light
recipe is produced.
[2599] FIGS. 85A-85B show a schematic curve 9000 of the electricity
price EP over time t (top) and the curve 9010 of the light
intensity LI (bottom) of the light fixture adapted thereto, said
light fixture being represented schematically in FIG. 84 as an
element of the vertical farm. It is possible to identify how the
electricity price, which is derived from the current electricity
supply, has an effect on the accordingly controlled light
intensity. In this schematic illustration, the overall irradiation
intensities, dark times, etc., have been neglected. A prediction
9001, 9011 for the further development is illustrated using dashed
lines in each case.
[2600] FIGS. 86A-86B show a further schematic curve 9100 of the
electricity price EP over time t (top) and the curve 9110 of the
light intensity LI (bottom) of the light fixture adapted thereto. A
brief surplus of electricity, identifiable by the pronounced
depression 9102 in the electricity price curve 9100, is captured by
a brief corresponding increase in the light intensity, identifiable
by the pronounced peak 9112 in the light intensity curve 9110.
Thereafter, the further light intensity curve 9113 is recalculated,
as illustrated by the tighter dashed line. The originally planned
light intensity curve 9111 (illustrated by the wider dashed line)
without the light intensity peak is slightly higher than the
recalculated light intensity curve 9113.
[2601] In the case of an electricity surplus with a longer
duration, the increase in the light intensity curve can be reduced
prematurely again where necessary and an energy storage can be
charged instead (not illustrated). The charged energy storage can
then be used conversely during phases of high electricity prices
for the energy supply of the vertical farm or of the controlled
agricultural system.
[2602] Customer Interaction
[2603] FIG. 87 shows a schematic flow chart 9200 of an exemplary
embodiment of the method for agriculture according to the
disclosure using the controlled agricultural system according to
the disclosure (the latter is not illustrated here).
[2604] Initially, the progress of the method starts with defining
the target product by the customer (method step 9210). The
definition is entered into the computer system of the controlled
agricultural system, for example by way of the GUI or any other
computer interface. Using this, the computer system converts the
customer's wishes into corresponding control parameters or control
signals (light recipe, etc.) (method step 9220). In the next method
step 9230, the control parameters thus established are applied to
the actuators (light fixture, etc.). The plant growth or the plant
health is monitored by way of the sensor system of the controlled
agricultural system (method step 9240). In the case of deviations
between the result of the check (actual values) and an expected
profile of the plant growth of the target product (intended
values), suitable measures are adopted; by way of example, the
control parameters are adapted (method step 9250). Then, there is a
return to method step 9230. By contrast, if the final state of the
target product has been reached, the product can be harvested.
[2605] A database may be provided for establishing possible
deviations, the ideal profile of the plant growth of the target
product (intended values) in some embodiments/implementations being
stored in said database, for example on the basis of empirical
values. As an alternative or in addition thereto, the computing
device of the computer system can be configured, with the aid of
suitable algorithms, to predict the ideal profile of the plant
growth of the target product (intended values) on the basis of the
definition of the target product and control parameters that are
suitable to this end (intended values). Moreover, the computing
device of the computer system can be configured to establish
deviations of the current actual values from these intended values
and, where necessary, calculate suitably corrected control
parameters.
[2606] FIG. 88 shows a schematic block diagram of a controlled
agricultural system 100, according to the disclosure. The
controlled agricultural system 100 comprises a computing device
140, a data storage device 170, coupled to the computing device
140, an actuator device 310, coupled to the computing device 140
via a control unit 130.1 and a sensor device 121, coupled to the
computing device 140 via a second control unit 130.2.
[2607] The data storage device 170 or even the computing device 140
may be based locally (on-site), in a (centralized) network or the
cloud. Furthermore, the data storage device 170 may also be
integrated into the computing device 140. The data storage device
170 may comprise a (digital/online-) platform, e.g. located in the
cloud. The platform may also be accessible by mobile devices, e.g.
laptop PC, tablet PC or smartphones via dedicated apps. Therefore,
a user 101 may access the platform via the computing device 140 or
a separate device (not shown). Furthermore, the platform may
comprise dashboards customized to various user groups such as
growers and customers.
[2608] The data storage device 170 comprises a database in which
growth recipes are stored. The database may also comprise data
documenting previous plant projects, e.g. from other growers using
the same platform.
[2609] The computing device 140 is configured to control the
actuator device 310 based on the data stored in the data storage
device 170, particularly for conducting growth recipes. Therefore,
the actuator device 310 may comprise various actuators for
adjusting various growth parameters, e.g. water, nutrient, light
(intensity, spectrum), etc.
[2610] Furthermore, the computing device 140 is configured to
collect the data from the sensor device 150, particularly for
monitoring the environmental conditions and the growth status of
the plants. Therefore, the sensor device 150 may comprise various
sensors for, e.g., the temperature, the illumination, the color of
the plants and fruits, or cameras for imaging methods, etc.
[2611] In some embodiments/implementations, the computing device
140 is configured to choose the best-match growth recipe currently
available in the database. Furthermore, the computing device 140
may be configured to analyze whether the best-match growth recipe
can be realized with the available setup of the controlled
agricultural system 100. Otherwise, the computing device 140
suggests a feasible growth recipe.
[2612] Furthermore, the computing device 140 is configured to
evaluate a success score based on data stored in the data storage
device 170 from similar configurations regarding customer demand,
result of the corresponding plant project, and the setup of the
respective agricultural system.
[2613] Furthermore, the computing device 140 is configured to
render a model plant (digital plant twin) based on the respective
growth recipe.
[2614] Furthermore, the computing device 140 is configured to
identify possible differences between the real plant and the model
plant. The computing device 140 may also be configured to adjust
the growth parameter by means of the actuator device 310 in order
to minimize any differences between the real plant 9330 and the
model plant.
[2615] FIG. 89 schematically shows the steps 9400 of a method for
agricultural management according to the disclosure. The method
aims to improve the growth results of real plants with the help of
a model plant (digital plant twin). For the following description,
in addition to FIG. 89, reference is made to FIG. 88. The method
comprises the following steps: [2616] Step 9410: Receiving a demand
on the platform (growers view), submitted by a customer via the
dashboard 101 of the platform (customers view); [2617] Step 9420:
Determining the growth parameters that influence the plant
characteristics relevant to the customer's demand; [2618] Step
9430: Calculating an appropriate growth recipe (preferably
best-match; optionally extrapolating from existing growth recipes)
by means of the computing device 140 based on the information of
steps 9410 and 9420 and the database 170 (e.g. collection of growth
recipes and results achieved under various environmental conditions
and setups); [2619] Step 9440: Applying the growth parameters to
the plants and rendering a model plant (digital plant twin) by
means of the computing device 140 based on the growth recipe
determined in step 9430; [2620] Step 9450: Comparing the growth of
the real plant with the model plant by means of the computing
device 140 based of the data from the sensor device 150 and the
digital plant twin; [2621] Step 9460: Analyzing which parameters
caused the deviations between the real plant and the model plant by
means of the computing device 140; [2622] Step 9470: Adjusting the
growth parameters of the growth recipe by means of the actuator
device 310 and the computing device 140 in order to minimize the
deviations detected in step 9450; [2623] Step 9480: Storing the
environmental data and growth data of the real plant(s) collected
by means of the sensor device 150 and the post-harvest data
(particularly regarding the characteristics relevant to the
customer's demand) into the database 170.
[2624] The steps 9450 to 9470 may be repeated (regularly or
randomly or from time to time or dependent on the growth status or
else) until harvest.
[2625] In an enhanced embodiment of the method, the methods shown
in FIG. 90 (evaluating success score) and/or 96 (deal making) may
be conducted between the steps 9430 and 9440.
[2626] FIG. 90 schematically shows the steps 9500 of another method
for agricultural management according to the disclosure. The method
aims to calculate a success score in order to evaluate the chances
of success for meeting a specific customer's demand. The method may
be optionally combined with the method shown in FIG. 89 and helps
to decide a grower whether to accept a customer's demand and/or to
improve the grower's success rate by acting appropriately before
starting the requested plant project. For the following
description, in addition to FIG. 90, reference is also made to
FIGS. 88 and 94. The method starts (S) from step 9430 of FIG. 89
and comprises the following steps: [2627] Step 9510: Analyzing by
means of the computing device 140 which growth recipe is feasible
with the available setup of the controlled agricultural system 100
based on the best-match growth recipe determined in step 9430 (FIG.
89); [2628] Step 9520: Searching the database 170 for similar
configurations (setup, growth recipe) by means of the computing
device 140; [2629] Step 9530: Calculating a success score by means
of the computing device 140 based on the search result of Step
9520; If score is not acceptable (SC?=N): [2630] Step 9540: Taking
appropriate measures to improve the success score and go to step
9550 afterwards or quit the plant project; If score is acceptable
(SC?=Y): [2631] Step 9550: Go to step 9440 (FIG. 89; conducting
plant project) or to 9610 (FIG. 91; deal making).
[2632] In Step 9530, the calculation of the success score may be
based on the number of previous successful growth for the same
customer's demand recorded in the database 170.
[2633] FIG. 91 schematically shows the steps 9600 of yet another
method for agricultural management according to the disclosure. The
method aims to arrange a deal making between the customer
submitting a specific plant demand via the platform 170 and the
grower submitting an offer to the customer via the platform 170.
The method may be optionally combined with the method shown in
FIGS. 89 and/or 95 and helps to make a deal and keep the customer
informed about the growth status of the requested plants. For the
following description, in addition to FIG. 91, reference is also
made to FIGS. 93 to 95. The method starts (S) from step 9430 of
FIG. 89 and comprises the following steps: [2634] Step 9610:
Preparing an offer based on customer's demand, calculated costs
and, optionally, the success score calculated according to FIG. 90;
[2635] Step 9620: Submitting the offer to the platform and
addressing the dashboard of the customer who submitted the request;
[2636] If the offer is not acceptable to the customer (O?=N):
[2637] Step 9630: Requesting amendments (e.g. price, plants
characteristics, delivery) to the offer by the customer via the
platform; [2638] If the requested amendments are not acceptable to
the grower (R?=N): [2639] Step 9640: No deal; [2640] If the
requested amendments are acceptable to the grower (R?=Y): go to
step 9650; [2641] If the offer is acceptable to the customer
(O?=Y): [2642] Step 9650: Deal; Making a respective contract
between the costumer and the grower, in some
embodiments/implementations via the platform; [2643] Step 9660:
Conducting the plant project agreed upon by both parties, i.e. go
to steps 9440-9480; [2644] Step 9670: Presenting the growth status
of the customized plants to the customer via the platform (on
customer's dashboard).
[2645] FIG. 92 schematically shows the interrelationship 9700
between a digital model 9710 (customer's demand) and a
corresponding real plant 9720 (customized product). The digital
model 9710 (digital plant twin) is rendered by means of the
computing device 140 of the controlled agricultural system 100 (see
FIG. 88) according to the customer's demand. By means of feedback
loops, plant growth algorithm and artificial intelligence (AI),
possible deviations between the real plants 9720 and the digital
plant twin 9710 are minimized. Furthermore, the digital plant twin
9710 allows predicting the result of changing growth parameters of
the growth recipe.
[2646] FIG. 93 schematically shows the steps 9800 of a method for
agricultural management according to the disclosure. The method
aims to facilitate taking standardized pictures of horticultural
objects, e.g. plants, in some embodiments/implementations with
suitable mobile devices (i.e. including a camera), e.g.
smartphones. The method starts by starting the app's picture mode
on the device and further comprises the following steps; [2647]
Step 9810: Selecting a picture style from a set of picture styles,
[2648] Step 9820: Providing a picture frame on GUI (shown on screen
of device) and indicating how to achieve alignment for taking a
standardized picture, [2649] Step 9830: Targeting horticultural
object with camera and aligning the viewer picture to the picture
frame, [2650] Step 9840: Checking alignment (AL?), [2651] If out of
alignment (No): repeat step 9830, [2652] If in alignment (Yes):
continue with step 9850, [2653] Step 9850: Taking standardized
picture, [2654] Step 9860: Deciding whether to take another
standardized picture (P?), [2655] If another picture is requested
(Yes): go back to step 9810, [2656] If another picture is not
requested (No): continue with step 9870, [2657] Step 9870:
Evaluating the picture(s) and showing the results.
[2658] Step 9810 may comprise selecting from a variety of picture
styles like distance shot, figure shot, full shot, medium shot,
close-ups, extreme close-ups, etc. Furthermore, the horticultural
object type may be selected from a set of picture styles, e.g.
plant (single, multiple), growing cabinet, etc. The selection may
be conducted by taking a picture of the environment beforehand,
analyzing the picture, e.g. by means of image recognition, and
determining an appropriate picture style.
[2659] Step 9820 may comprise indications (e.g. arrows in the
corners of the picture frame) on the GUI about adapting the
position of the device, particularly the distance to the respective
plant and the orientation (vertically and horizontally) as well as
the inclination, to enable a standardized picture, which is
suitable for subsequent analysis. For more details, see FIGS.
99-101.
[2660] Step 9830 may comprise moving the device back and forth,
tilting the device, etc. until the picture of the target object,
e.g. plant or growing cabinet including plants, seen by the camera
of the device, i.e. as depicted on the "viewer" of the app, matches
with the picture frame. For more details, see FIGS. 99-101.
[2661] Step 9850 may comprise shooting still pictures as well as
motion pictures (videos). Shooting may be assisted by flash or
continuous light in the visible (white or colored) or infrared
range of the spectrum.
[2662] Step 9870 may comprise image recognition and data analytics
(algorithms, AI) for evaluating the plant growth status and plant
health. This may involve calculating Leaf Area Index or Normalized
Difference Vegetation Index, detecting coloring/pigmentation,
number of fruits and vegetables, plant morphology, etc.
[2663] Step 9870 may further comprise graphical output, e.g.
graphs, growth trackers, time-lapse videos, etc., to represent the
results of the analysis. This may comprise topographic maps or 3D
data models based on different pictures, e.g. taken at different
positions, possibly also under different angles.
[2664] Step 9870 may further comprise displaying scores and badges
according to the grower's success, based on real-time, historical
and benchmarking data.
[2665] Step 9870 may further comprise comparing the captured
pictures with a picture database to determine plant abnormalities,
e.g. mold, pest, nutrient lack, tip burn, etc. In a refinement of
the method for agricultural management according to the disclosure,
further steps may suggest adjustments to the present growing
conditions.
[2666] FIG. 94 schematically shows an example 9900 of an image 9910
of a growing cabinet (object) in the "viewer" screen (viewfinder)
of an embodiment (e.g. software app running on a mobile device) of
the method for agricultural management according to the disclosure.
The (image of the) cabinet 9910 comprises two vertically stacked
drawers 9912.1, 9912.2 in which plants 9914.1, 9914.2 are arranged,
in some embodiments/implementations leafy greens and herbs. The
picture frame 9920 comprises arrows 9930.1-9930.4 (four arrows, one
arrow in each corner of the frame oriented to the center of the
frame) that indicate to the user to move the device (e.g.
smartphone running the app) closer to the growing cabinet 9910. A
red light 9940 indicates that the frame 9920 and the image 9910 of
the object are misaligned.
[2667] FIG. 95 schematically shows another view 10000 of the
example shown in FIG. 94. Again, the red light 9940 indicates a
misalignment between the picture frame 9920 and the object 9910
(plant cabinet). Here the arrows 9930.1-9930.4 indicate to the user
to move the device (e.g. smartphone running the app) closer to the
growing cabinet 9910.
[2668] FIG. 96 shows a view 10100 of the example of FIG. 94 with a
corrected position of the device, i.e. now the frame 9920 and the
(image of the) object 9910 are aligned (no arrows displayed),
indicated by a green light 10140. In other words, the device is now
in the correct position for taking a picture of the object 9910
(growing cabinet) according to the defined standard.
[2669] FIG. 97 shows an example of a result 10200 of an analysis of
the standardized picture captured in FIG. 96. The analysis depicts
a growth height 10210 of the plants (culinary herbs), detected from
the captured picture. Based on the height 10210, the software app
calculates the plant growth status (70%) and the harvest date (e.g.
October 16). Furthermore, based on the standardized picture 101,
the software app evaluates the health status (e.g. good). The
result of the analysis is displayed on a dashboard 10220.
[2670] FIG. 98 shows another example of a result 10300 of an
analysis of a standardized picture of e.g. basil or oregano. In
this example, the analysis of the growth status is based on the
Leaf Area Index detected from a suitable part 10310 of the picture,
i.e. at least one leaf of the plants. Again, the result is depicted
on a dashboard 10320 (in this example the result is the same as the
one shown in FIG. 97).
[2671] FIG. 99 shows a schematic block diagram of a controlled
agricultural system 100 for an agricultural facility 10400,
according to the disclosure. The controlled agricultural system 100
comprises a computing device 140, a data storage device 170,
coupled to the computing device 140, an actuator device 310,
coupled to the computing device 140 via a control unit 130.1, a
sensor device 150, coupled to the computing device 140 via a second
control unit 130.2 and lighting fixtures 110 (one lighting fixture
or multiple lighting fixtures), coupled to the computing device 140
via a third control unit 130.3.
[2672] The data storage device 170 or even the computing device 140
may be based locally (on-site) or in a (centralized) network or the
cloud. Furthermore, the data storage device 170 may also be
integrated into the computing device 140. The data storage device
170 may include a (digital/online-) platform, e.g. located in the
cloud. The platform may also be accessible by a mobile device 101,
e.g. laptop PC, tablet PC or smartphones via dedicated apps.
Therefore, a user may access the platform via the computing device
140 or the mobile device 101. Furthermore, the platform may
comprise dashboards customized to various user groups such as
growers and customers.
[2673] The data storage device 170 comprises a database in which
growth settings, including light recipes and temperature profiles
(temporal and/or spatial), for various plants are stored. The
database may also comprise data documenting previous plant
projects, e.g. from other growers using the same platform.
[2674] The computing device 140 is configured to control the
actuator device 310 based on the data stored in the data storage
device 170, e.g. for (re-) adjusting the temperature according to
the temperature profile of the respective plant species.
[2675] Furthermore, the computing device 140 is configured to
collect the data from the sensor device 150, e.g. for monitoring
the environmental conditions in the agricultural facility and/or
the plant growth.
[2676] The computing device 140 is configured to control the
lighting fixtures 110 based on the data stored in the data storage
device 170, e.g. according to the light recipes of the respective
plant species.
[2677] In a refined embodiment, the lighting fixtures 110 and/or
the actuators 310 are configured for direct access and control via
the mobile device 101, e.g. by means of a dedicated software
application (app). For instance, the lighting fixtures 110 and the
actuators 310 comprise sensors (photoelectrical, piezo, etc.).
Furthermore, the app is designed to control and regulate the
lighting fixtures 110 and the actuators 310 based on executable
command data transmitted by the mobile device 101.
[2678] For instance, the user may accept a new, improved or more
appropriate light recipe or any other adjustment of the
environmental and/or growth conditions suggested by the app and
execute it directly via the mobile device 101. An advantage of this
operation mode is that it also works if the computer-based system
is down or even without it.
[2679] Furthermore, the executable command data send by the mobile
device 101 may comprise dedicated (ultra)sonic sequences generated
by the speaker of the mobile device or modulations of a photoflash
LED or a specific IR-LED.
[2680] FIG. 100 shows a representation of a control unit 10502 of a
breeding and/or growing and/or raising facility 10601 (see FIG.
101) according to an embodiment of "Eco Certificates" as well as
"Medical Certificates". The control unit 10502 comprises at least
one input device 10510, a computing device 10520 and an output
device 10530. Here, as data sources, the input device 10510 may
comprise, inter alia, one or more databases 10512, one or more
sensor system arrangements 10514 and/or manual input means 10516.
The database 10512, or databases, can be stored both on local
storage media, mobile storage media or so-called cloud storage
media, i.e., nonlocal, decentralized storage media. The database or
databases 10512 can store data in respect of the breeding and/or
growing and/or raising facility 10601 per se, i.e., information
items about the components used in the breeding and/or growing
and/or raising facility or the products, such as plant or animal
products, produced therein. Moreover, it is conceivable that more
in-depth information items in respect of the products to be
produced or the components employed are stored in the database or
databases 10512, for example a life-cycle assessment of planted
products or raised animals, data sheets of employed components such
as, for example, light modules, or the like. Moreover, the database
or the databases 10512 may contain light recipes.
[2681] Here, a sensor system arrangement 10514 is understood to
mean one or more sensors that acquire data and that are connected
indirectly or directly, for example via an interface, to the
computing device 10520. The employed sensors of the sensor system
arrangement 10514 can be cameras, LIDAR, radar, spectroscopes,
sensors for measuring temperature, humidity or pH value, and other
sensors. By way of example, further sensors may be able to acquire
a growth, a maturity state, the occurrence and/or advance of
diseases or pests, a mineral or vitamin content of plants to be
grown or the like. To this end, the sensors of the sensor system
arrangement can also be connected to one another, to a database
and/or to a further computing device.
[2682] Manual input means of the input device 10510 can allow
manual input on the part of a user or operator. Here, the content
of the input can be light recipes or modifications to light
recipes, for example.
[2683] Moreover, manual input means may also contain customer
wishes, for example prescriptions from customer orders.
[2684] The computing device 10520 serves primarily to calculate and
carry out light recipes for controlling an illumination device
10534. Moreover, the computing device can serve to evaluate sensor
data from the sensor system arrangement 10514, for example in order
to adapt a light recipe on the basis of sensor data, or in order to
propose such an adaptation. Incidentally, the computing device
10520 can also be embodied to control the entire breeding and/or
growing and/or raising facility. To this end, the computing device
10520 may also comprise a plurality of units. Here, the individual
units may be connected to one another. In addition to a light
control, there can also be, for example, the control of watering,
feeding, fertilizing, climate control and the like.
[2685] Moreover, on the basis of the input prescriptions and
information items, the computing device can calculate, decide
and/or propose that alternative light recipes are more suitable
within the scope of the selected options, have a higher efficiency,
have a better life-cycle assessment, or the like. In this respect,
the computer unit 10520 may also comprise an intelligent control or
a self-learning control for improved actuation of the breeding
and/or growing and/or raising facility 10601.
[2686] In the present case, an output device 10530 is understood to
mean the components of the breeding and/or growing and/or raising
facility 10601 in respect of which there is an output of data
and/or control commands from the computing device 10520. Firstly,
this comprises the illumination device 10534, which is used to
illuminate the products and by means of which the light recipes are
applied. Moreover, one or more display units 10536 can be provided
in the output device 10530. A display unit 10536 can be provided or
usable for displaying very different contents. Thus, a display unit
10536 renders it possible to display, for example, an advance of
the growth of the products, a currently applied light recipe, a
future prediction of the growth, an order process, an advance of
order processes and the like. Here, a display unit 10536 can be,
for example, a monitor, a display of a mobile device, and other
apparatuses such as projectors, VR glasses or AR glasses and the
like.
[2687] Moreover, the output device 10530 may contain one or more
databases 10532. Here, in particular, it is also conceivable for
the databases 10532 of the output device 10530 to be identical or
partly identical with the databases 10512 of the input device
10510.
[2688] FIG. 101 shows a representation of a breeding and/or growing
and/or raising facility according to an embodiment of the
disclosure. In particular, FIG. 101 illustrates a flowchart of how
light recipes that have been assessed by a life-cycle assessment
can be used in a breeding and/or growing and/or raising facility
according to current or stored sensor data and/or other influencing
factors, or how they can be adapted thereto. As already described
in respect of FIG. 100, various sensor data are evaluated to this
end. Depending on type, the various sensor data can be stored in
different databases. Thus, for example, sensor system arrangements
of internal or external sensor system arrangements may interact
with a communications unit, the latter facilitating communication
with other illumination devices and/or with the database and an
external device. Moreover, database information items or further
sensor data may include surrounding factors, such as watering,
ventilation, fertilization, natural light as additional light, and
time zones and the like. By way of example, other sensor data may
contain data relating to the outside of the plant or the
surroundings thereof, such as, for example, data in relation to
air, ground, external environment, light conditions, LAI, LAD, or
data relating to the interior of the plant.
[2689] Further sensor data could originate from, for example,
camera, lidar, radar or similar sensors and/or may contain
illumination variables, for example in respect of the spectrum,
photon flux, mode of operation and the like.
[2690] The data captured thus can be evaluated together with
information items from a database, which, for example, may contain
light data, operational values and specifications for light recipes
for light fixtures or light fixture groups. In this way, it is
possible to acquire a life-cycle assessment or the individual
life-cycle assessment variables, for example. The life-cycle
assessment variables acquired thus can be evaluated in the
computing device 10520 or in a further computing device and a
life-cycle assessment can be created. Moreover, residual amounts of
light or residual irradiation durations, for example, can be
established from the data. The data established thus can then be
made available in a suitable manner by means of a display or
communications unit. Here, the communications unit may also contain
means for communication via a network, in particular for presenting
the established contents on mobile devices of a user, operator
and/or customer.
[2691] It should be noted that an evaluation or a pre-evaluation
may also be implemented in the input device 10510 and this need not
exclusively take place in the computing device 10520. This is
indicated by the overlap of the region that is surrounded by dashed
lines in FIG. 101, which is intended to symbolize the computing
device 10520, and of the region that is surrounded by dash-dotted
lines, which is intended to symbolize the input device 10510. Here,
moreover, the aforementioned database with light recipes can obtain
information items from a further database and evaluation unit and
control unit, or exchange data therewith. These data can be taken
into account in the case of an assessment, selection or
specification of light recipes and, in turn, can be input in the
computing device in respect of an application of the operational
data for regulating light. The computing device can control an
illumination on the basis of the input and/or stored data, for
example an illumination device or a breeding and/or growing and/or
raising facility or a part thereof.
[2692] The list below provides an overview of the respective
function of the blocks of the block diagram shown in FIG. 101.
[2693] 106.A Sensor system arrangements (internal and external).
[2694] 106.B Communication with other illumination devices and/or
with the database and evaluation unit. [2695] 106.C Environmental
parameters (watering, ventilation, fertilization, natural light as
additional light, time zones). [2696] 106.D Applying the operation
data for light control. [2697] 106.E Database and evaluation unit
and control unit (illumination, light fixture configuration,
surrounding factors). [2698] 106.F Sensor system external to plant
(air, ground, external environment, light conditions, LAI, LAD),
internal in plant. [2699] 106.G Illumination device [2700] 106.H
Database for light recipes (light data and operational values).
Specifying light recipe for light fixture or light fixture group.
[2701] 106.I Establishing life-cycle assessment and residual light
amount. [2702] 106.J Display and I communications unit. [2703] 106.
K Acquiring life-cycle assessment variables. [2704] 106.L Sensor
system (camera, LIDAR, radar, etc.) illumination variables
(spectrum, photon flux, mode of operation).
[2705] FIG. 102 shows the schematic construction of a building
complex for a breeding and/or growing and/or raising facility 10701
according to an embodiment of the present disclosure. According to
the shown embodiment, the breeding and/or growing and/or raising
facility AG 10710 comprises a plurality of building parts A.sub.i
(i=1, 2, 3, . . . n). Each building part A.sub.i in turn has
different segments S.sub.j, i.e., overall: A.sub.iS.sub.j with j=1,
2, . . . m.
[2706] Each segment A.sub.iS.sub.j may comprise one or more
illumination units B.sub.k, i.e., overall: A.sub.iS.sub.jB.sub.k
with k=1, 2, . . . p.
[2707] Each illumination unit A.sub.iS.sub.jB.sub.k can have, or be
set to, different light scenarios L.sub.x (x=1, 2, . . . r), i.e.,
A.sub.iS.sub.jB.sub.kL.sub.x with x=1, 2, . . . r, where all light
scenarios A.sub.iS.sub.jB.sub.kL.sub.x are known or defined at all
times t.sub.y (with y=1, 2, . . . s); these light scenarios can
then be coupled to the growth/breeding and/or growing and/or
raising process or an ordering process BS.
[2708] Hence, the respective energy costs can be established for
each of the light scenarios A.sub.iS.sub.jB.sub.kL.sub.x. At a
given time T.sub.z (with z=1, 2, . . . t), there is exactly one
A.sub.iS.sub.jB.sub.kL.sub.xT.sub.z data point which, of course,
may assume different values for each time, i.e., each T.sub.z.
Here, a current energy consumption
EDP(A.sub.iS.sub.jB.sub.kL.sub.xT.sub.z) can be assigned to each
data point.
[2709] A light recipe LR is program code, which selects and carries
out a set or variable or interactively determinable sequence of
light scenarios. Consequently, each light recipe LR.sub.e (e=1, 2,
. . . u) can be assigned a sequence of light scenarios
A.sub.iS.sub.jB.sub.kL.sub.x or the associated data points
A.sub.iS.sub.jB.sub.kL.sub.xT.sub.z or the energy costs
EDP(A.sub.iS.sub.jB.sub.kL.sub.xT.sub.z) connected therewith, or
the sum values SUM EDP(A.sub.iS.sub.jB.sub.kL.sub.xT.sub.z) can be
formed.
[2710] Now, an order process BS can be linked to one or more light
scenarios A.sub.iS.sub.jB.sub.kL.sub.x or respective sum values SUM
EDP(A.sub.iS.sub.jB.sub.kL.sub.xT.sub.z), and it is consequently
possible to specify an energy consumption per order process
BS.sub.w (w=1, 2, . . . v), i.e., BS.sub.w(SUM
EDP(A.sub.iS.sub.jB.sub.kL.sub.xT.sub.z)). Then, the latter can be
communicated to an operator, customer, etc., by way of a display,
by way of an app or in any other way and on other devices for
display, as already mentioned above. Hence, an operator or customer
knows about the energy costs per order and can regularly recall
this information item, can predict this into the future and the
like, even during the production process.
[2711] A light scenario can be controlled by program code which can
use current measurement variables such as plant growth, degree of
maturity, weather conditions, cost of electricity from the various
energy sources, etc., as control parameters in the program code.
Sensors or measurement variables can be directed to the properties
of the illumination arrangements relating to radiation. Here, light
scenarios A.sub.iS.sub.jB.sub.kL.sub.x of the illumination unit
A.sub.iS.sub.jB.sub.k are referred to as measurement record M1.
They can also be directed to properties specific to the
surroundings, such as, for example, radiation reflection on the
leaf and ground, temperature, humidity, etc. This measurement
record is referred to as M2.
[2712] In this way, it is also possible to create an overall energy
footprint per light recipe or per order and highlight this to an
operator and/or customer. This can then be used by the operator for
modifying the growing conditions or by the customer in respect of
their order, or possible cancellation.
[2713] In particular, the present disclosure allows an operator or
customer to also consider one or more ecological boundary
conditions, such as, for example, the availability of energy
sources, nuclear power, state funding, energy imports, energy
exports, energy storage, CO.sub.2 footprints, etc.
[2714] Table 6.1 below provides an overview of the employed indices
for better comprehension of the above-mentioned considerations.
TABLE-US-00007 TABLE 6.1 Breeding and/or growing and/or raising
facility AG Building A i 1-n Segments S j 1-m Illumination unit B k
1-p Light scenario L x 1-r Time T y s Integration time Delta-T z t
Energy consumption per data point EDP Light recipe LR e 1-u Order
process B w 1-v
All numbers are integers here. All indices are integer values.
T.sub.z=e.g., in the millisecond, second or minute range.
[2715] A light recipe can also specify the sum photon flux, for
example expressed in .mu.E/(m.sup.2s), specifically also the photon
flux in the photosynthetically active radiation PAR range.
[2716] Below the respective function of some of the blocks of the
block diagram shown in FIG. 102 are listed (the other ones have
already been explained above). [2717] 107.A Acquiring and/or
calculating unit and evaluation unit. [2718] 107.B Database of
light recipes; energy evaluation and assignment to light recipe.
[2719] 107.C Correlating light recipe to product. [2720] 107.D
Presentation and communication of product selection: energy
consumption of light recipe or energy consumption per desired order
process BS; selecting light recipe. [2721] 107.E Customer order
process of products based on ecologically rated lighting and/or
growing conditions. [2722] 107.F External control variables
(ecology, environmental factors, etc.). [2723] 107.G Interface to
FIG. 103.
[2724] FIG. 103 shows a more detailed representation of a
measurement and control device according to an embodiment of the
present disclosure. As emerges from FIG. 103, an evaluating device
may exchange data with a control device, and so sensor data and the
like, which are acquired and evaluated by the evaluating device,
can be used for controlling a breeding and/or growing and/or
raising facility. The control device can store data in respect of a
light recipe, or other data, in a database. Moreover, the control
device can call or activate light recipes from the database, said
light recipes then being used for controlling an illumination unit.
Here, the light recipe is transmitted to a control unit for an
illumination unit or an overall irradiation apparatus and there is,
either in a centralized or else decentralized fashion, an actuation
of the individual light sources of an illumination unit.
Ultimately, this leads to the emission of light of the selected
light sources.
[2725] The illumination produced thus can be evaluated, in turn,
within the scope of a control loop in an evaluation device, i.e.,
for example, in the computing device 10520. The data of the
evaluation device fed to the control device, and also further data,
can then inform a customer, an operator or other interested parties
about the respective product status, for example at regular
intervals, upon request, or else in real time. These information
items may moreover contain a delivery status, data in respect of a
residual irradiation amount, storage conditions and preconditions
and the like. The light recipes selected for illumination purposes
can likewise be communicated to a customer or user, or these can be
provided for selection purposes. Here, further aspects can be
selected for the respective product selection, such as, e.g., the
energy or the energy consumption of a certain light recipe or the
energy per desired order process. As already described, a customer
can then select on a transfer platform the products on the one hand
and the respective energy-assessed light scenarios on the other
hand. This applies analogously to operators of breeding and/or
growing and/or raising stations.
[2726] The corresponding order process or the customer wishes for
an order can then be taken into account as further controlled
variables, as a manual input as in the previous case.
[2727] Therefore, the control device for controlling the
illumination device 10534 can be embodied to acquire measurement
variables, data of the evaluation device, orders and the like. The
control device can also be embodied to take account of
customer-interactive modifications, automated orders that are
triggered by a predetermined manipulated variable being reached,
e.g., sensor measurements, order parameters and the like. Moreover,
the determination of a residual light amount, a time duration of
the irradiation or the residual irradiation and the like can be
determined in the control device or can be taken into account for
the control. Here, the control device can be part of a central
computing device of the breeding and/or growing and/or raising
facility. The control device can also be part of one or more
illumination apparatuses, wherein a breeding and/or growing and/or
raising facility may have a plurality of illumination
apparatuses.
[2728] Here, according to an embodiment of the present disclosure,
the interfaces of FIG. 102 and FIG. 103 may represent a transfer
platform, for example, on which customers and operators of a
breeding and/or growing and/or raising facility can use a common
database in order to carry out trade in respect of the products
and/or the light recipes. Moreover, it is conceivable that
customers are able to modify their orders, even still during a
growth process, adapt delivery times or delivery amounts or adapt
other parameters of the products, for example by purchasing or
modifying alternative light recipes.
[2729] The list below provides an overview of the respective
function of the blocks of the block diagram shown in FIG. 103.
[2730] 108.A Database for light recipe(s). [2731] 108.B Control
unit for the illumination unit/irradiation device. [2732] 108.C
Actuating the light sources of an illumination unit. [2733] 108.D
Light sources. [2734] 108.E Sensors for measuring light and
radiation variables; M1. [2735] 108.F Control device: acquiring:
measurement variables, evaluation device, order. Additionally,
customer-interactive modifications, also an automated order
triggered by a manipulated variable being reached (measurements,
order parameters). Determining the residual light amount, time
duration of the irradiation or residual irradiation. [2736] 108.G
Evaluation device. [2737] 108.H Sensors and measurement device of
plant specific and/or surroundings-specific parameters with data
acquisition and storage; M2. [2738] 108.I Interface from FIG. 102.
[2739] 108.J Presentation and communication of product selection:
energy of light recipe or energy for desired order process BS;
selecting light recipe. [2740] 108.K Customer order process of
product and energy-assessed light scenarios. Operator breeding
and/or growing and/or raising control. [2741] 108.L Customer
information about product status, delivery status, residual light
amount, storage conditions etc.
[2742] FIG. 104 shows a representation of a breeding and/or growing
and/or raising facility according to an embodiment of the
disclosure (particularly of the element "Medical Certificate") that
is based on the embodiment shown in FIG. 101. More specifically,
the block diagram 10901 shown in FIG. 104 comprises all the blocks
106.A-106.L of the block diagram shown in FIG. 101. Therefore,
reference is made to the description of FIG. 101 including the
description of the blocks 106.A-106.L above to avoid duplication of
the respective text.
[2743] In addition to the blocks 106.A-106.L already described
above, the supplemental blocks 109.A-109.E are added in FIG. 104.
The function of the supplemental blocks is described in the
following. [2744] 109.A Receiving light recipe from a customer and
coupling to a plant product, illumination location and illumination
unit. [2745] 109.B Certification body. [2746] 109.C Database for
certified light recipes. [2747] 109.D App for selection of light
recipes for growth product, and for selecting a provider or
producer, and for triggering an order process, and for the
interactive creation of a light recipe, and for capturing a
customer measurement. App may also be interactive (other customers,
user group). [2748] 109.E Customer measurement (determination of
active ingredients).
[2749] As emerges further from FIG. 104, a further database may be
provided for certified light recipes. This further database can be
provided internally as part of the input device 10510, i.e., in the
system of the breeding and/or growing and/or raising facility 10701
(see FIG. 102) or the control unit 10502 (see FIG. 100). However,
it is likewise conceivable that the further database for certified
light recipes is available externally, for example at a certifying
body such as the department of health, licensing authorities or
other establishments or databases.
[2750] This further database then can have corresponding interfaces
with certification bodies. Moreover, the further database can have
interfaces to a user output device, for example a user application,
which is also referred to as app here. The app may be provided for
selecting light recipes for growing products. Moreover, the app can
be embodied or provided for selecting a provider or producer and
for triggering an order process. Furthermore, the app can be
provided for interactive creation of a light recipe and for
creating a coupled light recipe. Moreover, it is conceivable for
the app to be embodied to form a sensor system by way of a
software/hardware interface or to be connected to an external
sensor system for the purposes of acquiring a customer measurement,
for example for determining active ingredients or content
concentrations of a product. Moreover, the app can be embodied in
interactive fashion, i.e., for use by a plurality of users or whole
groups of users.
[2751] Incidentally, the app can constitute an interface between
the control unit 10502 (see FIG. 100) and external databases. Here,
for example alternative light recipes or variations for light
recipes can be output from an internal database or evaluation
unit.
[2752] During the order process, a customer themselves can specify
a light recipe, for example a medical light recipe. By way of
example, this can be implemented on the basis of experience, tests
or else on account of suggestions from a possible user group. The
system may now accept this light recipe and adopt the latter in the
breeding and/or growing and/or raising program and then implement
said light recipe in a certain breeding and/or growing and/or
raising process, for example in respect of the location and/or the
time, in particular on plants that are then provided for the
respective customer. Naturally, this assumes that the light recipe
is accepted by the database, in particular in relation to the
observation of legal requirements or in relation to the
implementability of the light program. This test can be carried out
by an app. Here, the app can call or use information items, for
example current light fixture data such as the type of LEDs, the
age thereof, the location or position thereof, and/or possible
light recipes that are realizable by the light fixture, for example
in the case of a reinstallation of a light fixture, and others. To
this end, the app can communicate with the sensors of the breeding
and/or growing and/or raising facility or else prompt the latter to
carry out the current measurement, then said app can evaluate said
data and consequently check whether the light recipe can be
implemented using the available light fixtures or whether, for
example on account of occupancy, the light recipe and hence the
order process can be implemented at the order time desired by the
customer. What may occur in the process is that this problem cannot
be clearly implemented or that the problem cannot be solved by the
software. Consequently, the app can trigger technical method steps
that contain the communication with sensors and actuators, the
prompt for a current measurement, the collection and evaluation of
the data, the presentation of the result and a decision or a
plurality of alternatives for the solution. The app can also cause
data from sensors and/or actuators to have to be made available
within a certain time frame. Thus, for example, the app can accept
or discard the incoming data on account of the time frame thereof,
too. In the process, the app can also cause a repetition of a
measurement by virtue of renewed prompting of a sensor or an
actuator.
[2753] The use of an app as described above or the control or
monitoring of a growth process by means of a corresponding
application on a computing device such as a computer, tablet
computer, cellular telephone, etc., can moreover allow a
corresponding use of the appliance or of the app for outputting
data as part of the output device 10530 (see FIG. 100).
[2754] Referring again to FIG. 102, the respective light data can
be acquired, e.g. by means of sensors and evaluation devices, or
calculated (on account of known light properties of the light
sources) for each of the light scenarios
A.sub.iS.sub.jB.sub.kL.sub.x. This acquisition can be implemented
in defined spectral ranges, e.g. UV-B (380-415 nm), or in the blue,
red or dark-red range. The acquirable variables include, for
example, irradiance, incoming radiation angle, polarization, photon
flux, light modulation, pulsed operation, and then also the times
and time intervals of zero measurements such as during dark stages,
which of course also have a decisive contribution to the quality of
the products. This is referred to as measurement set M3 and the
latter can contain a multiplicity of individual measured values
(and correlation values).
[2755] Moreover, a sequence of light scenarios
A.sub.iS.sub.jB.sub.kL.sub.x or the associated data points
A.sub.iS.sub.jB.sub.kL.sub.xT.sub.z or the measurement sets
M.sub.3(A.sub.iS.sub.jB.sub.kL.sub.xT.sub.z) associated therewith
can be assigned to each light recipe LRe (e=1, 2, . . . u) or the
summed value SUM(A.sub.iS.sub.jB.sub.kL.sub.xT.sub.z) or SUM
M.sub.3(A.sub.iS.sub.jB.sub.kL.sub.xT.sub.z) can be formed.
[2756] The data SUM(A.sub.iS.sub.jB.sub.kL.sub.xT.sub.Z) or SUM
M.sub.3(A.sub.iS.sub.jB.sub.kL.sub.xT.sub.z) can be stored and
evaluated, for example for individual time measurements, time
interval measurements, overall measurement times and said data can
also be correlated with other measurement variables or influencing
factors (correlation factors K). The results can then be presented
graphically (display, VR or AR glasses) and/or communicated to a
customer or interested party or else the operator of the facility
AG in any other suitable form. Consequently, a multidimensional
effective space can be created.
[2757] A light scenario can be controlled by program code, which
can use current measurement variables such as plant growth,
concentration of active ingredients, concentration of toxic plant
ingredients, degree of maturity, weather conditions, electricity
costs of the various energy sources, etc., as control parameters in
the program code. Sensors or measurement variables can be designed
for the radiation properties of the illumination arrangements
(light scenarios A.sub.iS.sub.jB.sub.kL.sub.x of the illumination
unit A.sub.iS.sub.jB.sub.k are referred to here as measurement set
M1), or they can be designed for environment-specific properties
such as, for example, radiation reflection on the leaf and on the
ground, temperature, humidity, etc. This measurement set is denoted
M2 or plant-inherent active ingredients (concentrations of vitamin
C, stress indicators, etc.) are measured, possibly with the aid of
fluorescence measurements (measurement set M3). For reasons of
simplicity, the measurement sets M1, M2 and M3 are subsumed by the
term measurement set MM.
[2758] An order process BS can now be connected to one or more
light scenarios A.sub.iS.sub.jB.sub.kL.sub.x or the respective
summed values SUM(A.sub.iS.sub.jB.sub.kL.sub.xT.sub.z) and SUM
M.sub.3(A.sub.iS.sub.jB.sub.kL.sub.xT.sub.z) and the expected
effect functions W and, optionally, to the correlation factors K as
well, and can consequently reveal an expected effective variable
per order process Wf (f=1, 2, . . . y) and this can then be
communicated to an operator, customer, etc. (display, per app,
etc.). Hence, an operator or customer is informed with knowledge
about the (expected) effective variables per product order.
[2759] The aforementioned measurement or determination variables
SUM(A.sub.iS.sub.jB.sub.kL.sub.xT.sub.z) and SUM
M.sub.3(A.sub.iS.sub.jB.sub.kL.sub.xT.sub.z) and the expected
effect functions W and, optionally, the anticipated correlation
factors K as well can be assessed or certified by a certification
body (e.g., health office, benevolent societies, self-help
groups).
[2760] A light recipe created by a customer can be protected and
consequently be able to be licensed where applicable. Customers or
users can exchange, discuss, optimize, etc., light recipes via
social networks, user groups, etc.
[2761] Table 1 below provides an overview of the employed indices
for better comprehension of the above-mentioned considerations.
TABLE-US-00008 TABLE 1 Breeding and/or growing and/or raising
facility AG Building A i 1-n Segments S j 1-m Illumination unit B k
1-p Light scenario L x 1-r Time T y s Integration time Delta-T z t
Energy consumption per data point EDP Light recipe LR e 1-u Order
process B w 1-v Effect values WW
All numbers are integers here. All indices are integer values.
T.sub.z=e.g., in the millisecond, second or minute range.
[2762] A light recipe can also specify the sum photon flux, for
example expressed in .mu.E/(m.sup.2s), specifically also the photon
flux in the photosynthetically active radiation PAR range
Measurement sets M1, M2, M3, MM.
[2763] FIG. 105 shows a representation of a measurement and control
device according to an embodiment of the disclosure (particularly
of the element "Medical Certificate") that is based on the
embodiment shown in FIG. 103. More specifically, the block diagram
shown in FIG. 105 comprises all the blocks 108.A-108.L of the block
diagram shown in FIG. 103. Therefore, reference is made to the
description of FIG. 103 including the description of the blocks
108.A-108.L above to avoid duplication of the respective text.
[2764] In addition to the blocks 108.A-108.L already described
above, the only one supplemental block 110.A is added in FIG. 105.
The function of the supplemental block is as follows: [2765] 110.A
User groups, self-help groups, certification body for defining and
selecting suitable light recipes.
[2766] It is moreover conceivable that there is communication as to
what light recipes were created by customers or users, or whether a
light recipe is an adapted light recipe or original light
recipe.
[2767] FIG. 106 shows a schematic overview of tasks and steps for
operating the Controlled Agricultural System according to the
disclosure. The abbreviation ALF denotes the agricultural light
fixture and the abbreviation CAS denotes the Controlled
Agricultural System. The tasks and steps are managed by the
agriculture management software on the basis of the available data,
e.g. data from the sensors of the CAS. To this end the agriculture
management software comprises a plurality of program instructions,
which when executed by the computer system of the CAS, cause the
CAS to execute the tasks and steps as shown in FIG. 106.
Other Considerations
[2768] While various embodiments have been described and
illustrated herein, those of ordinary skill in the art will readily
envision a variety of other means and/or structures for performing
the function and/or obtaining the results and/or one or more of the
advantages described herein, and each of such variations and/or
modifications is deemed to be within the scope of the embodiments
described herein. More generally, those skilled in the art will
readily appreciate that all parameters, dimensions, materials, and
configurations described herein are meant to be exemplary and that
the actual parameters, dimensions, materials, and/or configurations
will depend upon the specific application or applications for which
the teachings is/are used. Those skilled in the art will recognize,
or be able to ascertain using no more than routine experimentation,
many equivalents to the specific inventive embodiments described
herein. It is, therefore, to be understood that the foregoing
embodiments are presented by way of example only and that, within
the scope of the appended claims and equivalents thereto,
embodiments may be practiced otherwise than as specifically
described and claimed. Embodiments of the present disclosure are
directed to each individual feature, system, aspect, article,
material, kit, and/or method described herein. In addition, any
combination of two or more such features, systems, aspects,
articles, materials, kits, and/or methods, if such features,
systems, aspects, articles, materials, kits, and/or methods are not
mutually inconsistent, is included within the inventive scope of
the present disclosure. Particularly, any element of the disclosure
and any aspect thereof may be combined, in any order and any
combination, with any other element of the disclosure and any
aspect thereof.
[2769] The above-described embodiments can be implemented in any of
numerous ways. For example, the embodiments may be implemented
using hardware, software or a combination thereof. When implemented
in software, the software code can be executed on any suitable
processor or collection of processors, whether provided in a single
computer or distributed among multiple computers.
[2770] Further, it should be appreciated that a computer may be
embodied in any of a number of forms, such as a rack-mounted
computer, a desktop computer, a laptop computer, or a tablet
computer. Additionally, a computer may be embedded in a device not
generally regarded as a computer but with suitable processing
capabilities, including a Personal Digital Assistant (PDA), a smart
phone or any other suitable portable or fixed electronic
device.
[2771] Also, a computer may have one or more input and output
devices. These devices can be used, among other things, to present
a user interface. Examples of output devices that can be used to
provide a user interface include printers or display screens for
visual presentation of output and speakers or other sound
generating devices for audible presentation of output. Examples of
input devices that can be used for a user interface include
keyboards, and pointing devices, such as mice, touch pads, and
digitizing tablets. As another example, a computer may receive
input information through speech recognition or in other audible
format.
[2772] Such computers may be interconnected by one or more networks
in any suitable form, including a local area network or a wide area
network, such as an enterprise network, and intelligent network
(IN) or the Internet. Such networks may be based on any suitable
technology and may operate according to any suitable protocol and
may include wireless networks, wired networks or fiber optic
networks.
[2773] The various methods or processes outlined herein may be
coded as software that is executable on one or more processors that
employ any one of a variety of operating systems or platforms.
Additionally, such software may be written using any of a number of
suitable programming languages and/or programming or scripting
tools, and also may be compiled as executable machine language code
or intermediate code that is executed on a framework or virtual
machine.
[2774] In this respect, various disclosed concepts may be embodied
as a computer readable storage medium (or multiple computer
readable storage media) (e.g., a computer memory, one or more
floppy discs, compact discs, optical discs, magnetic tapes, flash
memories, circuit configurations in Field Programmable Gate Arrays
or other semiconductor devices, or other non-transitory medium or
tangible computer storage medium) encoded with one or more programs
that, when executed on one or more computers or other processors,
perform methods that implement the various embodiments of the
disclosure discussed above. The computer readable medium or media
can be transportable, such that the program or programs stored
thereon can be loaded onto one or more different computers or other
processors to implement various aspects of the present disclosure
as discussed above.
[2775] The terms "program" or "software" are used herein in a
generic sense to refer to any type of computer code or set of
computer-executable instructions that can be employed to program a
computer or other processor to implement various aspects of
embodiments as discussed above. Additionally, it should be
appreciated that according to one aspect, one or more computer
programs that when executed perform methods of the present
disclosure need not reside on a single computer or processor, but
may be distributed in a modular fashion amongst a number of
different computers or processors to implement various aspects of
the present disclosure.
[2776] Computer-executable instructions may be in many forms, such
as program modules, executed by one or more computers or other
devices. Generally, program modules include routines, programs,
objects, components, data structures, etc. that perform particular
tasks or implement particular abstract data types. Typically, the
functionality of the program modules may be combined or distributed
as desired in various embodiments.
[2777] Also, data structures may be stored in computer-readable
media in any suitable form. For simplicity of illustration, data
structures may be shown to have fields that are related through
location in the data structure. Such relationships may likewise be
achieved by assigning storage for the fields with locations in a
computer-readable medium that convey relationship between the
fields. However, any suitable mechanism may be used to establish a
relationship between information in fields of a data structure,
including through the use of pointers, tags or other mechanisms
that establish relationship between data elements.
[2778] Also, various inventive concepts may be embodied as one or
more methods, of which an example has been provided. The acts
performed as part of the method may be ordered in any suitable way.
Accordingly, embodiments may be constructed in which acts are
performed in an order different than illustrated, which may include
performing some acts simultaneously, even though shown as
sequential acts in illustrative embodiments.
[2779] All definitions, as defined and used herein, should be
understood to control over dictionary definitions, definitions in
documents incorporated by reference, and/or ordinary meanings of
the defined terms.
[2780] The indefinite articles "a" and "an," as used herein in the
specification and in the claims, unless clearly indicated to the
contrary, should be understood to mean "at least one."
[2781] The phrase "and/or," as used herein in the specification and
in the claims, should be understood to mean "either or both" of the
elements so conjoined, i.e., elements that are conjunctively
present in some cases and disjunctively present in other cases.
Multiple elements listed with "and/or" should be construed in the
same fashion, i.e., "one or more" of the elements so conjoined.
Other elements may optionally be present other than the elements
specifically identified by the "and/or" clause, whether related or
unrelated to those elements specifically identified. Thus, as a
non-limiting example, a reference to "A and/or B", when used in
conjunction with open-ended language such as "comprising" can
refer, in one embodiment, to A only (optionally including elements
other than B); in another embodiment, to B only (optionally
including elements other than A); in yet another embodiment, to
both A and B (optionally including other elements); etc.
[2782] As used herein in the specification and in the claims, "or"
should be understood to have the same meaning as "and/or" as
defined above. For example, when separating items in a list, "or"
or "and/or" shall be interpreted as being inclusive, i.e., the
inclusion of at least one, but also including more than one, of a
number or list of elements, and, optionally, additional unlisted
items. Only terms clearly indicated to the contrary, such as "only
one of" or "exactly one of," or, when used in the claims,
"consisting of," will refer to the inclusion of exactly one element
of a number or list of elements. In general, the term "or" as used
herein shall only be interpreted as indicating exclusive
alternatives (i.e. "one or the other but not both") when preceded
by terms of exclusivity, such as "either," "one of," "only one of,"
or "exactly one of." "Consisting essentially of," when used in the
claims, shall have its ordinary meaning as used in the field of
patent law.
[2783] As used herein in the specification and in the claims, the
phrase "at least one," in reference to a list of one or more
elements, should be understood to mean at least one element
selected from any one or more of the elements in the list of
elements, but not necessarily including at least one of each and
every element specifically listed within the list of elements and
not excluding any combinations of elements in the list of elements.
This definition also allows that elements may optionally be present
other than the elements specifically identified within the list of
elements to which the phrase "at least one" refers, whether related
or unrelated to those elements specifically identified. Thus, as a
non-limiting example, "at least one of A and B" (or, equivalently,
"at least one of A or B," or, equivalently "at least one of A
and/or B") can refer, in one embodiment, to at least one,
optionally including more than one, A, with no B present (and
optionally including elements other than B); in another embodiment,
to at least one, optionally including more than one, B, with no A
present (and optionally including elements other than A); in yet
another embodiment, to at least one, optionally including more than
one, A, and at least one, optionally including more than one, B
(and optionally including other elements); etc.
[2784] In the claims, as well as in the disclosure above, all
transitional phrases such as "comprising," "including," "carrying,"
"having," "containing," "involving," "holding," "composed of," and
the like are to be understood to be open-ended, i.e., to mean
including but not limited to. Only the transitional phrases
"consisting of" and "consisting essentially of" shall be closed or
semi-closed transitional phrases, respectively, as set forth in the
eighth edition as revised in July 2010 of the United States Patent
Office Manual of Patent Examining Procedures, Section 2111.03
[2785] For the purpose of this disclosure and the claims that
follow, the term "connect" has been used to describe how various
elements interface or couple. Such described interfacing or
coupling of elements may be either direct or indirect. Although the
subject matter has been described in language specific to
structural features and/or methodological acts, it is to be
understood that the subject matter defined in the appended claims
is not necessarily limited to the specific features or acts
described. Rather, the specific features and acts are disclosed as
preferred forms of implementing the claims.
Glossary
[2786] Actuators
[2787] Actuators comprise components or devices, usually as part of
a machine, that can transform electric, hydraulic or pneumatic
energy into mechanical movement. Actuators can also be suited to
emit, for example by spraying, herbicides, nutrients, and so
on.
[2788] Agricultural Light Fixtures
[2789] Agricultural light fixtures provide lighting for plants,
algae, fungi, transgenic plants, and any other edible or useable
produce as well as for animals, including transgenic animals,
insects, bacteria, and viruses with natural and/or artificial
electromagnetic radiation.
[2790] The agricultural light fixture may comprise at least one
light module. Said one light module may have a light source and a
driver connected to the light source. Furthermore, the agricultural
light fixture further may have an interface unit, in particular a
hardware interface, configured to receive, emit, and/or store data
signals. The interface unit may be connected to the driver and/or
to the light source for controlling the operation state of the
driver and/or the operation of the light source.
[2791] Agricultural light is applied in order to influence,
stimulate and control the growth and well-being in all stages of
the individual development including shoot development,
reproduction, morphology, maturation, flowering, harvesting and
storage. In the following, due to simplicity, the term `light`
shall encompass the entire electromagnetic wavelength range from
the ultraviolet (100 to 400 nm) to the visible (400-780 nm) to the
infrared (780 nm to 1 mm) spectral range.
[2792] The light source may be configured to emit radiation in the
visible and/or the non-visible spectral range, as for example in
the far-red range and/or in the UV-B region of the electromagnetic
spectrum. It may be configured to emit monochromatic light, e.g.
green light at 525 nm, or narrow band radiation with a Full Width
At Half Maximum (FWHM) smaller than 50 nm, or broadband radiation
with a Full Width At Half Maximum (FWHM) greater than 100 nm. The
light source may be an integral part of the light fixture as well
as a remote yet connected element. It may be placed in various
geometrical patterns, distance pitches and may be configured for
alternating of color or wavelength emission or intensity or beam
angle. The fixture and/or light sources may be mounted such that
they are moveable or can be inclined, rotated, tilted etc. The
fixture and/or light source may be configured to be installed
inside a building or exterior to a building. In particular, it is
possible that the light source or selected light sources are
mounted such or adapted to being automatically controllable, in
some embodiments/implementations remotely, in their orientation,
movement, light emission, light spectrum, sensor etc.
[2793] Agricultural light fixtures can be part of a fixed, moveable
or portable growth or storage place. Agricultural light fixtures
can contain light sources, light source drivers and controllers,
sensors, optical components, actuators, as well as data storage,
processing and one-directional, bi-directional and
multi-directional communication devices. Agricultural light
fixtures can contain heating and cooling devices as well as heat
deflecting devices, such as heat reflective walls.
[2794] Agricultural light fixtures can contain or be made of
transparent polymeric materials, translucent materials, and
specular or diffusive materials.
[2795] Agricultural light fixtures for plant growth can be suited
to modulate light generated by the light sources with a rhythmic or
aperiodic signal produced artificially or a rhythmic signal
extracted from sound present in nature, and can be suited to
illuminate a plant with the modulated light.
[2796] Agricultural light fixtures can be operated based on the
execution of light recipes. Agricultural light fixtures can have
individual identifiers, like an RFID chip or a digital signature or
IP-address, allowing them to be connected to a computer system or
cloud computer network, so that they can be part of an
Internet-of-Things (IoT)-system.
[2797] Agricultural light fixtures can be suited for underwater
lighting, sweet and salt water.
[2798] Agricultural light fixtures can be part of an Industry 4.0
standard.
[2799] Light fixtures of agricultural purposes can contain
artificial light sources like Light Emitting Diodes (LED) with or
without conversion by using a fluorescent substance, commonly
referred to as phosphor, or laser diodes, organic light emitting
diodes (OLED), Quantum Dot light emitters, Fluorescent lamps,
Sodium low and high pressure lamps, Xenon and Mercury Short Arc
lamps, Halogen lamps, and the like. Light fixtures of agricultural
purposes can contain fluorescent or phosphorescent substances, for
example applied to the fixture surfaces. The light source of the
light fixtures of agricultural purposes can be adjusted or be
optimized for use in connection to optical components, such as
reflectors, symmetrical or asymmetrical lenses, filters and so
on.
[2800] Light fixtures of agricultural purposes can be grouped
together or can be arranged in a network or wireframe fashion.
[2801] An agricultural light fixture can be rotated, for example
from lighting top-down to lighting bottom-up at various stages of a
rotary growth cabinet.
[2802] An agricultural light fixture can be made of a flexible
material that is formable, e.g. bendable, and can therefore be
changed in form and shape. An agricultural light fixture can be
comprised of one or several light modules that can be changed,
individually or as a group, in their form and/or position thus
altering the shape and appearance of the fixture.
[2803] In some embodiments, the agricultural light fixture may
comprise a sensor, such as a resistive, a capacitive, an inductive,
a magnetic, an optical and/or a chemical sensor. It may comprise a
voltage or current sensor. The sensor may connect to the interface
unit and/or the driver of the agricultural light source.
[2804] In some embodiments, the agricultural light fixture may
comprise a brightness sensor, for example for sensing environmental
light conditions in proximity of agricultural objects, such as
plants. It may be used for sensing daylight conditions and the
sensed brightness signal may e.g. be used to improve yield and/or
energy efficiency. That way, it may be enabled to provide plants
with a required amount of light of a predefined wavelength, when
natural light conditions, such as daylight conditions, are not
sufficient. It is also possible, in particular when the area to be
illuminated is within an area without natural light, that daylight
conditions are simulated, based on a sensor remote to the light
module or light source of the agricultural light fixture, sensing
the actual daylight conditions. That way, comparison of yield and
influence of lighting conditions of an agricultural light fixture
with respect to natural lighting conditions may be assessed, while
minimizing other natural influences.
[2805] In some embodiments, the agricultural light fixture
comprises a sensor for plant growth, harvesting time, plant
morphology and/or plant health sensing. Such sensor data may allow
a better prediction, as to whether the growth conditions are
sufficient, as to when a harvesting is preferable, whether the
development of the plants are normal and/or on schedule or whether
the state of health of the plants is within acceptable limits.
[2806] The agricultural light fixture may also comprise a presence
sensor. This may allow to adapt the emitted light to the presence
of a farmer or other person in order to provide sufficient
illumination, prohibit or minimize eye damage or skin irritation or
such due to illumination in harmful or invisible wavelength
regions, such as UV or IR. It may also be enabled to provide light
of a wavelength that may warn or frighten away unwanted presences,
e.g. the presence of animals such as pets or insects.
[2807] In some embodiments, the agricultural light fixture
comprises a sensor or multi-sensor for predictive maintenance
and/or operation of the agricultural light fixture failure. This
may allow planning of maintenance of fixtures for times, where
outage of the agricultural light has minimal effect on the growth,
health or other predetermined characteristics of the plants.
[2808] In some embodiments, the agricultural light fixture
comprises an operating hour meter. The operating hour meter may
connect to the driver.
[2809] The agricultural light fixture may comprise one or more
actuators for adjusting the growing conditions for the plants. For
instance it may comprise actuators that allow adjusting the
temperature, humidity, lighting, air, ventilation in the proximity
of the light fixture. It may as well allow the application of
active agents, such as water, nutrients and/or pesticides.
[2810] While the sensor or actuator had been described as part of
the agricultural light fixture, it is understood, that any sensor
or actuator may be an individual element or may form part of a
different element of the Controlled Agricultural System. As well,
it may be possible to provide an additional sensor or actuator,
being configured to perform or performing any of the described
activities as individual element or as part of an additional
element of the Controlled Agricultural System.
[2811] In some embodiments, the agricultural light fixture further
comprises a light control unit that connects to the interface
unit.
[2812] The light control unit may be configured to control the at
least one light module for operating in at least one of the
following operation modes: dimming, pulsed, PWM, boost, irradiation
patterns, including illuminating and non-illuminating periods,
light communication, synchronization with other elements of the
Controlled Agricultural System, such as a second agricultural light
fixture.
[2813] The interface unit of the agricultural light fixture may
comprise a gateway, such as a wireless gateway, that may connect to
the light control unit. It may comprise a beacon, such as a
Bluetooth.TM. beacon.
[2814] The interface unit may be configured to connect to other
elements of the Controlled Agricultural System, e.g. one or more
other agricultural light fixtures and/or to one or more sensors
and/or one or more actuators of the Controlled Agricultural
System.
[2815] The interface unit may be configured to be connect by any
wireless or wireline connectivity, including radio and/or optical
connectivity.
[2816] The agricultural light fixture may be configured for
adaptive form shaping and adjustment of the distance to the plants.
It may be modularly structured and configured for easy upgrades and
replacements of modules. In some embodiments, the agricultural
light fixture may be configured to enable customer-specific and/or
plant-specific light spectra. It may be configured to enable
customer-specific and/or plant-specific Photosynthetically Active
Radiation (PAR). The agricultural light fixture may be configured
to change the form and/or position and/or orientation of the at
least one light module. Further the agricultural light fixture may
be configured to change the light specifications of the light
emitted by the light source, such as direction of emission, angle
of emission, beam divergence, color, wavelength, and intensity as
well as other characteristics.
[2817] In some embodiments, the agricultural light fixture may
comprise a data processing unit. The data processing unit may
connect to the light driver and/or to the interface unit. It may be
configured for data processing, for data and/or signal conversion
and/or data storage. The data processing unit may advantageously be
provided for communication with local, network-based or web-based
platforms, data sources or providers, in order to transmit, store
or collect relevant information on the light module, the plants to
be grown, or other aspects connected with the agricultural light
fixture.
[2818] Agricultural Plant or Facility
[2819] The term Agricultural plant or facility shall comprise
greenhouses, vertical farms, urban farms, aquaponics farms,
aeroponic farms, indoor farms, small kitchen farming units, and the
like. An agricultural facility needs control of energy, material,
human workforce, harvesting machines, agribots (agricultural
robots), waste, ecological recycling devices, ventilation, heating
and cooling, humidifying, and the like. An agricultural facility
can track or calculate the total energy.
[2820] The term Agritecture describes concepts of buildings and
buildings that are suited for vertical farming or the coexistence
of humans and plants or animals in one building. Agritecture can
include aspects of energy efficiency, flow of goods and energy, use
of natural lighting, use of natural energy or heat sources, like
geothermic, wind, water as well as design of the building.
[2821] Agricultural System
[2822] An agricultural system is an assemblage of components, which
are united by some form of interaction and interdependence and
which operate within a prescribed boundary to achieve a specified
agricultural objective on behalf of the beneficiaries of the
system.
[2823] The agricultural system may be connected to numerous other
systems, including the provision and distribution of energy, the
marketing of agricultural goods, the provision of monetary and
financial services, and of central relevance to this report the
planning of land use.
[2824] An agricultural system can include agricultural light
fixtures, sensors, actuators, networks, power grid-systems, growth
control devices, harvesting and post-harvesting equipment, user
interface, crop-management, and may comprise an agricultural
management system.
[2825] Automated Guided Vehicle (AGV)
[2826] An automated guided vehicle or automatic guided vehicle
(AGV) is a robot that follows markers or wires in the floor, or
uses vision, magnets, or lasers for navigation. An AGV can be
equipped to operate autonomously.
[2827] Beacon
[2828] A Beacon is a device that emits signal data for
communication purposes, for example based on Bluetooth technology.
A Beacon can establish a Wireless Local Area Network.
[2829] Controlled Agricultural System
[2830] In a Controlled Agricultural System according to the present
disclosure, a computing device may be locally based, network based,
and/or cloud-based. That means, the computing may be performed in
the Controlled Agricultural System or on any directly or indirectly
connected entities. In the latter case, the Controlled Agricultural
System is provided with some connecting means, which allow
establishment of at least a data connection with such connected
entities. The data connection can be done wireless (e.g. WLAN or
Bluetooth) or wireline (e.g. LAN).
[2831] In some embodiments, the Controlled Agriculture System
comprises an Agriculture Management System connected to the at
least one hardware interface. The agriculture management system may
comprise one or more actuators for adjusting the growing conditions
for the plants. For instance, growing conditions may be
temperature, humidity, water, nutrients, lighting, air,
ventilation, pesticides.
[2832] The present disclosure further comprises an agriculture
management software. The present disclosure further comprises a
data storage device with the agriculture management software,
wherein the data storage device is enabled to run the agricultural
management software. The data storage device may either comprise be
a hard disk, a RAM, or other common data storage utilities such as
USB storage devices, CDs, DVDs and similar.
[2833] The Controlled Agricultural System, in particular the
agriculture management software, may be configured to control and
handle supply and demand, waste management, recycling, disinfection
and/or Automatically Guided Vehicles (AGV). That way, human
interaction with and contamination of the farms may be reduced.
[2834] The Controlled Agricultural System may be part of a Digital
Supply Chain and collect inputs from customers, partners or other
third persons as well as provide feedback to them.
[2835] In some embodiments, the computing device is configured to
perform the agriculture management software.
[2836] The agriculture management software may comprise any member
selected from the following group or a combination thereof:
software rules for adjusting light to outside conditions, adjusting
the light intensity of the at least one agricultural light fixture
to environmental conditions, adjusting the light spectrum of the at
least one agricultural light fixture to environmental conditions,
adjusting the light spectrum of the at least one agricultural light
fixture to supply-and-demand conditions, adjusting the light
spectrum of the at least one agricultural light fixture according
to customer specification.
[2837] The agriculture management software may furthermore comprise
similar rules to adjust other parameters of the agricultural plant,
like temperature, humidity, CO2.
[2838] The Controlled Agricultural System may further comprise a
feedback system connected to the at least one hardware interface.
The feedback system may comprise one or more sensors for monitoring
the state of plants for which the Controlled Agricultural System is
provided. The state of plants may for example, be assessed by at
least one of the following: plant growth, plant health sensing,
stress detection, plant color, plant morphology, plant leaf
density, plant nutrients, plant chemicals, plant enzymes.
[2839] The Controlled Agricultural System may further comprise a
feedback software.
[2840] The feedback software may in some embodiments comprise
algorithms for plant health assessment on the basis of the data of
the sensors.
[2841] The feedback software of the Controlled Agricultural System
may in some embodiments comprise algorithms for deriving growth
strategies and/or lighting strategies on the basis of the data of
the sensors.
[2842] The feedback software of the Controlled Agricultural System
may in some cases comprise light recipes for plants depending on
any member selected from the following group or a combination
thereof: plant physiology, plant health, growth stage, harvesting,
storage and delivery.
[2843] The feedback software may be configured to provide
instructions to the agriculture management software for adapting
the growing conditions of the plants autonomously.
[2844] The feedback software may comprise algorithms for
interpreting sensor data and suggesting corrective actions to the
agriculture management software.
[2845] In some embodiments of the Controlled Agricultural System,
the instructions to the agriculture management software are based
on measured values and/or data of any member selected from the
following group or a combination thereof: daylight,
Photosynthetically Active Radiation, temperature, CO.sub.2, plant
stress, nutrition supply, electricity prices and current demand for
the plants, leaf reflection, plant fluorescence or phosphorescence.
The Agricultural System therefore may have a data interface to
receive the measured values and/or data. The data interface may be
provided for wire-bound transmission or wireless transmission. In
particular, it is possible that the measured values or the data are
received from an intermediate storage, such as a cloud-based,
web-based, network-based or local type storage unit.
[2846] Further, the sensors for sensing environmental or plant
conditions may be connected with or interconnected by means of
cloud-based services, often also referred to as Internet of
Things.
[2847] In some embodiments, the Controlled Agricultural System
comprises a software user interface (UI), particularly a graphical
user interface (GUI). The software user interface may be provided
for the light control software and/or the agriculture management
software and/or the feedback software.
[2848] The software user interface (UI) may further comprise a data
communication and means for data communication for an output
device, such as an augmented and/or virtual reality display.
[2849] The user interface may be implemented as an application for
a mobile device, such as a smartphone, a tablet, a mobile computer
or similar devices.
[2850] The Controlled Agricultural System may further comprise an
application programming interface (API) for controlling the
Agriculture System by third parties and/or for third party data
integration, for example energy prices, weather data, GPS.
[2851] In some embodiments, the Controlled Agricultural System
comprises a software platform for providing at least one of grow
data, plant health assessment and growth strategies, light recipes,
time-to-harvest, residual Photosynthetically Active Radiation
demand, delivery date.
[2852] The software platform may cumulate data from growers to
train machine learning algorithms for improving light recipes and
growth strategies.
[2853] The Controlled Agricultural System may be connected to smart
grid power supply.
[2854] The Controlled Agricultural System may also comprise a
plurality of agricultural light fixtures arranged in adjustable
groups.
[2855] The Controlled Agricultural System may further comprise a
farm control unit. The farm control unit may be configured for
running a farming management system. It is configured to connect to
one or more agricultural light fixtures. It may connect to a data
bus. The data bus may be configured to connect to an interface unit
of an agricultural light fixture. As part of the agriculture
management system, the farm control unit may be configured for
controlling an operating state of the agricultural light
fixture.
[2856] The agriculture management system may comprise a light
control system which may comprise any of the following elements:
monitoring and/or controlling the status of the at least one
agricultural light fixture, monitoring and/or controlling the use
of the at least one agricultural light fixture, scheduling the
lighting of the at least one agricultural light fixture adjusting
the light spectrum of the at least one agricultural light fixture,
defining the light spectrum of the at least one agricultural light
fixture, monitoring and/or controlling the use of at least one
sensor of the at least one agricultural light fixture or Controlled
Agricultural System.
[2857] The present disclosure further refers to a building with at
least one Controlled Agricultural System. The building may be
planned and build particularly for integration of the Controlled
Agricultural System. However, it is also possible, that the
Controlled Agricultural System was integrated in a pre-existing
building. According to the present disclosure, both cases as well
as a combination of these cases shall be referred to.
[2858] Controlled-Environmental Agriculture
[2859] Controlled-environment agriculture (CEA) is a
technology-based approach toward food production. The aim of CEA is
to provide protection and maintain optimal growing conditions
throughout the development of the crop. Production takes place
within an enclosed growing structure of an agricultural plant (such
as a greenhouse, a vertical farm or an urban farm). Plants are
often grown using hydroponic methods in order to supply the proper
amounts of water and nutrients to the root zone. CEA optimizes the
use of resources such as water, energy, space, capital and labor.
CEA technologies include hydroponics, aeroponics, aquaculture, and
aquaponics.
[2860] Controllable variables can be temperature (air, nutrient
solution, root-zone, leaf), humidity (% RH), carbon dioxide
(CO.sub.2), light (intensity, spectrum, duration and intervals),
nutrient concentration (measured e.g. in ppm, EC (Electrical
Conductivity)), Nutrient pH (acidity), pests.
[2861] CEA facilities can range from fully 100% environmentally
controlled enclosed closed loop systems, to fully automated
glasshouses with computer controls for watering, lighting and
ventilation, to low-tech solutions such as cloches or plastic film
on field grown crops and plastic-covered tunnels.
[2862] CEA methods can be used to grow literally any crop, though
the reality is a crop has to be economically viable and this will
vary considerably due to local market pricing, and resource
costs.
[2863] Crops can be grown for food, pharmaceutical and
nutraceutical applications. It can also be used to grow algae for
food or for biofuels.
[2864] Daily Light Integral (DLI)
[2865] A daily light integral (DLI) describes the number of
photosynthetically active photons (individual particles of light in
the 400-700 nm range) that are delivered to a specific area over a
24-hour period.
[2866] Data Analytics
[2867] Quantitative and/or qualitative examination of data to
reveal information and insights contained therein. Data analytics
shall comprise hardware, software and methods to analyze data in
order to obtain information like, distance to an object, object
classification, object morphology. In agriculture, an object can be
a plant, animal, and so on, as described above. Data analytics can
be connected to a computerized control system. All data can be
encrypted. Data analytics and processing can use Blockchain methods
for data persistence and confidence.
[2868] Digital Plant Twin
[2869] A Digital Plant Twin is a digital representation of a plant.
The digital plant twin contains all relevant information to
describe the growth of the plant (e.g. size, color, morphology,
heat map). A digital plant twin may be used to compare the expected
growth of a plant at a certain stage (described by the digital
plant twin) with the actual growth of the plant as detected by
sensors.
[2870] Gateway
[2871] Gateway means a networking hardware equipped for interfacing
with another network. More specifically, a gateway is a node on a
network that serves as a `gate` or entrance/exit point to/from the
network. A gateway may contain devices such as protocol
translators, impedance matching devices, rate converters, fault
isolators, or signal translators as necessary to provide system
interoperability. It may also require the establishment of mutually
acceptable administrative procedures between both networks.
[2872] Graphical User Interface (GUI)
[2873] A Graphical User Interface (GUI) is a form of a user
interface that allows users to interact with electronic devices
through graphical icons and visual indicators such as secondary
notation, instead of text-based user interfaces, typed command
labels or text navigation. GUI can be used for light scheduling and
real-time control of a horticultural farm.
[2874] Growth Recipe
[2875] A growth recipe comprises growth parameters, i.e. control
parameters which control the growth of plants. These control
parameters can include illumination conditions (see light recipe),
but also parameters like temperature, humidity, nutrient, CO.sub.2,
etc.
[2876] Hydroponics
[2877] Hydroponics is a subset of hydroculture, which is a method
of growing plants without soil by using mineral nutrient solutions
in a water solvent. Terrestrial plants may be grown with only their
roots exposed to the mineral solution, or the roots may be
supported by an inert medium, such as perlite or gravel.
[2878] Leaf Area Index (LAI)
[2879] Researchers often represent the vertical foliage structure
using the leaf area density (LAD) in each horizontal layer, where
LAD is defined as the total one-sided leaf area per unit of layer
volume. The leaf area index (LAI), which is defined as the leaf
area per unit of ground area covered by the projected area of the
crown, is then calculated by vertically integrating the LAD profile
data. The LAI ranges from 0 (bare ground) to over 10 (dense conifer
forests).
[2880] Life Cycle Assessment (LCA)
[2881] Life Cycle Assessment (LCA) is the assessment of the
environmental impact of a given product or service throughout its
lifespan. The goal of LCA is to compare the environmental
performance of products and services. The term `life cycle` refers
to the notion that the raw material production, manufacture,
distribution, use and disposal (including all inputs and
intervening transportation steps) need to be assessed. This is then
the `life cycle` of the product. The concept can also be used to
optimize the environmental performance of a single product
(eco-design) or to optimize the environmental performance of a
company.
[2882] Light Detection and Ranging (LiDAR)
[2883] LiDAR is a method to measure distances and speed of objects
by means of electromagnetic radiation similar to radar but using
optical wavelengths (light). Usually, a pulsed laser illuminates a
scene (scanning or in a flash) and sensors (photodiodes, either
single ones or an array of photodiodes) measure the time-delay of
the reflected pulses thus being able to calculate the distance of
an object.
[2884] Light Recipe
[2885] Light recipes define lighting conditions, particularly for
the illumination of plants.
[2886] A light recipe can be stored as a data set or a program code
and executed by a computer-implemented software program, by a
user-defined or user-selected program code, or by a sensor trigger
signal.
[2887] A light recipe can contain information and/or executable
commands that control light wavelength, for example suited to
chlorophyll absorption curves, light intensity at specific
wavelengths or overall, including photon fluxes, physical light
properties such as polarization, collimation and coherence, ratios
of photon fluxes in certain wavelength ranges, for example the
ratio of blue to red radiation, or blue to far-red (730 nm), or
UV-B to red radiation, or green to red radiation, duration of
ON-times (illumination) and OFF-times (no illumination), radiation
of light for measurement purposes, like monochromatic laser
radiation for fluorescence measurement.
[2888] A light recipe can be adaptive, that is, it can be dependent
on external trigger signals and part of a regulative feedback
control loop.
[2889] A light recipe can contain information for activating and
controlling light operation modes such as dimming, pulsing,
pulse-width modulation, lighting patterns, boosting, for example in
the millisecond range, data generation for light-based
communication including synchronization with other light fixtures
or agricultural operation networks for energy, material, and waste
management, or with other agricultural farming places.
[2890] A light recipe can be used for plant treatment as well as
for disinfection purposes.
[2891] A light recipe can contain information about bug-repelling
light features as well as for bug-usable light features, like
certain wavelengths in the ultraviolet, or the amount of light
polarization, e.g. the amount of left- or right-handed circular
polarization, heat radiation and the like.
[2892] A light recipe can contain information about the amount of
photosynthetically active radiating (PAR) or flux density.
[2893] A light recipe can contain information or be selectable
based on information about the total energy consumption of the
activated or selected light recipe over the entire lighting
duration time, or an energy equivalent such as the production of
CO.sub.2, oxygen or methane gases.
[2894] A light recipe can contain information about the residual
energy or equivalent thereof, for example the amount of lighting
energy until harvesting time.
[2895] A light recipe can be selectable and allow producers or
customers to order a produce at any time and provide the necessary
residual or remaining lighting data.
[2896] A light recipe can be user defined, also interactively.
[2897] A light recipe can be certified, in particular light recipes
for medical plants.
[2898] A light recipe can be sold or licensed as intellectual
property.
[2899] Light recipes can define the amount of canopy and
interstitial lighting.
[2900] A light recipe can contain information about the location
and shape of a light fixture, and can trigger a command code in
order to move a fixture into a certain position or shape.
[2901] A light recipe can be stored in an accessible database
system.
[2902] Photon Flux
[2903] The Photon Flux of defines the available photons per second,
with no regard for wavelength. This flux is measured in micromoles
of photons per second with a broadband "quantum sensor", typically
a silicon photodiode with an optical filter.
[2904] Photosynthetically Active Photon Flux Density (PFD or
PPFD)
[2905] The Photosynthetically Active Photon Flux Density (PFD or
PPFD) means the photon flux density of photons in the PAR part of
the spectrum. Its unit is .mu.mol(Photons)/(m.sup.2s).
[2906] Photosynthetically Active Radiation (PAR)
[2907] A Photosynthetically Active Radiation (PAR) is driving
photosynthesis in higher plants, it describes a wavelength
range--i.e. 400-700 nm--but does not define whether an energy or
photon quantity is being used.
[2908] Phototropism
[2909] Phototropism is the ability of a plant, or other
photosynthesizing organism, to grow directionally in response to a
light source. Positive phototropism is the response of a plant
toward a light source, while negative phototropism (also called
"aphototropism") causes growth in the opposite direction. Plant
roots usually use negative phototropism.
[2910] Plant
[2911] The term plant shall include crops, grains, fruits, algae,
fungi, transgenic plants, flowering plants, prokaryotes, and any
other edible or useable produce as well as animals, including fish,
transgenic animals, and insects.
[2912] Sensors
[2913] Sensors are devices, modules or subsystems whose purpose it
is to detect events or changes in its environment and send the
information to other electronics, frequently a computer processor.
Nowadays, there is a broad range of sensors available for all kinds
of measurement purposes, for example the measurement of touch,
temperature, humidity, air pressure and flow, electromagnetic
radiation, toxic substances and the like.
[2914] Sensors can be used to measure resistive, capacitive,
inductive, magnetic, optical or chemical properties.
[2915] Sensors include camera sensors, for example CCD chips, Lidar
sensors for measurements in the infrared wavelength range, Radar
Sensors, and acoustic sensors for measurement in the infrasound,
audible and ultrasound frequency range. Ultrasound is radiation
with a frequency above 20 kHz.
[2916] Sensors can be infrared sensitive and measure for example
the presence and location of humans or animals.
[2917] Sensor can be grouped into a network of sensors.
[2918] Sensors can be connected directly or indirectly to data
storage, data processing and data communication devices.
[2919] Sensors can be used to measure the content or concentration
of plant enzymes, vitamins, flavonoids, but also for ingredients in
the soil or other growth media, the type and amount of fertilizes,
nutrients or toxic substances. In particular, sensors can measure
the temperature and gas concentrations in warehouses, e.g. for
apples and bananas.
[2920] Sensors in cameras can be connected to a CCTV (Closed
Circuit Television). Light sensors can measure the amount and
orientation of reflected light from the plants (leaf reflectivity
index).
[2921] Smart Grid
[2922] Smart Grid is an electrical grid that may include a variety
of operational and energy measures including smart meters, smart
appliances, renewable energy resources, and energy efficient
resources. The smart grid means an interconnection and control of
power suppliers, storage, electrical loads and network resources in
power transmission and distribution grids of the electricity
supply. This allows optimization and monitoring of the
interconnected components. An aim is to secure the energy supply
based on efficient and reliable system operation.
[2923] Vapor Pressure Deficit
[2924] Vapor-pressure deficit, or VPD, is the difference (deficit)
between the amount of moisture in the air and how much moisture the
air can hold when it is saturated. Once air becomes saturated,
water will condense out to form clouds, dew or films of water over
leaves. It is this last instance that makes VPD important for
greenhouse regulation. If a film of water forms on a plant leaf, it
becomes far more susceptible to rot. On the other hand, as the VPD
increases, the plant needs to draw more water from its roots. In
the case of cuttings, the plant may dry out and die. For this
reason the ideal range for VPD in a greenhouse is from 0.45 kPa to
1.25 kPa, ideally sitting at around 0.85 kPa.
[2925] Visible Light Communication
[2926] Visible light communication (VLC) is a data communications
variant, which uses visible light between 400 and 800 THz (780-375
nm). In a more general term, VLC or optical light communication can
comprise UV- or IR-wavelengths in addition to visible wavelengths.
The technology usually uses LEDs or OLEDs to transmit data, and
photodiodes or digital cameras to receive the data.
* * * * *
References