U.S. patent application number 16/659157 was filed with the patent office on 2020-05-21 for measurement of nitrate-nitrogen concentration in soil based on absorption spectroscopy.
The applicant listed for this patent is WinField Solutions, LLC. Invention is credited to Nicholas Carleton Koshnick, MICHAEL JOHN PREINER, John Paul Strachan, Justin Stewart White.
Application Number | 20200158630 16/659157 |
Document ID | / |
Family ID | 43050500 |
Filed Date | 2020-05-21 |
United States Patent
Application |
20200158630 |
Kind Code |
A1 |
PREINER; MICHAEL JOHN ; et
al. |
May 21, 2020 |
Measurement of Nitrate-Nitrogen Concentration in Soil based on
Absorption Spectroscopy
Abstract
The nitrate-nitrogen concentration in soil is estimated based on
the nitrate-nitrogen 200 nm absorption peak. In one embodiment, a
device measures the attenuation spectrum of a soil-extractant
mixture over a wavelength range that includes wavelengths in the
vicinity of the 200 nm absorption peak (the spectral operating
range) and then determines the nitrate-nitrogen concentration based
on the attenuation spectrum.
Inventors: |
PREINER; MICHAEL JOHN;
(Arden Hills, MN) ; Koshnick; Nicholas Carleton;
(Arden Hills, MN) ; White; Justin Stewart; (Arden
Hills, MN) ; Strachan; John Paul; (Arden Hills,
MN) |
|
Applicant: |
Name |
City |
State |
Country |
Type |
WinField Solutions, LLC |
Arden Hills |
MN |
US |
|
|
Family ID: |
43050500 |
Appl. No.: |
16/659157 |
Filed: |
October 21, 2019 |
Related U.S. Patent Documents
|
|
|
|
|
|
Application
Number |
Filing Date |
Patent Number |
|
|
15659068 |
Jul 25, 2017 |
10488331 |
|
|
16659157 |
|
|
|
|
15009542 |
Jan 28, 2016 |
9714901 |
|
|
15659068 |
|
|
|
|
13903841 |
May 28, 2013 |
9255878 |
|
|
15009542 |
|
|
|
|
12775762 |
May 7, 2010 |
8472023 |
|
|
13903841 |
|
|
|
|
61215696 |
May 7, 2009 |
|
|
|
Current U.S.
Class: |
1/1 |
Current CPC
Class: |
G01N 21/33 20130101;
G01N 21/00 20130101; G01N 2033/245 20130101; G01N 33/24 20130101;
G01N 21/276 20130101; G01N 21/552 20130101 |
International
Class: |
G01N 21/33 20060101
G01N021/33; G01N 21/00 20060101 G01N021/00; G01N 33/24 20060101
G01N033/24; G01N 21/27 20060101 G01N021/27 |
Claims
1-36. (canceled)
37. A device for measuring a nitrate-nitrogen concentration in soil
based on attenuation over a spectral operating range, the device
comprising: a light source that generates light that spans a
spectral operating range; a detector having a sensitivity that
spans the spectral operating range; a sample chamber configured to
contain a soil-extractant mixture, the light propagating from the
light source to the detector and attenuated by the soil-extractant
mixture in the sample chamber, the detector generating a soil
spectral signal that indicates the light received by the detector
at different wavelengths across the spectral operating range; a
processor that is coupled to the detector, and that estimates an
attenuation spectrum of the soil-extractant mixture over the
spectral operating range based on the soil spectral signal, wherein
the processor, when estimating the attenuation spectrum, removes
interference in the soil-extractant mixture using one of spectral
deconvolution and curve-fitting, and wherein the processor
estimates the nitrate-nitrogen concentration based on the
attenuation spectrum.
38. The device of claim 1, wherein the spectral operating range
includes wavelengths proximate a nitrate-nitrogen absorption
peak.
39. The device of claim 2, wherein the nitrate-nitrogen absorption
peak includes a peak wavelength and estimate attenuation values for
wavelengths greater than the peak wavelength.
40. The device of claim 2, wherein the peak wavelength is 200
nm.
41. The device of claim 4, wherein the 200 nm nitrate-nitrogen
absorption peak includes estimated attenuation values for
wavelengths greater than 200 nm.
42. The device of claim 4, wherein the processor: curve-fits the
attenuation spectrum based on the nitrate-nitrogen 200 nm
absorption peak; receives a soil type and estimates the
nitrate-nitrogen concentration further based on the soil type;
receives a soil conductivity and estimates the nitrate-nitrogen
concentration further based on the soil conductivity; applies a
partial least squares regression to the attenuation spectrum to
estimate the nitrate-nitrogen concentration; is trained based on a
set of absorption spectra and their corresponding nitrate-nitrogen
concentrations; estimates the nitrate-nitrogen concentration based
on its training; estimates the nitrate-nitrogen concentration as a
function of a measurement time; and extrapolates the estimates to a
final estimated nitrate-nitrogen concentration.
43. The device of claim 1, wherein the processor removes
interference in the soil-extractant mixture using at least one of
spectral deconvolution or curve-fitting when estimating the
attenuation spectrum.
44. The device of claim 1, wherein the processor estimates the
attenuation spectrum based on the soil spectral signal, a reference
spectral signal and a dark spectral signal; wherein the reference
spectral signal is generated when the sample chamber contains
extractant without soil; wherein the dark spectral signal is
generated without light from a light source incident on the
detector.
45. The device of claim 1, wherein, at different times, the sample
chamber contains the soil-extractant mixture or extractant without
soil; wherein the detector generates the soil spectral signal when
the sample chamber contains the soil-extractant mixture; wherein
the detector generates a reference spectral signal when the sample
chamber contains extractant without soil; wherein the processor
estimates the attenuation spectrum based on the soil spectral
signal and the reference spectral signal.
46. The device of claim 1, further comprising a second sample
chamber configured to contain extractant without soil; wherein the
processor estimates the attenuation spectrum based on the soil
spectral signal and a reference spectral signal; wherein the
reference spectral signal is generated from the second sample
chamber containing extractant without soil.
47. The device of claim 1, wherein further comprising a reference
optical path from the light source to the detector; wherein the
reference optical path is not attenuated by the soil-extractant
mixture; wherein the processor estimates the attenuation spectrum
based on the soil spectral signal and a reference spectral signal;
wherein the reference spectral signal is generated based on the
reference optical path.
48. The device of claim 1, wherein the light source includes two
bulbs, one of which has a relatively stronger UV spectrum than the
other, and which can be separately controlled.
49. The device of claim 1, further comprising a centrifuge for
separating the soil-extractant mixture, the light propagating
through the separated soil-extractant mixture.
50. A method for measuring a nitrate-nitrogen concentration in soil
based on attenuation over a spectral operating range, the method
comprising: generating light that spans a spectral operating range;
providing a soil-extractant mixture that attenuates the light;
detecting the attenuated light; generating a soil spectral signal
that indicates the light detected at different wavelengths across
the spectral operating range; estimating an attenuation spectrum of
the soil-extractant mixture over the spectral operating range based
on the soil spectral signal; estimating the nitrate-nitrogen
concentration based on the attenuation spectrum, wherein estimating
the attenuation spectrum includes removing interference in the
soil-extractant mixture using one of spectral deconvolution and
curve-fitting.
51. The method of claim 14, wherein estimating the attenuation
spectrum includes removing interference in the soil-extractant
mixture using at least one of spectral deconvolution and
curve-fitting.
52. The method of claim 14, further comprising estimating the
attenuation spectrum based on the soil spectral signal, a reference
spectral signal and a dark spectral signal; wherein the reference
spectral signal is generated when a sample chamber contains
extractant without soil and the dark spectral signal is generated
without light from a light source incident on a detector.
53. The method of claim 14, wherein: the spectral operating range
includes wavelengths at least as short as 230 nm; and the
nitrate-nitrogen concentration is estimated based on the
attenuation spectrum.
54. A device for measuring a nitrate-nitrogen concentration in soil
based on attenuation over a spectral operating range, the device
comprising: a light source that generates light that spans a
spectral operating range, the spectral operating range including
wavelengths proximate a 200 nm nitrate-nitrogen absorption peak; a
detector having a sensitivity that spans the spectral operating
range; a sample chamber configured to contain a soil-extractant
mixture, the light propagating from the light source to the
detector and attenuated by the soil-extractant mixture in the
sample chamber, the detector generating a soil spectral signal that
indicates the light received by the detector at different
wavelengths across the spectral operating range; a processor that
is coupled to the detector, and that estimates an attenuation
spectrum of the soil-extractant mixture over the spectral operating
range based on the soil spectral signal, wherein the processor,
when estimating the attenuation spectrum, removes interference in
the soil-extractant mixture; wherein the 200 nm nitrate-nitrogen
absorption peak includes estimated attenuation values for
wavelengths greater than 200 nm, and wherein the processor
estimates the nitrate-nitrogen concentration based on the
attenuation spectrum.
55. The device of claim 18, wherein the processor removes
interference in the soil-extractant mixture using spectral
deconvolution.
56. The device of claim 18, wherein the processor removes
interference in the soil-extractant mixture using curve-fitting.
Description
CROSS REFERENCE TO RELATED APPLICATIONS
[0001] This application is a continuation of pending U.S.
application Ser. No. 12/775,762, file May 7, 2010, which claims the
benefit of U.S. Provisional Application No. 61/215,696, filed May
7, 2009, both of which are incorporated by reference in their
entirety.
BACKGROUND
1. Field of Art
[0002] The present invention generally relates to measurement of
nitrate-nitrogen concentrations in soil.
2. Description of the Related Art
[0003] Nutrient levels in soil have significant spatial and
temporal variations. Accordingly, there has been significant effort
placed into development of local nutrient management schemes, often
referred to as "precision agriculture," addressing nutrient level
variation. Local nutrient management increases agricultural
efficiency while reducing its environmental impact by allowing
growers to locally apply nutrients where needed. Increases in
nutrient costs and a growing awareness of the environmental
consequences of current agriculture practices have made
improvements in agricultural efficiency and environmental impact
increasingly important.
[0004] Nitrate-nitrogen is one of most important nutrients for a
variety of crops, but it is particularly mobile in the soil, making
it subject to large spatial variations. The conventional approach
to nitrate-nitrogen measurement is based on laboratory-based soil
measurements. Soil samples are typically mailed to the labs, where
the samples are unpacked, sorted, dried, ground, and then measured.
This process is fairly expensive and can take up to two weeks
before results are available. This can be a significant
drawback.
[0005] As an example, in-season nitrogen management in corn-growing
regions is often difficult because of the slow turnaround time of
laboratory-based soil testing. Extending the time when corn growers
are able to measure soil nitrogen levels would allow corn growers
to test fields before their last application of fertilizer. This
would enable corn growers to test fields later in the growing
season and implement better nitrogen management practices. Further,
allowing growers to promptly retest fields, such as retesting after
a rain, would allow growers to adopt more efficient nitrogen
management practices. Additionally, laboratory-based soil
measurement costs scale directly with the number of samples, making
it prohibitively expensive to sample at high grid densities.
[0006] As a result, there has been interest in developing faster,
simpler and/or less expensive soil measurement techniques to expand
the benefits of precision agriculture. Technologies used have
ranged from mid-infrared (mid-IR) spectroscopy to ion-selective
electrodes. However, each of these methods has suffered from some
combination of expense, low accuracy, stringent calibration
requirements or difficulty of use.
[0007] One approach is based on canopy sensors and satellite
imagery that can measure NDVI (normalized difference vegetative
index), which is essentially a color measurement that can be used
to infer nitrogen needs. These methods are typically fast and
operate on a relatively low cost/acre. Unfortunately, there are
numerous interferences to NDVI measurements, as many factors can
affect crop color, such as water needs and disease. Thus, it
appears to suffer from low accuracy. Additionally, this method
requires a dense crop canopy to be useful, which puts a tight
operational limit on its use. It can only be used fairly late in
the season.
[0008] There have also been several recent efforts to perform fast
"on-the-go" measurements of soil nitrate-nitrogen using
ion-selective electrodes. However, the fragility of the
ion-selective membrane has caused significant problems with the
robustness and reproducibility of soil measurements. Ion-selective
systems also require frequent calibration, making them unappealing
for routine field use.
[0009] Nitrate "strip tests," commonly available from scientific
supply stores or from manufacturers, have also been used. However,
nitrate strip tests typically suffer from poor accuracy compared to
standard laboratory-based tests and require extensive sample
preparation, including consumable reagents. For example, the
standard preparation time for nitrate strip tests typically
approaches 30 minutes, includes numerous preparation steps and
requires precise timing of the reaction steps.
[0010] In another recent approach, optical absorption has been used
for in-situ monitoring of soil nitrate content. However, this
approach was based on a filtering method, in which an optical probe
was encapsulated inside a porous stainless steel casing. As a
result, the method suffered from very slow measurement times (in
the tens of hours). In addition, this approach was focused on
measuring the nitrate absorption peak at 300 nm. However, the peak
at 300 nm has a relatively weak absorption cross section, and so
presents difficulties when measuring nitrate concentration values
typically found in agricultural soils. For example, experimental
results based on the 300 nm peak typically do not demonstrate
sensitivity below 100 ppm nitrate-nitrogen concentration, whereas
agronomically relevant levels of soil nitrate-nitrogen
concentration are in the 0-50 ppm range.
[0011] Accordingly, a rapid and economical soil nitrate-nitrogen
measurement system could significantly increase the efficiency of
agricultural nitrate use.
SUMMARY
[0012] The present invention overcomes the limitations of the prior
art by estimating the nitrate-nitrogen concentration in soil based
on the nitrate-nitrogen 200 nm absorption peak. In one embodiment,
a device measures the attenuation spectrum (which could include
effects due to scattering in addition to absorption) of a
soil-extractant mixture over a wavelength range that includes
wavelengths in the vicinity of the 200 nm absorption peak and then
determines the nitrate-nitrogen concentration based on the
attenuation spectrum. The wavelength range will be referred to as
the spectral operating range.
[0013] In one implementation, such a device includes a light
source, a detector, a sample chamber and a processor. The light
source generates light that spans the spectral operating range,
including sufficient amounts of light in the vicinity of 200 nm
(but not necessarily including 200 nm). The sample chamber holds a
soil-extractant mixture (e.g., a water-soil mixture). The light
propagates from the light source, through the soil-extractant
mixture in the sample chamber, to the detector. Due to the high
absorption at 200 nm, the path length through the soil-extractant
mixture is short, for example 2 mm or less in many cases. The
detector (e.g., a spectrometer) generates a signal that indicates
the light received by the detector at different wavelengths across
the spectral operating range (the soil spectral signal). The
processor uses the soil spectral signal to calculate an attenuation
spectrum for the water-soil mixture, and then estimates the
nitrate-nitrogen concentration based on the attenuation spectrum.
Various approaches are based on analyzing the attenuation spectrum
in order to estimate the strength of the nitrate-nitrogen
absorption peak at 200 nm.
[0014] In one approach, the processor determines the attenuation
spectrum based on the soil spectral signal, a reference spectral
signal and a dark spectral signal. The reference spectral signal is
generated when the sample chamber contains just the extractant
without soil, and the dark spectral signal is generated without
light from the light source incident on the detector. These three
signals can be generated at different times and in different
manners. For example, some or all of the signals can be generated
at different times using the same equipment. The reference spectral
signal and dark spectral signal could be generated as part of a
calibration process. A separate reference chamber could be used to
generate the reference spectral signal in parallel with the soil
spectral signal. Other variations will be apparent.
[0015] The spectral operating range is selected to adequately
estimate the 200 nm absorption peak, which has a 20 nm full width
half max. It usually will also extend into longer wavelengths
(e.g., the visible, near IR and/or mid IR) in order to provide
enough data to sufficiently account for contributions from other
sources (e.g., nitrite-nitrogen, soil scattering, humic acids,
organic matter/carbon, inorganic salts, etc.). The light source is
selected to provide sufficient power at the wavelengths of
interest. The light source preferably has sufficient power at the
deep UV range (around 200 nm) relative to the longer wavelengths so
that the longer wavelengths do not dominate the detector
response.
[0016] Once the attenuation spectrum is calculated, the
nitrate-nitrogen concentration can be determined using a number of
different approaches. The attenuation spectrum around 200 nm
includes the nitrate-nitrogen peak but also includes contributions
from other sources. These other soil interferences are taken into
account when estimating the nitrate-nitrogen concentration. Some
approaches are based on physical models of the contributions from
different sources. For example, the measured attenuation spectrum
can be modeled as the sum of contributions from different sources,
where the spectral shape of each contribution is known or modeled.
Regression can be used to then determine the relative weights of
each contribution, which in turn can be used to estimate the
concentration of each source.
[0017] In another approach, the contributions from the other soil
interferences may be well known or separately determined. These can
then be subtracted from the attenuation spectrum, leaving an
estimate of the absorption peak at 200 nm. A Gaussian function can
be fitted to this residual peak to estimate the nitrate-nitrogen
concentration.
[0018] Other approaches are more empirical, for example based on
training using actual samples with known nitrate-nitrogen
concentrations. Partial least squares regression is one possible
empirical approach. Partial least squares regression is a
multivariate statistical analysis technique that can extract the
correlation of the nitrate-nitrogen absorption peak at 200 nm to
the nitrate-nitrogen concentration value independent of the
background interferences.
[0019] In some cases, the processor can also take advantage of time
dynamics to estimate concentrations before the soil-extractant
mixture actually reaches the steady state concentration. The
extraction of soil components has some time constant. It may take
some time before the soil-extractant mixture is homogenous with
respect to a particular soil component. The concentration can be
measured at different times during the extraction process. The data
points can then be extrapolated to yield the steady state
concentration before the soil-extractant mixture has reached that
steady state, thus saving time in the overall process.
[0020] The speed with which nitrate is released from soil depends
in part on the type of soil and how quickly the soil is broken up.
With a more vigorous mechanism for breaking up the soil,
nitrate-nitrogen concentration should be estimated in 60 seconds or
less, essentially real-time.
[0021] The approaches described above can also be combined with
other techniques. For example, filtering or centrifuging can be
used to process the soil sample. Information obtained from other
sources, such as soil type, moisture, conductivity, temperature,
ambient humidity and pH, can also be used in the estimate of the
nitrate-nitrogen concentration.
[0022] The features and advantages described in the specification
are not all inclusive and, in particular, many additional features
and advantages will be apparent to one of ordinary skill in the art
in view of the drawings, specification, and claims. Moreover, it
should be noted that the language used in the specification has
been principally selected for readability and instructional
purposes, and may not have been selected to delineate or
circumscribe the inventive subject matter.
BRIEF DESCRIPTION OF DRAWINGS
[0023] The disclosed embodiments have other advantages and features
which will be more readily apparent from the following detailed
description and the appended claims, when taken in conjunction with
the accompanying drawings, in which:
[0024] FIG. 1 is a block diagram of a soil analysis device
according to the invention.
[0025] FIG. 2 is a flow diagram illustrating operation of the
device in FIG. 1.
[0026] FIG. 3 is a diagram of another soil analysis device
according to the invention.
[0027] FIGS. 4A and 4B are graphs of an attenuation spectrum,
identifying contributions from different sources.
[0028] FIG. 5 is a graph illustrating curve fitting to an
attenuation spectrum.
[0029] FIG. 6 is a graph summarizing experiments testing the
accuracy of the invention.
[0030] FIG. 7 is a graph of nutrient concentration as a function of
time.
DETAILED DESCRIPTION
[0031] The figures and the following description relate to
preferred embodiments of the present invention by way of
illustration only. It should be noted that from the following
discussion, alternative embodiments of the structures and methods
disclosed herein will be readily recognized as viable alternatives
that may be employed without departing from the principles of the
claimed invention.
[0032] FIG. 1 is a block diagram of a soil analysis device
according to the invention. The device includes a light source 110,
a sample chamber 120, a detector 130 and a processor 140. The
sample chamber 120 is configured to contain a soil-extractant
mixture. It is optically positioned between the light source 110
and detector 130, so that light 150 from source 110 propagates
through the soil-extractant mixture and to the detector 130. The
processor 140 is coupled to the detector 130.
[0033] The device measures the nitrate-nitrogen concentration in
soil using the nitrate-nitrogen absorption peak at 200 nm. In this
example, the device does this by considering the attenuation
spectrum of a soil-extractant mixture across a broad wavelength
range (which will be referred to as the spectral operating range)
that includes wavelengths in the vicinity of the 200 nm absorption
peak.
[0034] FIG. 2 is a flow diagram illustrating the operation of this
device. A soil-extractant mixture is provided 210 in the sample
chamber 120. The light source 110 generates 220 light that spans
the spectral operating range and this light illuminates the sample
chamber 120. The light propagates 230 through the soil-extractant
mixture and is attenuated by different amounts at different
wavelengths. The exiting light is incident on the detector 130
(typically a spectrometer), which detects 240 the amount of light
at different wavelengths. The resulting signal generated 250 by the
detector 130 will be referred to as the soil spectral signal, to
indicate that it is a spectrum across many wavelengths that
accounts for attenuation by soil. The detector 130 is sensitive
across the spectral operating range. The processor 140 estimates
260 the attenuation spectrum of the soil-extractant mixture based
on the soil spectral signal. The attenuation spectrum is calculated
over the spectral operating range. The processor 140 then estimates
270 the nitrate-nitrogen concentration based on the attenuation
spectrum.
[0035] In more detail, the spectral operating range typically
includes both the deep UV and the visible. Since this device is
based on the absorption peak at 200 nm, the spectral operating
range includes wavelengths in the vicinity of this peak in order to
estimate the strength of the absorption. For example, the spectral
operating range could include (but is not limited to) at least 10
nm to either side of 200 nm (i.e., 190-210 nm or 20 nm full width
half max), preferably 20 nm (180-220 nm) or more preferably 30 nm
(170-230 nm). The spectral operating range is not required to
include 200 nm. The 200 nm absorption peak has a 20 nm width, so
wavelengths to either side of the peak can be sufficient to
estimate the peak. For example, the spectral operating range may
include wavelengths that are only to one side of the peak: 205 nm
and longer, 210 nm and longer, or 215 nm and longer. Even ranges as
far removed as 230 nm and longer can possibly yield good results
depending on the situation. Estimating the 200 nm absorption peak
typically determines the lower end of the spectral operating range.
More wavelength samples around this peak generally will lead to
better results. However, the absorption peak has a 20 nm full width
half max, so extending the spectral operating range down to 160-170
nm represents a range of 3-4 widths below the peak.
[0036] On the high end, the spectral operating range should be
sufficient to account for spectral contributions other than
nitrate-nitrogen absorption. Thus, the spectral operating range
typically extends into and possibly beyond the visible. Typical
spectral operating ranges may extend to somewhere in the 500-1100
nm range on the high end, although wavelengths outside this range
are also possible.
[0037] Given the low end and high end considerations, typical
spectral operating ranges include 150-500 nm, 150-850 nm, 150-1100
nm, 170-1100 nm, 180-1100 nm, 190-500 nm and 190-850 nm. The
spectral operating range does not have to be continuous over a
wavelength range. For example, if the light source 110 includes
multiple devices, the spectral operating range might be 180-220 and
400-800 nm. It might also include discrete sources, sources with
tunable emission wavelengths, or narrow wavelength lines.
[0038] FIG. 3 is a diagram of another soil analysis device
according to the invention. In FIG. 3, the light source, detector
and processor are not shown. The sample chamber 320 is defined by
two quartz optical windows, which transmit well at 200 nm. The
incoming light is delivered by fiber 312 and the exiting light is
collected by fiber 332. The soil-extractant mixture is created in
mixing chamber 370 which is connected to the sample chamber
320.
[0039] In one specific design, the light source is a Heraeus UV-Vis
FiberLight model DTM 6/50S. This light source has two separately
controllable bulbs. One bulb is stronger in the UV compared to the
other bulb. Separate controls allows the user or manufacturer to
adjust the UV content of the illuminating light relative to the
visible content. The optical fibers are standard silica fibers. The
detector is a Stellarnet EPP2000C spectrometer, with a wavelength
range of 190-850 nm. An alternate detector is the Ocean Optics
Maya2000Pro spectrometer, with a wavelength range from 175-1100 nm.
The spectrometer wavelength range is narrower than the light
source, so the spectrometer determines the spectral operating range
which is 190-850 nm or 175-1100 nm in these examples.
[0040] The extractant in this example is water. The water-soil
mixture is about 1-1.5% soil by weight, for example 5-7.5 g of soil
mixed with 460 mL of water. More soil can be used, so long as
enough light is transmitted to the detector. For example, higher
percentages (5%) of soil can be used with soils that are less
optically absorbing. Less soil can also be used, so long as the
nitrate-nitrogen signal is sufficiently strong. Other extractants
include, but are not limited to, potassium chloride; ammonium
fluoride and hydrochloric acid (Bray method); sodium bicarbonate
(Olsen method); or ammonium-nitrate, acedic acid, ammonium
fluoride, and EDTA (Mehlic method).
[0041] The soil is mixed with the water by a motorized stirrer.
Other mechanisms such as heating or ultrasound can also be used to
increase the speed of extraction of the relevant soil nutrients
into the water-soil mixture. Filtering, centrifuging, mechanical
separation or other approaches may be used to additionally prepare
the mixture. This particular design does not use filtering or
centifuging in order to avoid the added complexity and longer
processing time.
[0042] The water-soil mixture enters the sample chamber 320 and
attenuates the light passing through it. Due to the high
absorption, the path of the light through the water-soil mixture
preferably is short, typically 1 cm or less, generally less than 2
mm.
[0043] The spectrometer detects the remaining light after
attenuation by the water-soil mixture. This signal is referred to
as the soil spectral signal, I.sub.soil. This spectrometer samples
the spectral operating range at 1 nm wavelength increments, or
roughly 650 samples over the entire wavelength range. Other
wavelength sampling can be used. For example, the sampling may be
finer around the 200 nm absorption peak (or any other areas where a
narrower spectral feature is expected) and coarser in regions where
only broad spectral features are expected. The nitrate absorption
peak has a Gaussian width of .about.20 nm, which could be
reasonably sampled with 5 nm resolution in most cases.
[0044] The processor estimates the attenuation spectrum based on
the soil spectral signal I.sub.soil. In this design, it also uses
two additional signals: a reference spectral signal I.sub.ref and a
dark spectral signal I.sub.dark. The reference spectral signal
I.sub.ref is the response when the sample chamber is filled with
water but no soil. The dark spectral signal I.sub.dark is the
response when no light is incident on the detector. For example,
the light source can be turned off or blocked. The attenuation
spectrum is then calculated as
.alpha.(.lamda.)=-log.sub.10[{I.sub.soil(.lamda.)}-I.sub.dark(.lamda.)][-
I.sub.ref(.lamda.)-I.sub.dark(.lamda.)]} (1)
Note that this approach is normalized with respect to spectral
variations in source power.
[0045] The measurements I.sub.soil, I.sub.ref and I.sub.dark can be
taken at different times and in different ways with respect to each
other. For example, the measurements can be time multiplexed. At
one time, the light source is turned off or blocked for I.sub.dark.
At another time, the light source is turned on and the sample
chamber filled with water for I.sub.ref. At a third time, the
sample chamber is filled with the water-soil mixture for
I.sub.soil. The different measurements can be made with different
frequencies. For example, I.sub.ref and I.sub.dark do not have to
be measured for every sample measurement of I.sub.soil. In one
approach, I.sub.ref and I.sub.dark are measured periodically (e.g.,
once per hour, or once per day, or once per some calibration
period), or as part of a calibration procedure.
[0046] In an alternate approach, the measurements I.sub.soil,
I.sub.ref and I.sub.dark can be made in parallel using different
equipment or multiple optical beam paths. For example, a second
chamber can be filled with water. Both the sample chamber and the
second chamber (the reference chamber) can be probed at the same
time.
[0047] Furthermore, not all three measurements I.sub.soil,
I.sub.ref and I.sub.dark are always required. In some cases,
similar or substitute information may be obtained from other
sources. For example, if the spectrometer is well characterized and
stable, the dark count I.sub.dark may be reliably supplied by the
manufacturer or determined by some other procedure. As another
example, the attenuation spectrum may be estimated based on the
intensity of the light before entering the sample chamber and the
intensity of the light exiting the sample chamber. Alternately, the
reference measurement may be based on a path where the light
propagates through air (or through an empty sample chamber) but not
water. In some cases, it might be advantageous to have a
simultaneous reference measurement of the beam (dual beam system),
where the reference beam could pass either through water (without
soil) or through just air (no water or soil). Factors such as the
absorption of water may be accounted for by models or methods other
than direct measurement.
[0048] In one approach, the light can take two optical paths, one
through the water-soil mixture and another reference optical path
not through the water-soil mixture (e.g., through only air without
water or soil). The light could be switched between the two paths,
or it could be split into two beams, one for each path. The
air-only reference measurement I.sub.refair is compared to a
reference measurement through water no soil I.sub.refwater. The
relationship between the two is assumed to be fairly stable. In the
field, the device makes measurements on the water-soil mixture
I.sub.soil and the air-only reference measurement I.sub.refair.
I.sub.refwater can then be determined from Lean based on the
previously determined relationship between I.sub.refair and
I.sub.refwater.
[0049] From the attenuation spectrum .alpha.(.lamda.), the
processor estimates the nitrate-nitrogen concentration. The
concentration of nitrate-nitrogen (which has an absorption peak at
200 nm) could be estimated based solely on comparing the
attenuation spectrum at 200 nm against standards with known
nitrate-nitrogen concentrations. However, the measurement at 200 nm
is partly due to nitrate-nitrogen concentration and partly due to
other interferences in the water-soil mixture. Thus, the estimate
of nitrate-nitrogen concentration can be significantly improved by
accounting for these other interferences.
[0050] Three common sources of interference to the UV
nitrate-nitrogen measurement are scattering from soil particles,
humic acids and/or organic matter, and inorganic salts. FIG. 4A is
a graph of an attenuation spectrum, identifying contributions from
different sources. The curve 410 graphs the attenuation spectrum of
an unfiltered, vigorously stirred 50:1 water:soil mixture, taken
with a .about.1 mm path length cell. The soil has a nitrate
concentration (measured via cadmium reduction and a discrete
analyzer) of .about.8.5 ppm. The spectrum shows a clear nitrate
absorption peak near 200 nm, a weaker organic matter absorption
peak near 250 nm, and a broad background attenuation (.about.1 at
500 nm) due to scattering from soil particles.
[0051] FIG. 4B shows the attenuation spectra of two concentrated
solutions of dissolved salts, and illustrates how the spectral
shape of the salts is significantly different from that of
nitrate-nitrogen. Curve 420 is for 25 mMol KCl, and curve 430 is
for 40 mMol (NH.sub.4).sub.2SO.sub.4. As a note, the concentrations
used in the graph are much higher than would be found in a typical
soil. For example, typical soil levels of 0-1000 ppm K by weight
would correspond to 0-20 ppm K in a 50:1 water:soil solution, while
the inset shows K levels of .about.54,000 ppm by weight in
solution. It should also be noted that taking a reference
measurement of the water without soil can be used to remove effects
of interferences (ions, residual nitrate, etc.) from the water
supply, thus eliminating the need for distilled or purified
water.
[0052] Different approaches can be used to account for these
interferences. Some are based on physical models of the
contributions from different sources. Others are more empirical,
for example training based on actual samples with known
nitrate-nitrogen concentrations.
[0053] At the preferred water:soil ratios of 20:1 or less, the
scattering from soil particles is expected to present the largest
background signal. However, the spectral shape of this background
(which shows up as a broad absorption/extinction that steadily
increases at shorter wavelengths) is different from the absorption
of nitrate, which has a well-defined, Gaussian shape with a peak at
200 nm and a Gaussian width of 20 nm. As a result of this spectral
shape, spectral deconvolution and curve-fitting techniques may be
used to effectively remove this interference. Additionally, if
needed, flocculents or salts could be added to decrease the
turbidity of the water soil mixtures, although these materials
should be chosen so as not to absorb in the UV region of
interest.
[0054] Organic matter and humic acids are additional potential
sources of interference due to their absorption in the UV. This is
primarily due to conjugated carbon-carbon bonds which typically
absorb around 254 nm, although this can vary depending on the
particular molecular species present. Appropriate curve-fitting
algorithms may be used to remove the effect of these spectrally
distinct interferences. Additionally, soil organic matter in
agricultural soils is typically 1-10% as measured with the
loss-on-ignition technique, and only a small fraction of this is
reactive (conjugated) carbon, so the magnitude of these
interferences is expected to be relatively small.
[0055] Some inorganic salts (such as KCl, NaCl, etc) can also
absorb in the deep UV when dissolved in solution. However, as with
organic matter, the spectral shape of this absorption is typically
quite different from the absorption spectrum of nitrate-nitrogen,
typically consisting of a relatively sharp increase in absorption
with decreasing wavelength that extends to below 190 nm. See the
inset of FIG. 4, for example. This distinct shape allows removal of
this interference with appropriate curve-fitting algorithms.
[0056] In one approach, the attenuation spectrum is modeled as
consisting of the two nitrate-nitrogen absorption peaks (modeled as
Gaussian curves at 201 nm and 302 nm), and one or more Gaussian
curves to account for nitrite, organic/humic matter absorption, and
Rayleigh background attenuation. By performing this type of
analysis on a representative set of soils, the optimal fitting
parameters to remove background interferences can be determined. An
example of a possible fitting algorithm is shown below
Abs .varies. C Nitrate e - ( .lamda. - .lamda. Nitrate w Nitrate )
2 + C j e - ( .lamda. - .lamda. j w j ) 2 + ( B R - A R log .lamda.
) ( 2 ) ##EQU00001##
Where .lamda., is the wavelength, w.sub.j is the width of the
absorption peak for the species of interest, .lamda..sub.j is the
center of the absorption peak, the sum over the C.sub.j, terms are
for potential absorption interferences (such as nitrite, organic
matter, etc.), and the A.sub.R and B.sub.R account for Rayleigh
scattering.
[0057] FIG. 5 illustrates curve fitting based on three Gaussians:
one for the nitrate nitrogen absorption peak at 200 nm (Gaussian
1), one for Rayleigh scattering (Gaussian 2) and one for organic
carbon (Gaussian 3). The solid curve 510 shows the attenuation
spectrum.
[0058] Other types of physical models can also be used. For
example, it is possible to remove the soil interferences from UV
measurements on soil nitrate-nitrogen by fitting a broad background
on top of the narrow (.about.20 nm full width) absorption peak at
200 nm due to nitrate-nitrogen. Particular embodiments of the
background fitting functions could include a polynomial background,
one or more Gaussian backgrounds or an empirically derived
function. The narrow peak due to nitrate-nitrogen can be
characterized by first measuring pure nitrate-nitrogen in the
extractant and then using these measured absorption peaks and
widths as fitting constants when performing the measurement on
soil-extractant mixtures.
[0059] In a different approach, the estimate of nitrate-nitrogen
concentration can be determined empirically, for example based on a
learning algorithm or other adaptive or self-organizing algorithm.
A training set includes samples of attenuation spectra and their
corresponding nitrate-nitrogen concentrations. The training set
preferably covers the different variations expected in the field,
for example different soil types and background contributions. This
set is used to train the selected algorithm. A measured attenuation
spectrum is then input to the trained algorithm, which estimates
the nitrate-nitrogen concentration.
[0060] In one approach, partial least squares regression is used.
In preliminary experiments, partial least squares regression was
able to achieve +/-3.5 ppm accuracy. Note that an accuracy of 4 ppm
for the nitrate-nitrogen concentration in soil corresponds to an
accuracy of 0.2 ppm for the nitrate-nitrogen concentration in a
1:20 soil:water mixture. This would be acceptable for many types of
analysis. Other types of principle components analysis can also be
used.
[0061] Other sources of information can also be used. For example,
if the soil type is known (e.g., sandy, salty, clay), that can be
used as an input to estimate the nitrate-nitrogen concentration.
Other factors such as pH, conductivity, soil:water mixture
viscosity, soil moisture content, soil reflection spectrum, and
soil density can also be used as inputs to estimate the
nitrate-nitrogen concentration.
[0062] In some designs, in addition to estimating the
nitrate-nitrogen concentration, the processor also indicates the
confidence in the estimate. For example, if it is difficult to fit
a certain attenuation spectrum, the processor might provide an
estimate but also flag the sample as a bad fit. This might occur,
for example, if the attenuation spectrum included an unknown
interference. If necessary, these samples could then be discarded
or sent to a lab for analysis.
[0063] FIG. 6 is a graph summarizing experiments. This experiment
is based on ten soil samples, representing a variety of soil types
(sand, loam, clay, etc). Each dot represents one sample. For each
of these samples, the nitrate-nitrogen concentration was estimated
using the approach described above (based on attenuation spectrum
and the 200 nm absorption peak) and also using the standard
Cd-reduction technique. The dashed line would be perfect
correlation between the two techniques. The sample dots fall near
the dashed line. These results indicate the viability of quickly
and accurately predicting soil nitrate-nitrogen levels at
commercially relevant levels using the technique described
above.
[0064] In some cases, when mixing soil with an extractant, it can
take significant time for the nutrient or nutrients of interest to
dissolve in the extractant. FIG. 7 is a graph of nutrient
concentration (e.g., nitrate-nitrogen concentration) as a function
of time, illustrating the time extrapolation of final
concentrations of the nutrient. This can be used to improve the
measurement speed.
[0065] UV-visible spectroscopy equipment can give accurate signals
after measurement times much less than 1 second. The measurement of
interest is often the final value after all of the relevant
nutrients are part of the solution. The effective measurement time
can be decreased by using data points, measured as a function of
time, to predict the value at saturation before the measured values
become steady.
[0066] Referring to FIG. 7, the process begins with the mixing of
soil and extractant. The concentration of the nutrient of interest
(e.g., nitrate-nitrogen concentration) is calculated at different
times, thus yielding a plot of concentration vs time, as shown in
FIG. 7. The data points are curve fit to a functional form that
will predict the final answer (e.g., exponential or other
asymptotic function). The curve fit is updated as more data points
are collected. The error of the fit is also estimated. The soil
measuring cycle is terminated when the estimated error is less than
some threshold value, or after some set maximum measurement time
has been exceeded. Referring to FIG. 7, in cases where the
measurement system is much faster than the underlying extraction
process, the fitting function can estimate the final value well
before the extraction process actually reaches that value, thus
reducing the time required to estimate concentration.
[0067] The process of fitting the data points can be done in a
number ways. One approach involves least squares regression of the
data point to a physically or chemically motivated formula for the
time dependence. One such function is a constant minus an
exponentially decreasing function. Another function is a polynomial
as a function of time. Another function is some linear combination
of these functional forms with various fitting parameters. An
alternate approach for fitting the time dependence is the use of a
machine learning algorithm trained on a large set of appropriately
labeled data.
[0068] Parameters relating to the speed and shape of the time
dependence fitting can also be provided. Examples of relevant
parameters include measurements relating to the extractant/moisture
content of the soil (correlating to the amount of nutrients that
are already dissolved) and soil composition (percentage clay, silt,
sand, organic matter, etc.) which relates to the physical
extraction processes.
[0069] In various embodiments, the attenuation spectrum can be
obtained by techniques other than propagating the light directly
through the soil-extractant mixture. For example, evanescent-field
fiber absorption spectroscopy or attenuated total reflection (ATR)
are two alternate techniques to measure the attenuation
spectrum.
[0070] In other aspects, the estimates of nitrate-nitrogen
concentration are combined with other measurements. In one
embodiment, an optical detector measures scattered light. This
signal is used as an additional input to reduce the soil
interferences, since small particulates (such as those found in a
soil/extractant mixture) can strongly scatter light and thus
interfere with optical transmission measurements.
[0071] Another embodiment could contain optical reflectivity
measurements of the soil before extractant mixing in the UV,
visible, near IR, and/or mid IR spectra. The reflectivity of dry
soil as a function of wavelength is generally correlated to soil
type. Such information can be used, in conjunction with the other
embodiments discussed herein to provide data of interest to the end
user, and for additional tests.
[0072] Another embodiment includes the integration of additional
measurements such as soil moisture, soil conductivity, temperature,
ambient humidity, soil pH, soil/extractant solution viscosity, etc.
which are useful in their own right but can also be integrated with
the above measurements to increase accuracy. For example, by
measuring the moisture content of the soil, the nitrate-nitrogen
measurement can be made more accurate by subtracting the weight of
the water from the initial soil sample.
[0073] The approaches described above have many advantages. Certain
implementations have the potential to combine the accuracy of
lab-based soil sampling but at a significantly faster speed and
lower cost. By measuring nitrate-nitrogen directly in the soil, the
interferences that hinder indirect NDVI measurements are avoided.
In addition, by using the 200 nm absorption peak rather than the
300 nm absorption peak, lower concentrations of nitrate-nitrogen
can be measured. To be agronomically relevant, a nitrate-nitrogen
measurement system generally should be able to accurately measure
soil nitrate-nitrogen concentration in the range of 0-50 ppm.
Furthermore, the approach described above can be implemented in a
fast, portable instrument with no chemical reagents, thus offering
a more timely and cost-effective high density analysis compared to
soil chemistry labs. Field instruments can be used to essentially
sample nitrate-nitrogen concentration in real-time with high
density across a field.
[0074] This can allow growers to rapidly and economically measure
soil nitrate-nitrogen levels, thus enabling them to improve their
fertilizer management decisions. For example, split application of
nitrogen (through side-dressing) can greatly improve nitrogen use
efficiency. However, side-dressing is time sensitive, and
management decisions of how much nitrogen to apply are often
limited by the cost and slow turnaround of current soil testing
procedures. Fertilizer is a significant agricultural cost and the
inefficient use of fertilizer has large additional societal and
environmental costs. Nitrous oxide arising from nitrogen-based
fertilizer use is a significant cause of the driving force for
global warming, and nitrogen runoff from agriculture causes serious
water quality issues. Thus, improving fertilizer management will
have large economic and environmental benefits.
[0075] Upon reading this disclosure, those of skill in the art will
appreciate still additional alternative structural and functional
designs. Thus, while particular embodiments and applications have
been illustrated and described, it is to be understood that the
present invention is not limited to the precise construction and
components disclosed herein and that various modifications, changes
and variations which will be apparent to those skilled in the art
may be made in the arrangement, operation and details of the method
and apparatus of the present invention disclosed herein without
departing from the spirit and scope of the invention as defined in
the appended claims.
* * * * *