U.S. patent application number 14/226236 was filed with the patent office on 2014-07-24 for system, computer-implemented method, and non-transitory, computer-readable medium to determine relative market value of a sale group of livestock based on genetic merit and other non-genetic factors.
This patent application is currently assigned to Leachman Cattle of Colorado, LLC. The applicant listed for this patent is Leachman Cattle of Colorado, LLC. Invention is credited to Leland Leachman, Tim J. Watts.
Application Number | 20140207523 14/226236 |
Document ID | / |
Family ID | 49775254 |
Filed Date | 2014-07-24 |
United States Patent
Application |
20140207523 |
Kind Code |
A1 |
Leachman; Leland ; et
al. |
July 24, 2014 |
SYSTEM, COMPUTER-IMPLEMENTED METHOD, AND NON-TRANSITORY,
COMPUTER-READABLE MEDIUM TO DETERMINE RELATIVE MARKET VALUE OF A
SALE GROUP OF LIVESTOCK BASED ON GENETIC MERIT AND OTHER
NON-GENETIC FACTORS
Abstract
Systems, computer-readable medium having computer program, and
related computer implemented methods are provided to determine the
relative market value of a sale group and to generate a genetic
merit scorecard. Such systems, computer-readable medium having
computer program, and related computer implemented methods utilize
the genetic merit estimates of relatives of a sale group, along
with associated economic weighting factors to determine the
relative market value of the sale group. The genetic merit
scorecard reflects the relative market value and ranking of the
genetic merits of the sale group, as compared to the industry.
Inventors: |
Leachman; Leland;
(Wellington, CO) ; Watts; Tim J.; (Billings,
MT) |
|
Applicant: |
Name |
City |
State |
Country |
Type |
Leachman Cattle of Colorado, LLC |
Fort Collins |
CO |
US |
|
|
Assignee: |
Leachman Cattle of Colorado,
LLC
Fort Collins
CO
|
Family ID: |
49775254 |
Appl. No.: |
14/226236 |
Filed: |
March 26, 2014 |
Related U.S. Patent Documents
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Application
Number |
Filing Date |
Patent Number |
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14152845 |
Jan 10, 2014 |
8725557 |
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14226236 |
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14011304 |
Aug 27, 2013 |
8660888 |
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14152845 |
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14011304 |
Aug 27, 2013 |
8660888 |
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14011304 |
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61811720 |
Apr 13, 2013 |
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61822736 |
May 13, 2013 |
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61860686 |
Jul 31, 2013 |
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61811720 |
Apr 13, 2013 |
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61822736 |
May 13, 2013 |
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61860686 |
Jul 31, 2013 |
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61811720 |
Apr 13, 2013 |
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61822736 |
May 13, 2013 |
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61860686 |
Jul 31, 2013 |
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Current U.S.
Class: |
705/7.33 |
Current CPC
Class: |
G06Q 30/0204 20130101;
G06Q 40/04 20130101; G06Q 10/06 20130101; G06Q 50/02 20130101; G06Q
30/0206 20130101; G06Q 30/018 20130101 |
Class at
Publication: |
705/7.33 |
International
Class: |
G06Q 50/02 20060101
G06Q050/02; G06Q 30/02 20060101 G06Q030/02 |
Claims
1. An online genetic merit scorecard system, the system comprising:
one or more processors; an input/output unit adapted to be in
communication with the one or more processors; one or more genetic
merit databases in communication with the one or more processors to
store and associate a plurality of genetic merit estimates with a
plurality of economic weighting factors; one or more electronic
interfaces positioned to display an online genetic merit scorecard
and defining one or more genetic merit interfaces; and
non-transitory computer-readable medium positioned in communication
with the one or more processors and having one or more computer
programs stored thereon including a set of instructions that when
executed by one or more processors cause the one or more processors
to perform operations of: generating the genetic merit interface to
display to a user thereof one or more online genetic merit
scorecards, the genetic merit interface allowing an input of a
plurality of genetic merit estimates associated with a sale group;
determining, by one or more processors, relative market value of
the sale group responsive to receiving the plurality of genetic
merit estimates from the one or more genetic merit databases; and
outputting to the one or more genetic merit interfaces the online
genetic merit scorecard for the sale group responsive to
determining the relative market value, the online genetic merit
scorecard including the relative market value of the sale
group.
2. A genetic merit scorecard system as defined in claim 1, wherein
the online genetic merit scorecard further includes one or more of:
documentation of calf management practices associated with the sale
group positioned to be readily accessible to a user of the one or
more electronic interfaces, and source and age identification of
the sale group through an USDA approved process positioned to be
readily accessible to a user of the one or more electronic
interfaces.
3. A genetic merit scorecard system as defined in claim 1, wherein
the plurality of genetic merit estimates associated with the sale
group include genetic merit estimates of at least two of the
following: average daily gain, carcass weight, marbling, back fat
thickness, feed to gain ratio, ribeye area, yield grade,
tenderness, percentage of choice, pedigree, breed effects, feed
intake, animal health, weaning weight, post-weaning weight gain,
maintenance energy, maternal merit, birth weight, or residual fed
intake, residual average daily gain, or any ea or non-linear
combination of any two or more of these traits.
4. A genetic merit scorecard system as defined in claim 1, wherein
the plurality of genetic merit estimates associated with the sale
group comprises one or more of genetic merit estimates of feed
intake, weaning weight, post-weaning weight gain, carcass weight,
marbling, ribeye area, and back fat thickness.
5. A genetic merit scorecard system as defined in claim 1, wherein
the sale group includes cattle that are fed and harvested for beef
production.
6. A genetic merit scorecard system as defined in claim 1, wherein
the plurality of genetic merit estimates associated with the sale
group comprises one or more genetic merit estimates obtained from
the relatives of the sale group.
7. A genetic merit scorecard system as defined in claim 6, wherein
the relatives of the sale group comprise one or more sires of the
sale group.
8. A genetic merit scorecard system as defined in claim 6, wherein
the relatives of the sale group comprise one or more sires of the
sale group and one or more grandsires of the sale group.
9. An online genetic merit scorecard system, the system comprising:
one or more processors; an input/output unit adapted to be in
communication with the one or more processors; one or more genetic
merit databases in communication with the one or more processors to
store and associate a plurality of information regarding one or
more sale groups with a plurality of economic outcomes and a
plurality of economic weighting factors; and non-transitory
computer-readable medium positioned in communication with the one
or more processors and having one or more computer programs stored
thereon including a set of instructions that when executed by one
or more processors cause the one or more processors to perform
operations of: utilizing one or more electronic interfaces
positioned to display an online genetic merit scorecard and
defining one or more genetic merit interfaces, the genetic merit
interface allowing a use thereof to input a plurality of
information regarding the one or more sale groups; determining, by
one or more processors, a plurality of economic weighting factors
responsive to receiving the plurality of information from the
genetic merit interfaces and a plurality of economic outcomes from
the one or more genetic merit databases; determining, by one or
more processors, relative market value of the one or more sale
groups responsive to receiving the plurality of information and the
plurality of economic weighting factors from the one or more
genetic merit databases; and outputting to the one or more genetic
merit interfaces the online genetic merit scorecard for the one or
more sale groups responsive to determining the relative market
value, the online genetic merit scorecard including the relative
market value of the sale group.
10. A genetic merit scorecard system as defined in claim 9, wherein
the plurality of information regarding one or more sale groups
includes at least one of the following: genetic merit estimates
associated with the one or more sale groups, performance
information of the one or more sale groups, performance information
from one or more contemporary groups, performance information of
relatives of the one or more sale groups, environmental conditions,
management information, and nutritional information.
11. A genetic merit system as defined in claim 10, wherein the
genetic merit estimates associated with the one or more sale groups
include genetic merit estimates of at least two of the following:
average daily gain, carcass weight, marbling, back fat thickness,
feed to gain ratio, ribeye area, yield grade, tenderness,
percentage of choice, pedigree, breed effects, feed intake, animal
health, weaning weight, post-weaning weight gain, maintenance
energy, maternal merit, birth weight, or residual feed intake,
residual average daily gain, or any linear or non-linear
combination of any two or more of these traits.
12. A genetic merit scorecard system as defined in claim 10,
wherein the genetic merit estimates associated with the one or more
sale groups includes at least one of the following: genetic merit
estimates of the one or more sale groups, genetic merit estimates
of relatives of the one or more sale groups, and combinations
thereof.
13. A genetic merit scorecard system as defined in claim 12,
wherein the genetic merit estimates of the one or more sale groups
are obtained from at least one of the following: biometric
measurements, DNA analysis, expected progeny differences of the
sale group, and combinations thereof.
14. A genetic merit scorecard system as defined in claim 12,
wherein the genetic merit estimates of relatives of the one or more
sale groups are obtained from at least one of the following:
biometric measurements, analysis, expected progeny differences of
the relatives of the sale group, and combinations thereof.
15. A genetic merit scorecard system as defined in claim 9, wherein
the genetic merit scorecard further includes one or more of:
documentation of calf management practices associated with the sale
group, and source and age identification of the sale group through
an USDA approved process positioned to be readily accessible to a
user of the one or more electronic interfaces.
Description
RELATED APPLICATIONS
[0001] This application is a Continuation application of U.S.
Nonprovisional application Ser. No. 14/152,845 filed on Jan. 10,
2014, and is also a Continuation application of U.S. Nonprovisional
application Ser. No. 14/011,304 filed on Aug. 27, 2013, now U.S.
Pat. No. 8,660,888 issued on Feb. 25, 2014, and also claims
priority to U.S. Provisional Patent Application Ser. Nos.
61/811,720, filed on Apr. 13, 2013, 61/822,736, filed on May 13,
2013, and 61/860,686 filed on Jul. 31, 2013, all of which are
incorporated herein by reference in their entireties.
BACKGROUND
[0002] 1. Field of the Invention
[0003] Embodiments of the present invention relate generally to the
field of genetic quality and relative market value of livestock.
More specifically, embodiments of the present invention facilitate
an owner or potential buyer of one or more sale groups of livestock
to evaluate the relative market value of the sale groups based on
predictions derived from genetic merit estimates of the herd.
[0004] 2. Description of Related Art
[0005] Ranchers invest significant amounts of money to build a
quality herd with the desired genetic merits. Today, ranchers
typically invest more than $10,000 per animal in land, machinery,
and livestock costs, and then invest more money in high quality
bulls. But most ranchers are not able to realize the increased
value for the quality of their animals and instead sell their
annual calf crops on the commodity market at or near average price.
For example, a sale group of calves is valued on many attributes
depending on the ultimate purpose for the calves. The top
attributes for cattle that are sold to be developed for slaughter
(and not for breeding) are the tendency to stay healthy and the
genetic potential for growth, carcass merit, and feed efficiency.
Additionally, buyers of calves have considerable risk and
uncertainty. They prefer to buy superior calves, but have great
difficulty assessing the genetic merit and future healthiness of
the calves at the time of purchase. Therefore, it is very important
to determine what the value of the livestock is and what premium or
discount they should command based on these attributes.
[0006] Certain breeding associations like the American Angus
Association (AAA) generate genetic merit estimates that predict the
relative performance of offspring of registered animals on traits
that predict market value. AAA also generates several dollar
denominated indexes based on the expected progeny differences.
These expected progeny differences are usually available only for
registered seedstock. For example, one of the indexes from the AAA
is Beef Value ($9). This index specifically represents the expected
average dollar-per-head difference in the progeny post-weaning
performance and carcass value of a progeny of a particular
registered sire compared to progeny of other sires.
[0007] Recently, some companies offer genomic-enhanced Expected
Progeny Differences ("EPD"), where information from DNA sequences
is used to predict calf genetic merit. The AAA launched a project
with Zoetis to utilize DNA-based information to estimate the
marbling and gain characteristics of high percentage, unregistered
Angus cattle. For example, the GMX.TM. Score provides documentation
to prospective feedlot buyers to assess the relative genetic merit
of calves for both marbling and weight gain,
SUMMARY
[0008] The Applicants recognize the importance of determining
relative market value of a sale group or a group of animals offered
for sale from a livestock operation. Various embodiments of methods
and apparatus for determining relative market value of a sale group
are provided herein. Exemplary embodiments of the present invention
include an online genetic merit scorecard system. This system
includes one or more processors, an input/output unit adapted to be
in communication with the one or more processors, one or more
genetic merit databases in communication with the one or more
processors to store and associate a plurality of genetic merit
estimates with a plurality of economic weighting factors, one or
more electronic interfaces positioned to display an online genetic
merit scorecard and defining one or more genetic merit interfaces,
and non-transitory computer-readable medium. The non-transitory
computer-readable medium is positioned in communication with the
one or more processors and has one or more computer programs stored
thereon including a set of instructions. This set of instructions
when executed by one or more processors cause the one or more
processors to perform operations of generating the genetic merit
interface to display to a user thereof one or more online genetic
merit scorecards, determining relative market value and ranking of
the genetic merits of the sale group responsive to receiving the
plurality of genetic merit estimates from the one or more genetic
merit databases and outputting to the one or more electronic
interfaces the online genetic merit scorecard for the sale group
responsive to determining the relative market value and the ranking
of the genetic merits tier the sale group. In certain embodiments,
the set of instructions may further include determining relative
market value for the sale group by use of one or more multivariate
non-linear regression equations based on the plurality of genetic
merit estimates. The genetic merit interface allows an input of a
plurality of genetic merit estimates associated with a sale group.
The sale group includes cattle that are fed and harvested for beef
production. The online genetic merit scorecard includes the
relative market value and one or more rankings of genetic merits of
the sale group.
[0009] In some embodiments, the online genetic merit scorecard
system includes one or more processors, an input/output unit
adapted to be in communication with the one or more processors, one
or more genetic merit databases in communication with the one or
more processors to store and associate a plurality of genetic merit
estimates with a plurality of economic outcomes and a plurality of
economic weighting factors; and non-transitory computer-readable
medium. This non-transitory computer-readable medium is positioned
in communication with the one or more processors and having one or
more computer programs stored thereon including a set of
instructions. This set of instructions when executed by one or more
processors cause the one or more processors to perform operations
of utilizing one or more electronic interfaces positioned to
display an online genetic merit scorecard and defining one or more
genetic merit interfaces, then determining, by one or more
processors, a plurality of economic weighting factors responsive to
receiving the plurality of genetic merit estimates from the genetic
merit interfaces and economic outcomes from the one or more genetic
merit databases. The instructions further include determining, by
one or more processors, relative market value and ranking of the
genetic merits of the sale group responsive to receiving the
plurality of genetic merit estimates and the plurality of economic
weighting factors from the one or more genetic merit databases and
outputting to the one or more electronic interfaces the online
genetic merit scorecard for the sale group responsive to
determining the relative market value and the ranking of the
genetic merits for the sale group. The genetic merit interface
allows an input of a plurality of genetic merit estimates
associated with a sale group. The sale group includes cattle that
are fed and harvested for beef production. The online genetic merit
scorecard includes the relative market value and one or more
rankings of genetic merits of the sale group.
[0010] Exemplary embodiments of the invention include a
computer-implemented method to determine relative market value of a
sale group. The sale group includes cattle that are fed and
harvested for beef production. The method includes determining, by
one or more processors, a plurality of economic weighting factors
responsive to a plurality of genetic merit estimates associated
with the sale group and one or more economic outcomes, and then
determining, by one or more processors, relative market value and
ranking of the genetic merits of the sale group responsive to the
plurality of genetic merit estimates and a plurality of economic
weighting factors. The method includes outputting to one or more
electronic interfaces, positioned to display an online genetic
merit scorecard to thereby define one or more genetic merit
interfaces, the online genetic merit scorecard for the sale group
responsive to determining the relative market value and the ranking
of the genetic merits of the sale group. The online genetic merit
scorecard includes the relative market value and one or more
rankings of genetic merits of the sale group being displayed on the
one or more genetic merit interfaces.
[0011] In certain embodiments, the online genetic merit scorecard
may further include one or more of documentation of calf management
practices associated with the sale group positioned to be readily
accessible to a user of the one or more electronic interfaces. In
certain embodiments, the online genetic merit scorecard may further
include one or more of source and age identification of the sale
group through an USDA approved process positioned to be readily
accessible to a user of the one or more electronic interfaces.
[0012] In certain embodiments, the plurality of genetic merit
estimates associated with the sale group includes genetic merit
estimates of at least two of the following--average daily gain,
carcass weight, marbling, back fat thickness, feed to gain ratio,
ribeye area, yield grade, tenderness, percentage of choice,
pedigree, breed effects, feed intake, animal health, weaning
weight, post-weaning weight gain, maintenance energy, maternal
merit, birth weight, or residual feed intake, residual average
daily gain, or any linear or non-linear combination of any two or
more of these traits. In certain embodiments, the plurality of
genetic merit estimates associated with the sale group may be
limited to genetic merit estimates of at least two of the
following--feed intake, weaning weight, post-weaning weight gain,
carcass weight, marbling, ribeye area, and back fat thickness.
[0013] In certain embodiments, the plurality of genetic merit
estimates associated with the sale group includes one or more
genetic merit estimates Obtained from the relatives of the sale
group. In certain embodiments, the relatives of the sale group may
include one or more sires of the sale group. In some embodiments,
the relatives of the sale group may include one or more sires of
the sale group and one or more grandsires of the sale group.
[0014] Exemplary embodiments of the invention include a
computer-implemented method to determine a relative market value of
a sale group. An embodiment of this invention includes this
computer-implemented method determining the relative market value
and a ranking of the genetic merits of a sale group. This computer
implemented method has several steps. First, a genetic merit
interface is generated to display at one or more of the plurality
of remote computers. This genetic merit interface allows a user to
input a plurality of information associated with the sale group and
to transmit from a respective remote computer the plurality of
information associated with the sale group to a genetic merit
scorecard system. Then, a relative market value for the sale group
is determined in response to receiving the plurality of information
associated with the sale group at the respective remote computer. A
relative market value and ranking of the genetic merits of the sale
group may be determined in response to receiving the plurality of
information associated with the sale group at the respective remote
computer. A genetic merit scorecard is generated for the sale group
in response to determining the relative market value for the sale
group. A genetic merit scorecard may be generated for the sale
group in response to determining the relative market value and
ranking of the genetic merits of the sale group. The genetic merit
scorecard may include the relative market value for the sale group
and some of the plurality of information associated with the sale
group.
[0015] The plurality of information associated with the sale group
includes at least one of the following: genetic merit estimates
associated with the sale group, performance information of the sale
group, performance information from a contemporary group,
performance information of relatives of the sale group,
environmental conditions, management information, and nutritional
information.
[0016] In another embodiment, the genetic merit estimates
associated with the sale group includes at least one of the
following: genetic merit estimates of the sale group, genetic merit
estimates of relatives of the sale group, and combinations thereof.
In an embodiment, the genetic merit estimates of the sale group are
obtained from at least one of the following: biometric
measurements, DNA analysis, and Expected Progeny Differences of the
sale group, and combinations thereof. In an embodiment, the genetic
merit estimates of relatives of the sale group are obtained from at
least one of the following: biometric measurements, DNA analysis,
Expected Progeny Differences of the relatives of the sale group,
and combinations thereof.
[0017] In certain embodiments, the plurality of genetic merit
estimates associated with the sale group includes one or more
genetic merit estimates Obtained from the relatives of the sale
group. In certain embodiments, the relatives of the sale group may
include one or more sires of the sale group. In some embodiments,
the relatives of the sale group may include one or more sires of
the sale group and one or more grandsires of the sale group. In
another embodiment, the genetic merit estimates include genetic
merit estimates of at least two of the following: average daily
gain, carcass weight, marbling, back fat thickness, feed to gain
ratio, ribeye area, yield grade, tenderness, percentage of choice,
pedigree, breed effects, feed intake, animal health, weaning
weight, post-weaning weight gain, maintenance energy, maternal
merit, birth weight, or residual feed intake, residual average
daily gain, or any linear or non-linear combination of any two or
more of these traits.
[0018] In another embodiment, the plurality of genetic merit
estimates associated with the sale group includes genetic merit
estimates of feed intake, weaning weight, post-weaning weight gain,
carcass weight, marbling, ribeye area, and back fat thickness.
[0019] In an embodiment, the sale group may be composed of a
plurality of animals of a similar age. In an embodiment, the sale
group may be composed of a plurality of animals whose age and
source have been verified by a certification process. In an
embodiment of the invention, the genetic merit scorecard may
include documentation of calf management practices associated with
the sale group and source and age identification of the sale group
through an USDA approved process, in addition to the relative
market value and/or rankings of the genetic merits of the sale
group.
[0020] By way of example, an embodiment of the invention can
include a computer-implemented method to determine a relative
market value of a sale group. An embodiment of the present
invention can include a computer-implemented method to determine a
relative market value and ranking of genetic merits of a sale
group. In these embodiments, a genetic merit interface is generated
to display at one or more of the plurality of remote computers.
This genetic merit interface allows a user to input a plurality of
genetic merit estimates associated with the sale group and to
transmit from a respective remote computer the plurality of genetic
merit estimates to a genetic merit scorecard system. A relative
market value for the sale group is determined responsive to
receiving the plurality of genetic merit estimates at the
respective remote computer. A genetic merit scorecard is generated
for the sale group responsive to determining the relative market
value for the sale group. A genetic merit scorecard may be
generated for the sale group responsive to determining the relative
market value and the genetic merits of the sale group. The genetic
merit scorecard may include the relative market value for the sale
group and at least one genetic merit estimate from the plurality of
genetic merit estimates. In an embodiment, the genetic merit
scorecard may include ranking of the genetic merits of the sale
group. In another embodiment, the plurality of genetic merit
estimates associated with the sale group comprises genetic merit
estimates of feed intake, weaning weight, post-weaning weight gain,
carcass weight, marbling, ribeye area, and back fat thickness.
[0021] By way of example, an embodiment of the present invention
can include a genetic merit scorecard system. The genetic merit
scorecard system can comprise one or more processors: an
input/output unit connected to the one or more processors and a
non-transitory memory, the input/output unit adapted to be in
communication with a plurality of remote computers through a
communications network to receive a plurality of genetic merit
estimates associated with the sale group, from each of the
plurality of remote computers; one or more genetic merit databases
to associate the plurality of genetic merit estimates with a
plurality of economic weighting factors; and a non-transitory
computer-readable medium positioned in communication with the one
or more processors and having a computer program stored thereon
including a set of instructions. This set of instructions when
executed by one or more processors cause the one or more processors
to perform operations of: generating a genetic merit interface to
display at one or more of the plurality of remote computers, the
genetic merit interface allowing an input of a plurality of genetic
merit estimates associated with the sale group and to transmit from
a respective remote computer the plurality of genetic merit
estimates to a genetic merit scorecard system; determining a
relative market value for the sale group responsive to receiving
the plurality of genetic merit estimates at the respective remote
computer; and outputting a genetic merit scorecard for the sale
group responsive to determining the relative market value for the
sale group. The genetic merit scorecard includes the relative
market value for the sale group and at least one genetic merit
estimate from the plurality of genetic merit estimates. The genetic
merit scorecard includes the relative market value for the sale
group and at least one ranking of genetic merits of the sale
group.
[0022] In another embodiment, the genetic merit scorecard system
receives an input of the plurality of genetic merit estimates
associated with the sale group including genetic merit estimates of
feed intake, weaning weight, post-weaning weight gain, carcass
weight, marbling, ribeye area, and back fat thickness.
[0023] In another embodiment, the genetic merit scorecard system
has the computer program stored thereon that includes a further set
of instructions. This further set of instructions when executed by
one or more processors cause the one or more processors to further
perform operations of determining a relative market value for the
sale group responsive to receiving the plurality of genetic merit
estimates at a respective remote computer by using one or more
multivariate non-linear regression equations based on the plurality
of genetic merit estimates.
[0024] In another embodiment of the genetic merit scorecard system,
the genetic merit scorecard further includes a recommended feed
regimen for the sale group based on the plurality of genetic merit
estimates to optimize the realization of the maximum market
potential of the sale group.
[0025] In another embodiment of the genetic merit scorecard system,
the genetic merit scorecard system has the computer program stored
thereon that includes a further set of instructions. This further
set of instructions that when executed by one or more processors
cause the one or more processors to further perform operations of
transmitting the genetic merit scorecard for the sale group to an
auction computer. In this embodiment, the genetic merit scorecard
system further has one or more buyer computers, each buyer computer
being connected to a communication network and having a buyer
interface, the buyer interface allowing a buyer to view at least
the genetic merit scorecard and to submit bids on price of the sale
group; and one or more auction computers, each auction computer
being connected to a communication network and having one or more
processors performing further operations. These operations include
receiving the genetic merit scorecard for the sale group; receiving
all bids on price of the sale group from one or more buyer
computers; determining a highest bid for the sale group; and
facilitating a financial transaction for the buyer with the highest
bid to purchase the sale group.
[0026] In another embodiment of the genetic merit scorecard system,
the genetic merit scorecard system has the computer program stored
thereon that includes a further set of instructions. This further
set of instructions that when executed by one or more processors
cause the one or more processors to further perform operations of
transmitting the genetic merit scorecard for the sale group to a
broker database. In this embodiment, the genetic merit scorecard
system further has one or more buyer computers, each buyer computer
being connected to a communication network and a broker database,
and having a buyer interface, the buyer interface allowing a buyer
to input a plurality of purchasing requirements; one or more broker
databases to associate plurality of genetic scorecards for the sale
groups with purchasing requirements from the buyer computers; and
one or more broker computers, each broker computer being connected
to a communication network and a broker database, and having one or
more processors performing operations of receiving from the broker
database at least one of the following--the plurality of genetic
merit estimates associated with the sale group, the relative market
value of the sale group, and the genetic merit scorecard of the
sale group; receiving the plurality of purchasing requirements from
one or more buyer computers; identifying a sale group from the
broker database responsive to the purchasing requirements from a
particular buyer computer; and facilitating a financial transaction
for the particular buyer to purchase the identified sale group.
[0027] According to various embodiments of the present invention, a
non-transitory computer-readable medium has a computer program
stored therein including a set of instructions that when executed
by one or more processors cause the one or more processors to
perform operations of generating a genetic merit interface to
display at one or more of the plurality of remote computers, the
genetic merit interface allowing an input of a plurality of genetic
merit estimates associated with the sale group and to transmit from
the respective remote computer the plurality of genetic merit
estimates to a genetic merit scorecard system, determining a
relative market value for the sale group responsive to receiving
the plurality of genetic merit estimates at a respective remote
computer, and outputting a genetic merit scorecard for the sale
group responsive to determining the relative market value and
genetic merits for the sale group. The genetic merit scorecard
includes the relative market value for the sale group and at least
one genetic merit estimate from the plurality of genetic merit
estimates. The genetic merit scorecard includes the relative market
value for the sale group and at least one ranking of genetic merits
of the sale group.
[0028] An embodiment of the present invention includes a
computer-implemented method to determine a relative market value of
a sale group. The computer implemented method includes the steps of
generating a genetic merit interface to display at one or more of
the plurality of remote computers, the genetic merit interface
allowing an input of a plurality of information associated with the
sale group and to transmit from a respective remote computer the
information associated with the sale group to a genetic merit
scorecard system, calculating economic outcomes based on simulation
models responsive to receiving the information associated with the
sale group at the respective remote computer; analyzing the
economic outcomes to derive a plurality of economic weighting
factors; determining a relative market value for the sale group
responsive to the plurality of economic weighting factors and the
plurality of information associated with the sale group at the
respective remote computer; and outputting a genetic merit
scorecard for the sale group responsive to determining the relative
market value for the sale group. The genetic merit scorecard may
include the relative market value for the sale group and the
plurality of information associated with the sale group. The
genetic merit scorecard includes the relative market value for the
sale group and at least one ranking of genetic merits of the sale
group.
[0029] By way of example, an embodiment of the present invention
can include a genetic merit scorecard system to determine a
relative market value of a sale group. The genetic merit scorecard
system includes one or more processors; an input/output unit
connected to the one or more processors and a non-transitory
memory, the input/output unit adapted to be in communication with a
plurality of remote computers through a communications network to
receive a plurality of information associated with the sale group,
from each of the plurality of remote computers; one or more genetic
merit databases to associate the plurality of information
associated with the sale group with a plurality of economic
weighting factors; non-transitory computer-readable medium
positioned in communication with the one or more processors and
having a computer program stored thereon including a set of
instructions. This set of instructions when executed by one or more
processors cause the one or more processors to perform operations
of: generating a genetic merit interface to display at one or more
of the plurality of remote computers, the genetic merit interface
allowing an input of a plurality of information associated with the
sale group and to transmit from a respective remote computer the
information associated with the sale group to a genetic merit
scorecard system; calculating economic outcomes based on simulation
models responsive to receiving the information associated with the
sale group at the respective remote computer; analyzing the
economic outcomes to derive a plurality of economic weighting
factors; determining a relative market value for the sale group
responsive to the plurality of economic weighting factors and the
plurality of information associated with the sale group at the
respective remote computer; and outputting a genetic merit
scorecard for the sale group responsive to determining the relative
market value for the sale group. The genetic merit scorecard may
include the relative market value for the sale group and the
plurality of information associated with the sale group. The
genetic merit scorecard includes the relative market value for the
sale group and at least one ranking of genetic merits of the sale
group.
[0030] By way of example, an embodiment of the present invention
can include a non-transitory computer-readable medium having a
computer program stored therein including a set of instructions
that when executed by one or more processors cause the one or more
processors to perform operations of: generating a genetic merit
interface to display at one or more of the plurality of remote
computers, the genetic merit interface allowing an input of a
plurality of information associated with the sale group and to
transmit from a respective remote computer the information
associated with the sale group to a genetic merit scorecard system;
calculating economic outcomes based on simulation models responsive
to receiving the information associated with the sale group at the
respective remote computer; analyzing the economic outcomes to
derive a plurality of economic weighting factors; determining a
relative market value for the sale group responsive to the
plurality of economic weighting factors and the plurality of
information associated with the sale group at the respective remote
computer; and outputting a genetic merit scorecard for the sale
group responsive to determining the relative market value for the
sale group. The genetic merit scorecard may include the relative
market value for the sale group and the plurality of information
associated with the sale group. The genetic merit scorecard
includes the relative market value for the sale group and at least
one ranking of genetic merits of the sale group.
[0031] By way of example, an embodiment of the present invention
can include a computer-implemented method to determine a national
average market value of an animal or a plurality of animals, based
on genetic merits. A reported number of potential sires registered
by each breed by year of birth and average Expected Progeny
Differences for all potential sires of each such year are obtained
from a database. Then, the within breed Expected Progeny
Differences are adjusted using breed factors that account for
scaling and base differences between breeds. Economic weighting
factors based on simulation models are applied to the adjusted
Expected Progeny Differences. Values for non-reported breeds are
estimated based on information obtained from breeds with similar
biological characteristics. The national average market value is
determined by allocating proportional contribution of each breed as
a percentage of the total number of potential sires registered.
This national average market value is the base to which all
relative market values are compared.
BRIEF DESCRIPTION OF THE DRAWINGS
[0032] So that the manner in which the features and benefits of the
invention, as well as others which will become apparent, may be
understood in more detail, a more particular description of the
embodiments of the invention may be had by reference to the
embodiments thereof which are illustrated in the appended drawings,
which form a part of this specification. It is also to be noted,
however, that the drawings illustrate only various embodiments of
the invention and are therefore not to be considered limiting of
the invention's scope as it may include other effective embodiments
as well,
[0033] FIG. 1 is a schematic block diagram of an exemplary computer
implemented method to determine the relative market value of a sale
group.
[0034] FIG. 2 is a schematic block diagram of another exemplary
computer implemented method to determine the relative market value
of a sale group.
[0035] FIG. 3A is a schematic block diagram of another exemplary
computer implemented method to determine the relative market value
of a sale group.
[0036] FIG. 3B is a schematic block diagram of another exemplary
computer implemented method to determine the relative market value
of a sale group.
[0037] FIG. 3C is a schematic block diagram of another exemplary
computer implemented method to determine the relative market value
of a sale group.
[0038] FIG. 3D is a schematic block diagram of another exemplary
computer implemented method to determine the relative market value
of a sale group.
[0039] FIG. 3E is a schematic block diagram of another exemplary
computer implemented method to determine the relative market value
of a sale group.
[0040] FIG. 3F is a schematic block diagram of another exemplary
computer implemented method to determine the relative market value
of a sale group.
[0041] FIG. 4A is a block diagram that illustrates an exemplary
computer system in accordance with one or more embodiments of the
present invention.
[0042] FIG. 4B is a schematic block diagram of the operational flow
of computer-readable operations stored on a computer-readable
medium in the memory of a computer according to an exemplary
embodiment of the present invention,
[0043] FIG. 5 is a schematic diagram of a genetic merit interface
displayed at a remote computer, according to an exemplary
embodiment of the present invention.
[0044] FIG. 6 is a schematic diagram of a genetic merit interface
displayed at a remote computer, along with an image of the output,
according to an exemplary embodiment of the present invention.
[0045] FIG. 7A is a schematic diagram of a certificate with the
genetic merit scorecard, generated using a computer-implemented
method according to an exemplary embodiment of the present
invention.
[0046] FIG. 7B is a schematic diagram of a certificate with the
genetic merit scorecard, generated using a computer-implemented
method according to an exemplary embodiment of the present
invention.
[0047] FIG. 8 is a schematic block diagram of a system,
computer-implemented method, and non-transitory, computer-readable
medium to determine relative market value of a sale group,
according to an exemplary embodiment of the present invention.
[0048] FIG. 9 is a schematic block diagram of a system,
computer-implemented method, and non-transitory, computer-readable
medium configured to run on the interact to determine relative
market value of a sale group, according to an exemplary embodiment
of the present invention,
[0049] FIG. 10 is a schematic block diagram of a system,
computer-implemented method, and non-transitory, computer readable
medium configured to run on the internet to determine relative
market value of a sale group and utilize this as part of an auction
system, according to an exemplary embodiment of the present
invention.
[0050] FIG. 11 is a schematic block diagram of a system,
computer-implemented method and non-transitory, computer-readable
medium configured to run on the interact to determine relative
market value of a sale group and utilize the genetic merit
scorecard as part of a brokering system, according to an exemplary
embodiment of the present invention.
[0051] FIGS. 12A, 12B, 12C, and 12D are a series of flowcharts
depicting components of an exemplary computer program used in the
genetic merit scorecard system, according to an exemplary
embodiment of the present invention.
DETAILED DESCRIPTION
[0052] The present invention will now be described more fully
hereinafter with reference to the accompanying drawings, which
illustrate various embodiments of the invention. This invention,
however, may be embodied in many different forms and should not be
construed as limited to the embodiments set forth herein. Rather,
these embodiments are provided so that this disclosure will be
thorough and complete, and will fully convey the scope of the
invention to those skilled in the art. It is to be fully recognized
that the different teachings of the various embodiments discussed
below may be employed separately or in any suitable combination to
produce desired results. The various characteristics mentioned
above, as well as other features and characteristics described in
more detail below, will be readily apparent to those skilled in the
art upon reading the following detailed description of the various
embodiments, and by referring to the accompanying drawings. In the
drawings and description that follow, like parts are marked
throughout the specification and drawings with the same reference
numerals, respectively. The prime notation, if used, indicates
similar elements in alternative embodiments. The drawings are not
necessarily to scale. Certain features of the disclosure may be
shown exaggerated in scale or in somewhat schematic form and some
details of conventional elements may not be shown in the interest
of clarity and conciseness.
[0053] Exemplary embodiments of the present invention
advantageously provide, for example, systems, computer-readable
program products, and related computer-implemented methods to
determine a relative market value of a sale group. In a certain
embodiment, the sale group is a plurality of animals from a herd of
livestock.
[0054] As used herein, a herd can be any company of animals of one
species, including but not limited to, domestic animals, feeding or
traveling together, as the term is known and understood by those
skilled in the art. Such animals can include, for example, but are
not limited to, cattle and other bovines, sheep, goats, pigs and
other swine. A herd may be a group of all male animals, all
females, or all young animals, or any combinations thereof. A herd
refers to all of the animals on the livestock operation, and may
include a sale group, cows, bulls, calves, or any combinations
thereof.
[0055] As used herein, calves refer to the young of the animals,
including but not limited to, the young of domestic animals, for
example cattle and other bovines, sheep, goats, pigs and other
swine, as the term is known and understood by those skilled in the
art, in certain specific embodiments, a calf may refer to a young
bovine animal, less than one year of age.
[0056] As used herein, a sale group is an animal or a plurality of
animals for which a relative market value is determined. In certain
embodiments, the sale group is composed of young animals, usually
calves. The calves may be unregistered or registered calves. The
calves may be individually identified by electronic identification
(EID) or Radio-Frequency identification (RFID) tags or buttons.
Thus, the relative market value is determined as part of a process
verified individual calf identification program. In certain
embodiments, the sale group is composed of young animals, selected
by age and source. Source and age verification must be documented
and verified through a recognized United States Department of
Agriculture program. The genetic merit of a sale group cannot be
realized without proper health and management practices, including
age-appropriate vaccination and other treatment procedures. Without
proper documentation of health and other management practices,
buyers will discount the realizable value of the genetic merit of
the animals due to the risk of sickness and death. The most
valuable cattle are the ones with a strong nutritional foundation,
solid health history and the genetic background to perform both in
the yard and on the rail. In certain embodiments, the sale group is
part of a herd. A sale group may be a group of all male animals,
all female animals, or all young animals, or any combinations
thereof. In certain specific embodiments, a sale group may be a
group of male castrated bovines or steers. In other embodiments, a
sale group may be a group of calves, belonging to the same age
group. For example, a sale group may be a group of animals of
either sex but between 1 and 2 years of age, also known as
yearlings. In certain embodiments, a sale group may comprise a
single animal. In another embodiment, the sale group is composed of
unregistered calves.
[0057] In certain other embodiments, the relative market value is
determined for a sale group that contains only cattle. In another
embodiment, the relative market value is determined for a sale
group that has only cattle of a particular breed. In another
embodiment, the relative market value is determined for a sale
group that has cattle, fed and harvested exclusively for beef
production.
[0058] During beef production, sale groups are purchased and sold
at various stages of the production process. For example, a
cow-calf producer maintains a breeding herd of cattle that produce
calves. Then the calves may leave the ranch or farm of origin to be
in the backgrounder or stocker segment of production, where the
calves graze until they reach a particular age and weight range.
Some of these calves are sold or purchased for feedlot or feedyard
operations. Calves may proceed directly from the farm or ranch of
origin to a feedlot to be finished. In the feedlot stage of
production, these animals are fed with the intent of adding muscle
and fat appropriately until they reach market weight. This process
may be referred to as finishing or fattening. The cattle may be fed
a grain-based diet or allowed to feed on grass pastures. Once the
cattle reach the desired or market weight, they are sent to a
processing facility to be harvested. The relative market value of a
sale group may be determined at any stage of the beef production
process. In certain embodiments, the relative market value of a
sale group is determined prior to the feedlot stage of production.
In certain embodiments, the relative market value of a sale group
is determined for marketing to auction markets, to background
facilities, to finishing facilities, or to any other operator in
the beef production process. In certain embodiments, the relative
market value of a sale group is determined when the calves are sold
or purchased after the cow-calf stage of production. In other
embodiments, the relative market value of a sale group is
determined when cattle are sold or purchased after the backgrounder
or stocker segment of production.
[0059] Breed associations, like the AAA, offer predictions of the
genetic merit differences of offspring of one registered ancestor
versus offspring of another registered ancestor. AAA does not offer
predictions of genetic merit for groups of calves out of multiple
ancestors, nor do they offer predictions for animals out of
unregistered ancestors. The predictions offered by AAA and other
breed associations cannot be compared across databases or across
breeds. Thus, for example, a prediction on Angus cattle cannot be
directly compared to a prediction on Hereford cattle. No
association currently offers predictions that can incorporate
offspring of animals from multiple databases (i.e., from multiple
breeds with separate databases or even from different country
databases on the same breed).
[0060] As used herein, ancestors refer to the forebears of an
animal or a plurality of animals, as the term is known and
understood by those skilled in the art. Such animals can include,
for example, but are not limited to, dams, sires, granddams, and
grandsires. For example, the ancestors of a herd of calves include
the bull, the cow, and the parents of the bull and the cow. The
genetic merits of the ancestors are the inherited productivity or
performance qualities that are transmitted to the progeny.
[0061] The term "progeny" refers to any and all future generations
derived or descending from an animal. The term "grandprogeny"
refers to the second generation derived or descending from an
animal.
[0062] The term "relatives" refers to any and all lineal
descendants, collateral descendants, lineal ancestors, collateral
ancestors, siblings, half-siblings and other kin related by blood
to an animal or a plurality of animals. For example, the relatives
of a herd of calves may include the bulls, the cows, other
offspring of the bulls and the cows, and the parents and siblings
of the bulls and the cows. The genetic merits of the relatives are
the inherited productivity or performance qualities that are
transmitted to the progeny. These genetic merits are predicted from
all available observations on all relatives.
[0063] Genetic merit is the term used to describe the influence of
an animal's genetic makeup on the expression of that animal's
phenotype. Genetic merits depend on the animal's genetic makeup and
may include interactions with non-genetic factors. Genetic merits
can be determined by both biometric measurements, and genetic tests
that involve obtaining samples of DNA from an individual animal.
Genetic merits, for example, include, but are not limited to,
carcass merit, carcass weight, average daily gain, and teed
efficiency. These genetic merits drive feedlot and harvest
profitability. While assessing the relative market value of a young
animal or a sale group, one could utilize predictions of its
genetic merits derived from the relatives, or use these predictions
in combination with the measurements obtained from the animal or
the sale group, and the external factors in which the animals have
been raised. External factors that affect the expression of the
genetic merit of an animal as a phenotype include, for example,
production or growth environment conditions, management systems,
nutrition, or combinations of such factors. Certain genotypes may
enable an animal to display superior performance in certain
environmental conditions. Environmental factors like weather,
parasites and stress may affect the genetic merit and therefore,
its relative market value. Management strategies, like
transportation, production systems, time on feed and feed quality,
also affect cattle performance and therefore, its relative market
value. These environmental factors and management strategies as
applicable to the sale group, its relatives, and its contemporary
group are captured as inputs into the genetic merit scorecard
system. In certain embodiments of this invention, relative market
value is determined by analytical models that also account for
these external factors. Market value of an animal may also be
determined based on an estimate of the genetic value of an animal
as a parent. So the market value of such an animal would be the
mathematical analysis of the predictions regarding the
transmissibility of its genetic merits.
[0064] The term "genetic merit estimate" as used herein refers to
predictions and/or biometric measurements of genetic merits. Most
commonly, predictions about the genetic merits are used to
characterize the value of the ancestor as a breeding animal
relative to other breeding animals. Predictions of genetic merit
have never been used to predict the relative market value of
multi-breed feeder calves compared to a genetic merit based
national market value average. Embodiments of the present invention
utilize genetic merit estimates obtained from relatives of the sale
group and the sale group itself and include at least two of the
following: average daily gain, carcass weight, marbling, back fat
thickness, feed to gain ratio, ribeye area, yield grade,
tenderness, percentage of choice, pedigree, breed effects, feed
intake, animal health, weaning weight, post-weaning weight gain,
maintenance energy, maternal merit, birth weight, or residual teed
intake, residual average daily gain, or any linear or non-linear
combination of any two or more of these traits. The genetic merit
estimates may also factor in information from the plurality of
animals directly including phenotypes, parentage, and DNA
information including genomic predictions obtained from single
nucleotide polymorphism information or DNA sequence information.
The genetic merit estimates as utilized in this invention may be
derived from genetic tests, phenotypes, or EPD. Embodiments of the
invention may also utilize information from genetic tests performed
on the animal or its relatives or the sale group to measure the DNA
markers or other DNA sequence information.
[0065] In certain embodiments, the plurality of genetic merit
estimates associated with the sale group includes one or more
genetic merit estimates Obtained from the relatives of the sale
group. In certain embodiments, the relatives of the sale group may
include one or more sires of the sale group. In some embodiments,
the relatives of the sale group may include one or more sires of
the sale group and one or more grandsires of the sale group.
[0066] One of the most reliable determinants of the genetic merit
estimate is Expected Progeny Differences or EPD. They are valuable
predictions used for selecting breeding animals. EPD is the
prediction of how the progeny of an animal will perform relative to
the progeny of animals within the same dataset being analyzed. This
dataset may include a herd, an entire breed, or a plurality of
breeds, and may include animals of multiple breed compositions. For
example, the database contains phenotypic observations,
contemporary groupings, and sometimes DNA observations that are
then compared to a relationship matrix of all animals in the
database. The relationship matrix ties together all animals in the
database by showing their degree of relatedness on a scale of 0
(unrelated) to 1 (clone). EPD can be adjusted to reflect across
data set differences, including across breed differences. So when
two animals are compared using their EPD, the EPD indicate the
differences one can expect to see in the progeny. EPD are most
commonly expressed as units of measure for the genetic merit
estimates, positive or negative. Some EPD are expressed as
proportional values such as probabilities. Some EPD are expressed
as standardized values. Genetic merit estimates such as EPD for
birth weight, weaning weight, post-weaning weight gain are
expressed in pounds. EPD used in this invention are obtained from
several sources, including but not limited to, inventors'
proprietary databases (e.g., the Leachman database) and publicly
available databases like those maintained by breed associations.
EPD are subject to change as more records are added, because the
prediction of genetic merit changes depending on the available
information. More records are added as new measures are taken, new
animals are born, and new herds are added to the databases.
Accuracy is a measure of the reliability that can be placed on the
EPD. An accuracy of close to 1.0 indicates higher reliability for
that EPD, and is usually impacted by the number of data points that
are captured for the relatives.
[0067] EPD are unbiased predictions of genetic differences, but EPD
are not accurate. Accuracy is a measure of the reliability that can
be placed on the EPD. An accuracy of close to 1.0 indicates higher
reliability for that EPD, and is usually impacted by the number of
data points that are captured for the relatives of the animal.
Accuracy can also be affected by the technology and methods
involved in the production of the EPD. EPD that include
observations or biometric measurements and DNA markers can have a
higher accuracy value than EPD that are produced using only
pedigree estimates. The accuracy of the mean EPD of a group of
animals is typically much higher than the accuracy of the EPD for
individual animals. As an example, one might take individual
estimates of weights of a group of 250 animals. The accuracy (the
proximity of true value to the predicted or measured value)
associated with each estimate of individual weight is relatively
low. However, the accuracy of the estimated average weight of the
250 animals is much higher. In certain embodiments of the
invention, this statistical precept has been applied to the
averages of EPD. The accuracy of the average EPD of a group of
animals is much higher than the accuracy of the EPD of the
individual animals in the group. In certain embodiments of the
invention, relative market value and genetic merit estimates of a
sale group are not based on EPD and other predictive values for
individual animals. Instead, data from and predictions for groups
of animals are used. These resulting group predictions are far more
accurate than individual predictions that are readily available in
the industry.
[0068] Embodiments of the invention include utilizing mean EPD of
the genetic merits of a group of animals and their relatives,
instead of the EPD of individual animals or its ancestors. For
example, in operations that involve multi-sire breeding, or in
pastoral conditions where multi-sires are present, it is difficult
to assign paternity. Therefore, instead of utilizing tests to
determine the paternity of the sale group, it may be cost-effective
to use mean EPD of the relatives associated with the sale group.
Simulation models can associate the mean EPD values with economic
factors and thus the model can directly project the relative market
value of the sale group based on the mean EPD of the relatives. In
other embodiments of the invention, the mean EPD of all possible
parents of the sale group may be utilized to determine the relative
market value of the sale group. In certain embodiments, the mean
EPD of each genetic merit is utilized along with the variance of
the EPD for the sale group to determine the relative market value.
In certain embodiments of the invention, as one can predict the
variability of a group's genetic merit estimates, and therefore,
the variability of the relative market value of the sale group.
[0069] Current DNA-based calf valuation programs, such as that
offered by Zoetis and AAA, estimate the genetic merits of an
individual unregistered calf based directly on the calf's own DNA.
In most cases, the sire of the calf is not identified. The
predictions for DNA based differences are generally derived by
utilizing the matrix of EPD and relationships for all animals in
the database, which include the registered relatives of the calf.
The specific EPD of relatives of the calves are typically not
utilized in this calculation. Scores from these programs are not
tied to current market prices or any specific relative market
value. Further, these scores do not allow comparisons with animals
of other breeds, or from other databases, or with a national
average. Embodiments of the invention utilize EPD information on
sires and on other relatives (i.e., maternal grandsires) and may
include phenotype information on the animals themselves to
determine relative market values. Embodiments of the invention
allow for bundling the genetic prediction with a specific set of
age and source verified calves. Embodiments of the invention
predict dollar per pound predictions of the relative market value
for a group of animals or the sale group.
[0070] A few examples of the genetic merits and genetic merit
estimates are described below in greater detail. In certain
embodiments of the invention, one or more of these EPD are used as
genetic merit estimates in the computation models to derive a
relative market value. In other embodiments of the invention, one
or more of these EPD are used along with other real-time
measurements in the computation models to derive a relative market
value.
[0071] Embodiments of the present invention include utilizing
Average Daily Gain as a genetic merit estimate for calculating a
relative market value. For example, Average Daily Gain may be
derived from EPD on post-weaning weight gain. Average Daily Gain
EPD of an animal, expressed in pounds, predicts the difference in
post-weaning weight gain between the weight gains of the progeny of
such animal compared to the progeny of other animals. Analytical
models used in the present invention may take into account Average
Daily Gain EPD of the individual animal, or of the sale group, or
of the relatives of the animal or sale group, or of combinations
thereof.
[0072] Embodiments of the present invention include utilizing
Carcass Weight as a genetic merit estimate for calculating a
relative market value. Carcass Weight can be derived from Carcass
Weight EPD of an animal or from a formula driven by weaning weight,
post-weaning weight gain, ribeye area, marbling, back fat, and feed
intake. Carcass Weight EPD, expressed in pounds, predicts the
difference in carcass weight between the weights of the progeny of
such animal compared to the progeny of other animals.
[0073] Embodiments of the present invention include utilizing Feed
to Gain Ratio, Residual Average Daily Gain, Residual Feed Intake,
and/or Feed intake as genetic merit estimates for calculating a
relative market value. Each of these genetic merit estimates
predicts the amount of feed required by the animal to produce a
pound of live weight. In addition, exemplary embodiments of the
present invention utilize Feed Intake EPD to predict the amount of
feed required to attain the predicted carcass weight. Analytical
models used in the present invention may take into account Feed to
Gain Ratio EPD of the relatives, and/or Feed to Gain Ratio by the
individual animal or by the herd. Analytical models used in the
present invention may take into account Residual Average Daily Gain
EPD, Residual Feed Intake EPD, and Feed intake EN) of the
individual animals or the sale group, or the relatives, or any
combinations thereof.
[0074] Embodiments of the present invention include utilizing
Ribeye Area as a genetic merit estimate for calculating a relative
market value. Ribeye Area EPD predicts the difference in square
inches of the ribeye area of an animal's progeny compared to the
progeny of other animals. Ribeye Area factors into the carcass
yield grade equation that estimates the percentage of edible cuts
that can be obtained from the carcass. Larger Ribeye Area EPD also
predicts that the animal can be fed to a heavier carcass weight
before yield grade discounts are applied.
[0075] Embodiments of the present invention include utilizing Yield
Grade as a genetic merit estimate for calculating a relative market
value. Yield Grade EPD is a prediction of the relative red meat
yield of the carcass that is driven by carcass weight, fat, and
ribeye area. A Yield Grade EPD is calculated for percent of retail
product that can be produced by the progeny of the animal compared
to the progeny of other animals.
[0076] Embodiments of the present invention include utilizing
Marbling or intramuscular Fat (IMF) as a genetic merit estimate for
calculating a relative market value. Marbling EPD is expressed as a
difference in USDA marbling score or a difference in the percentage
of intramuscular fat. Marbling is a prediction of the USDA's score
of the amount of intramuscular fat in the ribeye muscle of an
animal's progeny compared to progeny of other animals. Higher
marbling animals command carcass premiums.
[0077] Embodiments of the present invention include utilizing
Percentage of Choice as a genetic merit estimate for calculating a
relative market value. Percentage of Choice EPD is a prediction of
the percentage of the carcass of an animal's progeny that will
grade in USDA's choice or better carcass category, when compared to
progeny of other animals. This genetic merit estimate may be driven
by the Marbling EPD.
[0078] Embodiments of the present invention include utilizing the
Weaning Weight as a genetic merit estimate for calculating a
relative market value. Weaning Weight EPD is expressed in pounds
and predicts the average differences in weight of an animal's
progeny compared to progeny of other animals for a standard weaning
age, usually at about 205 days. Analytical models used in the
present invention may take into account Weaning Weight of the
individual animal, or of the sale group, or of the relatives of the
animal or sale group, or of combinations thereof.
[0079] Embodiments of the present invention include utilizing
Animal Health as a genetic merit estimate for calculating a
relative market value. Animal Health EPD can be calculated based on
treatment and mortality rates in animals within a database.
Analytical models used in the present invention may include Animal
Health EPD of the individual animal, or of the sale group, or of
the relatives of the animal or sale group, or of combinations
thereof.
[0080] Embodiments of the present invention include utilizing
Tenderness as a genetic merit estimate for calculating a relative
market value. Tenderness EPD can be utilized to estimate carcass
value as more tender beef is more valuable. Analytical models used
in the present invention may include Tenderness EPD of the
individual animal, or of the sale group, or of the relatives of the
animal or sale group, or of combinations thereof.
[0081] Breeds consist of animals with a common origin and selection
history. Animals within a breed have physical characteristics that
distinguish them from other breeds or groups of animals within the
same species. Breed differences exist due in part to natural and
artificial selection pressures. A breed association is the
organization that typically maintains pedigree and performance
information and arranges for timely genetic evaluation of animals
within that breed. Breed associations also establish regulations
for registration of animals, promote the breed, and advance the
interests of its members. Breed Effects are adjustment factors that
allow comparison of EPD from differing breeds and/or different
breed databases. Breed Effects include base adjustment factors
which may be derived from proprietary databases (e.g., Leachman
database) or from publicly available databases. An example of a
publicly available database, are the across breed comparison charts
that are provided by the United States Department of Agriculture
(USDA) Agricultural Research Service (ARS). Certain embodiments of
the invention utilize Breed Effects that include the variance of
the EPD within a breed to rescale the EPD and aid in across breed
and/or across database comparisons. Embodiments of the present
invention include utilizing Breed Effects for standardizing genetic
merit estimates from multiple breeds. These standardized genetic
merit estimates are then used for calculating a relative market
value.
[0082] Producer's bull battery is the historical inventory of bulls
used in the herd. Embodiments of the present invention include
utilizing a ten year history of all the bulls used in the herd.
Bull identity is stored based on the bull's registration number and
breed. Corresponding estimates of genetic merit are stored on each
bull. This ancestral data is then used to estimate the relative
market value of the corresponding sale groups.
[0083] Cowherd size is the approximate number of breeding age
females kept in the herd. Embodiments of the present invention
utilize the cowherd size to assess the bull battery inventory. A
minimum percentage of bull battery inventory is required to produce
the relative market value estimate for a sale group.
[0084] Embodiments of the present invention include estimating the
genetic merit contribution of the dams of the sale group via
genetic merit estimates on the older portion of the bull battery.
In the event that females are purchased, the genetic merit of the
dams cannot be estimated in this fashion and are then assumed to be
either equal to industry average or to the breed average if breed
of the dams can be accurately ascertained. Other embodiments of the
present invention include utilizing genetic merit estimates for
dams from their herd of origin in the same way that genetic merits
are estimated for the sale groups.
[0085] Data about any measurement of the relatives' attributes or
EPD of relatives are most useful for evaluating younger animals
before performance and productivity measurements from the
individual animals or their progeny are obtained. Pedigree
information is also important for understanding genetic variability
and its role in determining genetic merit. In certain embodiments
of the invention, the EPD of relatives, for example that of the
sires and maternal grandsires, are the only genetic merit estimates
used in determining the relative market value of a sale group.
Simulation models can associate the EPD values with economic
factors and thus the model can directly project the relative market
value based on the EPD alone. The genetic merit estimates may
include the EPD of only one parent, for example the sire.
[0086] Genetic merits affect the expense in raising the sale group
and the income derived from it. A simulation model has been
developed that provides appropriate bio-economic weights to these
genetic merit estimates in estimating the relative value of the
sale group. The economic weighting factors thus derived are applied
to every EPD that a user inputs using the genetic merit scorecard
system. These economic weighting factors are derived utilizing
current assumptions for the changing real world prices for cattle
and feed, labor, interest, health costs, and other costs associated
with livestock health and environment.
[0087] In an embodiment of the genetic merit scorecard system, the
relative market value is determined using a plurality of
information associated with the sale group. The plurality of
information associated with the sale group include at least one of
the following: genetic merit estimates associated with the sale
group, performance information of the sale group, performance
information from a contemporary group, environmental conditions,
management information, and nutritional information. Performance
information associated with an animal or a plurality of animals
includes reproductive performance metrics, production performance
metrics, and economic performance metrics of the animal or the
plurality of animals, as the term is known and understood by those
skilled in the art. In certain embodiments, genetic merit estimates
associated with the sale group are mean EPD values for the
relatives of the sale group, instead of individual EPD values. In
certain embodiments of the invention, a herd average is used to
determine the relative market value for commercial customers'
calves. In another embodiment, the sale group may be composed of
animals registered with the breed association or of unregistered
progeny of these animals.
[0088] In certain embodiments, the relative market value is
determined based on the genetic merit estimates, for example feed
intake, feed to gain, residual feed intake, and residual average
daily gain, which are all proxies for this trait. Existing systems
value the output and make standard cost assumptions on the feed
intake. Embodiments of the invention take into account specific EPD
for intake on the relatives of the sale group. Thus, these
embodiments of the genetic merit scorecard system offer better
prediction of likely feeding costs, and a more accurate prediction
of relative market value for the sale group.
[0089] In another embodiment of the genetic merit scorecard system,
the system allows for a user to access the previously determined
relative market value of a sale group. This user can then input one
or more changes in the plurality of genetic merit estimates and
determine a revised relative market value for the sale group. This
revised relative market value is then reflected on a revised
genetic merit scorecard. A user could input other information
obtained from an animal or the sale group such as the associated
environmental conditions, performance information, management
information, nutritional information, or combinations thereof.
[0090] In another embodiment of the genetic merit scorecard system,
the system allows for a user to input information from a particular
buyer of the sale group. The information is associated to a
particular buyer and includes specific environmental conditions,
market conditions, management information, nutritional information,
or combinations thereof.
[0091] Various embodiments of the present invention advantageously
provide systems, machines, non-transitory computer medium having
computer program instructions stored thereon, and
computer-implemented methods for determining relative market value
of a sale group,
[0092] FIG. 1 is an illustration of an exemplary embodiment of the
computer-implemented methods of the invention. In one embodiment,
the method utilizes 11 a variety of genetic merit estimate inputs,
including but not limited to, EPD values for genetic merits from an
animal, a plurality of animals, or their relatives, and/or
performance information from an individual animal, or from its
contemporary group, or its relatives. The set of animals, whose
relative market value is determined, is referred to as the sale
group. The method may also utilize genetic merit estimates derived
from DNA analysis of the sale group or its relatives. DNA analysis
involves obtaining information from the genetic material from any
type of cell or tissue of an individual animal, or a sale group, or
of its contemporary group, or its relatives. Economic weighting
factors are calculated 12 using market values associated to each of
the above input factors. Market values can include historical sales
values, sales projection data, and real-time market values for
animals, carcasses, and operational expenses, like feed, labor,
interest, and health. Then utilizing all relevant genetic merit
estimates and associated economic weighting factors, analytical
models are assembled 13 to derive linear and/or non-linear
associations. The analytical model, for example, may include, but
is not limited to, a multivariate regression analysis that fits the
various genetic merit estimates in linear and non-linear forms
against the economic weighting factors derived from a simulation
model. Using these models, a relative market value is determined 14
for a sale group. In an embodiment, one can also generate 15 a
genetic merit scorecard for the sale group based on the relative
market value and the genetic merit estimates. Such a genetic merit
scorecard may contain a relative market value along with a star
ranking of the genetic merits of the sale group on a percentile
basis. An example of a genetic merit scorecard 65 is provided in
FIG. 6.
[0093] The relative market value may be expressed in various ways.
In one embodiment, the relative market value is a difference in
market value per head of a sale group compared to the market value
of a sale group that represents the average progeny of all
registered bulls in the country or market region. In another
embodiment, the relative market value is a difference in market
value per centum weight of the sale group compared to the market
value per centum of a sale group that represents the average
progeny of all registered bulls in the country or market region.
The national average is estimated by calculating the average EPD
for each breed by year. These EPD are then input into the linear
estimation models to estimate relative market values for progeny by
all registered bulls within each breed. Then the relative market
values are combined into a single national average based on each
breed's contribution to the total number of registered bulls in the
country.
[0094] FIG. 2 is an illustration of another exemplary embodiment of
the computer-implemented methods of the invention, in this
embodiment, inputs 21 of various genetic merit estimates are used,
including but not limited to, EPD values for genetic merits from an
animal, a plurality of animals, or their relatives, and/or
performance information from an individual animal, or from its
contemporary group, or its relatives. In an embodiment, the EPD
values used are mean EPD values for the sale group. The method may
also utilize genetic merit estimates derived from DNA analysis. DNA
analysis involves obtaining information from the genetic material
from any type of cell or tissue of an individual animal, or a sale
group, or of its contemporary group, or of its relatives. Economic
outcomes are calculated 22 based on simulation models that utilize
each of the above input factors. The simulation results are
analyzed using multivariate regression analysis to derive linear
and/or non-linear associations such as economic weighting factors
23. Relative market value for a sale group is determined 24. In an
embodiment, one can also generate 25 a genetic merit scorecard for
a sale group based on the relative market value and the genetic
merit estimates. Such a genetic merit scorecard may contain a
relative market value along with a star ranking of the genetic
merits of the animals on a percentile basis. An example of a
genetic merit scorecard 65 is provided in FIG. 6.
[0095] In certain embodiments, the current and historical data from
the genetic merit database provides a series of data points, each
of which is defined by one or more input variables, or genetic
merit estimates, and one or more outputs, such as economic values.
The inputs include genetic merit estimates of any of the following:
average daily gain, carcass weight, marbling, back fat thickness,
feed to gain ratio, ribeye area, yield grade, tenderness,
percentage of choice, pedigree, breed effects, feed intake, animal
health, weaning weight, post-weaning weight gain, maintenance
energy, maternal merit, birth weight, or residual feed intake,
residual average daily gain, or any linear or non-linear
combination of any two or more of these traits. In certain
embodiments, the independent variables may include a limited set of
genetic merit estimates of feed intake, weaning weight,
post-weaning weight gain, carcass weight, marbling, ribeye area,
and back fat thickness. A regression analysis is performed on the
data points to determine the relationship between the genetic merit
estimates and the economic values. The multiple regression analysis
produces an equation with a constant term .alpha., and a plurality
of subsequent terms. Except for the constant term, the nth term of
the equation may begin with a non-zero coefficient .beta. number
n-1 and may include either a single input variable of any degree or
the product of two or more input variables of any degrees.
[0096] The regression can be linear or non-linear. In an embodiment
of the invention, the regression is non-linear. This embodiment
allows the regression analysis to produce broader results because
the terms of the resulting equation to calculate the relative
market value will not be restricted to having a degree of one. The
broader range of possible results increases the likelihood that the
derived result will correlate closely to the data points from the
genetic merit database.
[0097] An example of a model developed using the
computer-implemented methods of an embodiment of this invention is
described below in the form of an equation:
Relative market value=.alpha.+(.beta.1.times.Weaning
EPD)+(.beta.2.times.Post-Weaning Gain
EPD)+(.beta.3.times.Post-Weaning Gain EPD
squared)+(.beta.4.times.Marbling EPD)+(.beta.5.times.Marbling EPD
squared)+(.beta.6.times.Ribeye Area EPD)+(.beta.7.times.Fat
EPD)+(.beta.8.times.Carcass Weight EPD)+(.beta.9.times.Feed Intake
EPD)+(.beta.10.times.Breed effect)
In this equation, .alpha. is the intercept while the .beta.s
represent economic weighting factors associated with each of the
specific EPD values.
TABLE-US-00001 TABLE 1 Relative Market Value Prediction per Head
Expected Genetic Merit Economic Progeny Estimate (EPD Weighting
Difference name) Factor Value Partial solution Intercept
-54.63230595 -54.63230595 Ribeye Area 18.83628065 0.225 4.238163145
Marbling 70.15643278 0.37 25.95788013 Fat -365.0592968 0.004
-1.460237187 Weaning weight 0.698390155 38.5 26.88802097
PostW_gain_epd 3.203660424 33.25 106.5217091 Breed adjustment 0 0 0
Carcass weight 0 0 0 PostW_gain_epd2 -0.033147268 1107.25
-36.70231265 Marbling2 -43.68630945 0.13775 -6.017789127 Relative
Market $64.79 Value per head
[0098] Table 1 is a non-limiting example of how the relative market
value of a sale group can be determined using the various genetic
merit estimates expressed as the EPD and their associated economic
weighting factors. In this example, the set of calves out of the
ancestor (whose genetic estimates are in column 3) would have a
relative market value of $64.79/head. If the calves weighed 500
lbs., the relative market value can be also expressed as $12.98 per
cwt (hundred weight) or $0.1298 per pound.
[0099] FIG. 3A is an illustration of another exemplary embodiment
of the computer-implemented methods of the invention. In this
embodiment, input 31 of a variety of genetic merit estimate inputs
are used, including but not limited to, EPD values for genetic
merits from an animal, a plurality of animals, or their relatives,
and/or performance information from an individual animal, or from
its contemporary group, or its relatives. The method may also
utilize genetic merit estimates derived from DNA analysis of the
sale group. If required, an across-breed adjustment is made 32. A
simulation model is used 33 that directly projects the value
differences based on the ancestral EPD. The relative market value
for the sale group is determined 34. In an embodiment, one can also
generate 35 a genetic merit scorecard based on the relative market
value and the genetic merit estimates. Such genetic merit scorecard
may contain a relative market value of the sale group along with a
star ranking of the genetic merits of the animals on a percentile
basis. An example of a genetic merit scorecard 65 is provided in
FIG. 6.
[0100] FIG. 3B is an illustration of another exemplary embodiment
of the computer-implemented methods of the invention and is
described below.
[0101] In this embodiment, a variety of genetic merit estimates 311
are inputted, including but not limited to, EPD values for genetic
merits from an animal, a plurality of animals, or their relatives,
and/or performance information from an individual animal, or from
its contemporary group, or its relatives. First, Breed EPI) on
sires and maternal grand sires 312 are converted into standard
deviation unit differences. Then. Breed standard deviation unit
differences 313 are adjusted to a standard, across breed basis
utilizing EPD adjustment factors from USDA-ARS, the Leachman
database, and/or other EPD databases.
[0102] A regression analysis is performed using the standard
deviation units for each trait to determine 314 the feeder calf
value. Note that in some cases, not all EPD are available on sires
and grandsires. In such cases, the coefficients for the input
variables change due to correlated responses between missing traits
and available traits. The feeder calf value is a value assigned to
ancestors (like sires and maternal grandsires), and is a projection
of the value of offspring of the animal. The feeder calf value for
a sire predicts the value of the sire's offspring. The feeder calf
value in standard deviation units 315 is then converted to dollar
units for each sire and maternal grandsire. Missing feeder calf
values for sires and grandsires are assigned to appropriate
population averages. The feeder calf value in dollars for sires,
including missing sires, is averaged 316. The feeder calf value for
maternal grandsires, including missing maternal grandsires, is
averaged 316. The relative market value of the sale group 317 is
calculated based on the feeder calf value of the sires and the
grandsires. In an embodiment, one can also generate 318 a genetic
merit scorecard based on the relative market value and the genetic
merit estimates. Such a genetic merit scorecard may contain a
relative market value of the sale group along with a star ranking
of the genetic merits of the animals on a percentile basis. An
example of a genetic merit scorecard 65 is provided in FIG. 6.
[0103] FIG. 3C is an illustration of another exemplary embodiment
of the computer implemented methods of the invention, and is
described below.
[0104] In this embodiment, a variety of genetic merit estimates 319
are inputted, including but not limited to, EPD values for genetic
merits from an animal, a plurality of animals, or their relatives,
and/or performance information from an individual animal, or from
its contemporary group, or its relatives. First, Breed EPD on sires
and maternal grandsires 320 are converted into standard deviation
unit differences. Then. Breed standard deviation unit differences
321 are adjusted to a standard, across breed basis utilizing EPD
adjustment factors from USDA-ARS, the Leachman database, and/or
other EPD databases. Utilizing 322 current and historical data from
the genetic merit database, a regression analysis is performed 323
using the standard deviation units for each trait to determine 324
the feeder calf value. Note that in some cases, not all EPD are
available on sires and grandsires. In such cases, the coefficients
for the input variables change due to correlated responses between
missing traits and available traits. The feeder calf value in
standard deviation units 325 is then converted to dollar units for
each sire and maternal grandsire. Missing feeder calf values for
sires and grandsires are assigned to appropriate population
averages. The feeder calf value in dollars for sires, including
missing sires, is averaged 326. The feeder calf value for maternal
grandsires, including missing maternal grandsires, is averaged 326.
The relative market value of the sale group 327 is calculated based
on the feeder calf value of the sires and the grandsires.
[0105] In a certain embodiment, relative market value of the sale
group is calculated using the following formula:
Relative market value of the sale group=(Feeder Calf
Value).sub.Sires+1/2(Feeder Calf Value).sub.Maternal
Grandsires.
[0106] In an embodiment, one can also generate 328 a genetic merit
scorecard based on the relative market value and the genetic merit
estimates. Such genetic merit scorecard may contain a relative
market value of the sale group along with a star ranking of the
genetic merits of the animals on a percentile basis. An example of
a genetic merit scorecard 65 is provided in FIG. 6.
[0107] FIG. 3D is an illustration of another exemplary embodiment
of the computer implemented methods of the invention, and is
described below.
[0108] In this embodiment, a variety of genetic merit estimates 329
are inputted, including but not limited to, EPD values for genetic
merits from an animal, a plurality of animals, or their relatives,
and/or performance information from an individual animal, or from
its contemporary group, or its relatives. First, Breed EPD on sires
and maternal grandsires 330 are converted into standard deviation
unit differences. Then. Breed standard deviation unit differences
331 are adjusted to a standard, across breed basis utilizing EPD
adjustment factors from USDA-ARS, the Leachman database, and/or
other EPD databases. In an embodiment, current and historical data
from the genetic merit database are used in a regression analysis
to determine 332 the feeder calf value.
[0109] The following equation is determined 332 and then applied to
standard deviation units for each trait:
Feeder Calf Value in standard deviation
units=.alpha.+(.beta.1.times.Weaning
EPD)+(.beta.2.times.Post-Weaning EPD)+(.beta.3.times.Carcass Weight
EPD)+(.beta.4.times.Marbling EPD)+(.beta.5.times.Ribeye Area
EPD)+(.beta.6.times.Fat EPD)+(.beta.7.times.Intake
EPD)+(.beta.8.times.Weaning Weight EPD
squared)+(.beta.9.times.Post-Weaning Gain EPD
squared)+(.beta.10.times.Carcass Weight EPD
squared)+(.beta.11.times.Marbling EPD
squared)+(.beta.12.times.Ribeye Area EPD
squared)+(.beta.13.times.Fat EPD squared)+(.beta.14.times.Feed
intake EPD squared)+(.beta.15.times.Weaning EPD.times.Post-Weaning
EP))+(.beta.16.times.Weaning EPD.times.Carcass Weight
EPD)+(.beta.17.times.Weaning EPD.times.Marbling
EPD)+(.beta.18.times.Weaning EPD.times.Ribeye Area
EPD)+(.beta.19.times.Weaning EPD.times.Fat
EPD)+(.beta.20.times.Weaning EPD.times.intake
EPD)+(.beta.21.times.Post-Weaning EPD.times.Carcass Weight
EPD)+(.beta.22.times.Post-Weaning EPD.times.Marbling
EPD)+(.beta.23.times.Post-Weaning EPD.times.Ribeye Area
EPD)+(.beta.24.times.Post-Weaning EPD.times.Fat
EPD)+(.beta.25.times.Post-Weaning EPD.times.intake
EPD)+(.beta.26.times.Ribeye Area EPD.times.Carcass Weight
EPD)+(.beta.27 Ribeye Area EPD.times.Marbling
EPD)+(.beta.28.times.Ribeye Area EPD.times.Fat
EPD)+(.beta.29.times.Ribeye Area EPD.times.Intake
EPD)+(.beta.30.times.Marbling EPD.times.Carcass Weight
EPD)+(.beta.31.times.Marbling EPD.times.Fat
EPD)+(.beta.32.times.Marbling EPD.times.intake EPD)+(.beta.33 Fat
EPD.times.Carcass Weight EPD)+(.beta.34.times.Fat EPD.times.Intake
EPD)+(.beta.35.times.Intake EPD.times.Carcass Weight
EPD)+(.beta.36.times.Carcass Weight EPD cubed)
TABLE-US-00002 Coefficients for Equation .alpha. (Intercept)
0.051200 .beta.1 sdWW -0.179 .beta.2 SdPWG 0.07603 .beta.3 SdCWT
0.9583 .beta.4 SdMarb 0.5673 .beta.5 SdREA 0.2191 .beta.6 SdBF
1.535 .beta.7 SdInt -0.1618 .beta.8 SDWW2 -0.0183 .beta.9 SDPWG2
0.175 .beta.10 SDCWT2 0.05376 .beta.11 SDIMF2 0.002981 .beta.12
SDREA2 0.004488 .beta.13 SDBF2 0.2591 .beta.14 SDINT2 0.002199
.beta.15 WWxPWG 0.04432 .beta.16 WAxCWT -0.0183 .beta.17 WWxMarb
-0.02093 .beta.18 WWxREA -0.03006 .beta.19 WWxBF -0.006867 .beta.20
WWxInt 0.02907 .beta.21 PWGxCWT -0.2192 .beta.22 PWGxMarb -0.0904
.beta.23 PWGxREA -0.05858 .beta.24 PWGxBF -0.3929 .beta.25 PWGxInt
0.04765 .beta.26 REAxCWT 0.04621 .beta.27 REAxIMF 0.02275 .beta.28
REAxBF 0.08042 .beta.29 REAxInt -0.006367 .beta.30 MarbxCWT 0.04614
.beta.31 MarbxBF 0.09427 .beta.32 MarbxInt -0.002338 .beta.33
BFxCWT 0.2655 .beta.34 BFxInt -0.06213 .beta.35 IntxCWT -0.02418
.beta.36 SdCWT3 -0.003442
[0110] Note that in some cases, not all EPD are available on sires
and grandsires. In such cases, the coefficients for the input
variables change due to correlated responses between missing traits
and available traits. The feeder calf value in standard deviation
units 333 is then converted to dollar units for each sire and
maternal grandsire. Missing feeder calf values for sires and
grandsires are assigned to appropriate population averages. The
feeder calf value in dollars for sires, including missing sires, is
averaged 334. The feeder calf value for maternal grandsires,
including missing maternal grandsires, is averaged 334. The
relative market value of the sale group 335 is calculated based on
the feeder calf value of the sires and the grandsires.
[0111] In a certain embodiment, relative market value of the sale
group is calculated using the following formula:
Relative market value of the sale group=(Feeder Calf
Value).sub.Sires+1/2(Feeder Calf Value).sub.Maternal
Grandsires).
[0112] In certain embodiment, one can also generate 336 a genetic
merit scorecard based on the relative market value and the genetic
merit estimates. Such a genetic merit scorecard may contain a
relative market value of the sale group along with a star ranking
of the genetic merits of the animals on a percentile basis. An
example of a genetic merit scorecard 65 is provided in FIG. 6.
[0113] FIG. 3E is an illustration of another exemplary embodiment
of the computer-implemented methods of the invention, and is
described below.
[0114] In this embodiment, a variety of genetic merit estimates 337
are inputted, including but not limited to, EPD values for genetic
merits from an animal, a plurality of animals, or their relatives,
and/or performance information from an individual animal, or from
its contemporary group, or its relatives. Breed EPD on sires and
maternal grandsires 338 are adjusted for differences in variances
and scaling. EPD adjustment factors from USDA-ARS, the Leachman
database, and/or other EPD databases may be utilized.
[0115] A regression analysis is performed to determine 339 the
feeder calf value. Note that in some cases, not all EPD are
available on sires and grandsires. In such cases, the coefficients
for the input variables change due to correlated responses between
missing traits and available traits. Missing feeder calf values for
sires and grandsires are assigned to appropriate population
averages. The feeder calf value in dollars for sires, including
missing sires, is averaged 340. The feeder calf value for maternal
grandsires, including missing maternal grandsires, is averaged 340.
The relative market value of the sale group 341 is calculated based
on the feeder calf value of the sires and the grandsires. In an
embodiment, one can also generate 342 a genetic merit scorecard
based on the relative market value and the genetic merit estimates.
Such a genetic merit scorecard may contain a relative market value
of the sale group along with a star ranking of the genetic merits
of the animals on a percentile basis. An example of a genetic merit
scorecard 65 is provided in FIG. 6.
[0116] FIG. 3F is an illustration of another exemplary embodiment
of the computer-implemented methods of the invention, and is
described below.
[0117] In this embodiment, a variety of genetic merit estimates 343
are inputted, including but not limited to, EPD values for genetic
merits from an animal, a plurality of animals, or their relatives,
and/or performance information from an individual animal, or from
its contemporary group, or its relatives. Breed EPD on sires and
maternal grandsires 344 are adjusted for differences in variances
and scaling. EPD adjustment factors from USDA-ARS, the Leachman
database, and/or other EPD databases may be utilized.
[0118] A regression analysis is performed to determine 345 the
feeder calf value. The following equation is determined 345:
Relative market value=.alpha.+(.beta.1.times.Weaning
EPD)+(.beta.2.times.Post-Weaning EPD)+(.beta.3.times.Carcass Weight
EPD)+(.beta.4*Marbling EPD)+(.beta.5.times.Ribeye Area
EPD)+(.beta.6.times.Fat EPD)+(.beta.7.times.Intake
EPD)+(.beta.8.times.Weaning Weight EPD
squared)+(.beta.9.times.Post-Weaning Gain EPD
squared)+(.beta.10.times.Carcass Weight EPD
squared)+(.beta.11.times.Marbling EPD
squared)+(.beta.12.times.Ribeye Area EPD
squared)+(.beta.13.times.Fat EPD squared)+(.beta.14.times.Feed
intake EPD squared)+(.beta.15.times.Weaning EPD.times.Post-Weaning
EPD)+(.beta.16.times.Weaning EPD.times.Carcass Weight
EPD)+(.beta.17.times.Weaning EPD.times.Marbling
EPD)+(.beta.18.times.Weaning EPD.times.Ribeye Area
EPD)+(.beta.19.times.Weaning EPD.times.Fat
EPD)+(.beta.20.times.Weaning EPD.times.intake
EPD)+(.beta.21.times.Post-Weaning EPD.times.Carcass Weight
EPD)+(.beta.22.times.Post-Weaning EPD.times.Marbling
EPD)+(.beta.23.times.Post-Weaning EPD.times.Ribeye Area
EPD)+(.beta.24.times.Post-Weaning EPD.times.Fat
EPD)+(.beta.25.times.Post-Weaning EPD.times.Intake
EPD)+(.beta.26.times.Ribeye Area EPD.times.Carcass Weight
EPD)+(.beta.27 Ribeye Area EPD.times.Marbling
EPD)+(.beta.28.times.Ribeye Area EPD.times.Fat
EPD)+(.beta.29.times.Ribeye Area EPD.times.Intake
EPD)+(.beta.30.times.Marbling EPD.times.Carcass Weight
EPD)+(.beta.31.times.Marbling EPD.times.Fat
EPD)+(.beta.32.times.Marbling EPD.times.Intake EPD)+(.beta.33 Fat
EPD.times.Carcass Weight EPD)+(.beta.34.times.Fat EPD.times.Intake
EPD)+(.beta.35.times.Intake EPD.times.Carcass Weight
EPD)+(.beta.36.times.Carcass Weight EPD cubed)
TABLE-US-00003 Coefficients for Equation .alpha. (Intercept)
0.051200 .beta.1 sdWW -0.179 .beta.2 SdPWG 0.07603 .beta.3 SdCWT
0.9583 .beta.4 SdMarb 0.5673 .beta.5 SdREA 0.2191 .beta.6 SdBF
1.535 .beta.7 SdInt -0.1618 .beta.8 SDWW2 -0.0183 .beta.9 SDPWG2
0.175 .beta.10 SDCWT2 0.05376 .beta.11 SDIMF2 0.002981 .beta.12
SDREA2 0.004488 .beta.13 SDBF2 0.2591 .beta.14 SDINT2 0.002199
.beta.15 WWxPWG 0.04432 .beta.16 WAxCWT -0.0183 .beta.17 WWxMarb
-0.02093 .beta.18 WWxREA -0.03006 .beta.19 WWxBF -0.006867 .beta.20
WWxInt 0.02907 .beta.21 PWGxCWT -0.2192 .beta.22 PWGxMarb -0.0904
.beta.23 PWGxREA -0.05858 .beta.24 PWGxBF -0.3929 .beta.25 PWGxInt
0.04765 .beta.26 REAxCWT 0.04621 .beta.27 REAxIMF 0.02275 .beta.28
REAxBF 0.08042 .beta.29 REAxInt -0.006367 .beta.30 MarbxCWT 0.04614
.beta.31 MarbxBF 0.09427 .beta.32 MarbxInt -0.002338 .beta.33
BFxCWT 0.2655 .beta.34 BFxInt -0.06213 .beta.35 IntxCWT -0.02418
.beta.36 SdCWT3 -0.003442
[0119] Note that in some cases, not all EPD are available on sires
and grandsires. In such cases, the coefficients for the input
variables change due to correlated responses between missing traits
and available traits. Missing feeder calf values for sires and
grandsires are assigned to appropriate population averages. The
feeder calf value in dollars for sires, including missing sires, is
averaged 346. The feeder calf value for maternal grandsires,
including missing maternal grandsires, is averaged 346. The
relative market value of the sale group 347 is calculated based on
the feeder calf value of the sires and the grandsires. In a certain
embodiment, relative market value of the Feeder Calf sale group is
calculated using the following formula:
Relative market value of the Feeder Calf sale group=(Feeder Calf
Value).sub.Sires+1/2(Feeder Ca Value).sub.Maternal Grandsires
[0120] In an embodiment, one can also generate 348 a genetic merit
scorecard based on the relative market value and the genetic merit
estimates. Such a genetic merit scorecard may contain a relative
market value of the sale group along with a star ranking of the
genetic merits of the animals on a percentile basis. An example of
a genetic merit scorecard 65 is provided in FIG. 6.
[0121] By way of example, an embodiment of the present invention
can include a computer-implemented method to determine a national
average market value of an animal or a plurality of animals, based
on genetic merits. A reported number of potential sires registered
by each breed by year of birth and average EPD for all potential
sires of each such year are obtained from a database. Then, the
within breed EPD are adjusted using breed factors that account for
scaling and base differences between breeds. Economic weighting
factors based on simulation models are applied to the adjusted EPD.
Values for non-reported breeds are estimated based on information
obtained from breeds with similar biological characteristics. The
national average market value is determined by allocating
proportional contribution of each breed as a percentage of the
total number of potential sires registered. This national average
market value is the base to which all relative market values are
compared.
[0122] Furthermore, the systems, computer-readable program product,
and related computer-implemented methods to generate a genetic
merit scorecard according to exemplary embodiments of the present
invention, and as discussed above, can be implemented using one or
more computers, one or more servers, one or more databases, and one
or more communications networks. The systems, according to
exemplary embodiments of the invention, are perhaps best
illustrated by FIGS. 4-9.
[0123] Exemplary embodiments of the present invention include an
online genetic merit scorecard system, as illustrated by using an
example in FIG. 4A. An online system indicates that the system is
accessible to a user over a network and may encompass accessibility
through data networks, including but not limited to, the internet,
intranets, private networks or dedicated channels. This online
genetic merit scorecard system 491 includes one or more processors
403a-403n, an input/output unit 404 adapted to be in communication
with the one or more processors, one or more genetic merit
databases 406 in communication with the one or more processors to
store and associate a plurality of genetic merit estimates with a
plurality of economic weighting factors, one or more electronic
interfaces 407 positioned to display an online genetic merit
scorecard and defining one or more genetic merit interfaces, and
non transitory computer-readable medium 402. The non-transitory
computer-readable medium is positioned in communication with the
one or more processors and has one or more computer programs stored
thereon including a set of instructions 405. This set of
instructions when executed by one or more processors cause the one
or more processors to perform operations of generating the genetic
merit interface to display to a user thereof one or more online
genetic merit scorecards, determining relative market value and
ranking of the genetic merits of the sale group responsive to
receiving the plurality of genetic merit estimates from the one or
more genetic merit databases and outputting to the one or more
electronic interfaces 407 the online genetic merit scorecard for
the sale group responsive to determining the relative market value
and the ranking of the genetic merits for the sale group. The
genetic merit interface allows an input of a plurality of genetic
merit estimates associated with a sale group. In certain
embodiments, the set of instructions may further include
determining relative market value for the sale group by use of one
or more multivariate non-linear regression equations based on the
plurality of genetic merit estimates. The sale group includes
cattle that are fed and harvested for beef production. The online
genetic merit scorecard includes the relative market value and one
or more rankings of genetic merits of the sale group. An example of
an online genetic merit scorecard 65 is provided in FIG. 6. Various
portions of systems and methods described herein, may include or be
executed on one or more computer systems similar to system 401.
[0124] In some embodiments, the online genetic merit scorecard
system includes one or more processors, an input/output unit
adapted to be in communication with the one or more processors, one
or more genetic merit databases in communication with the one or
more processors to store and associate a plurality of genetic merit
estimates with a plurality of economic outcomes and a plurality of
economic weighting factors; and non-transitory computer-readable
medium. This non-transitory computer-readable medium is positioned
in communication with the one or more processors and having one or
more computer programs stored thereon including a set of
instructions. This set of instructions when executed by one or more
processors cause the one or more processors to perform operations
of utilizing one or more electronic interfaces positioned to
display an online genetic merit scorecard and defining one or more
genetic merit interfaces, then determining, by one or more
processors, a plurality of economic weighting factors responsive to
receiving the plurality of genetic merit estimates from the genetic
merit interfaces and economic outcomes from the one or more genetic
merit databases. The instructions further include determining, by
one or more processors, relative market value and ranking of the
genetic merit estimates for the sale group responsive to receiving
the plurality of genetic merit estimates and the plurality of
economic weighting factors from the one or more genetic merit
databases and outputting to the one or more electronic interfaces
407 the online genetic merit scorecard for the sale group
responsive to determining the relative market value and the ranking
of the genetic merits of the sale group. The genetic merit
interface allows an input of a plurality of genetic merit estimates
associated with a sale group. The sale group includes cattle that
are fed and harvested for beef production. The online genetic merit
scorecard includes the relative market value and one or more
rankings of genetic merits of the sale group.
[0125] In certain embodiments, provided is a computer-implemented
method to determine relative market value of a sale group. The sale
group includes cattle that are fed and harvested for beef
production. The method includes determining, by one or more
processors, a plurality of economic weighting factors responsive to
a plurality of genetic merit estimates associated with the sale
group and one or more economic outcomes, and then determining, by
one or more processors, relative market value and ranking of the
genetic merits of the sale group responsive to the plurality of
genetic merit estimates and a plurality of economic weighting
factors. The method includes outputting to one or more electronic
interfaces 407, positioned to display an online genetic merit
scorecard to thereby define one or more genetic merit interfaces,
the online genetic merit scorecard for the sale group responsive to
determining the relative market value and the ranking of the
genetic merits of the sale group. The online genetic merit
scorecard includes the relative market value and one or more
rankings of genetic merits of the sale group being displayed on the
one or more genetic merit interfaces.
[0126] In certain embodiments, the online genetic merit scorecard
may further include one or more of documentation of calf management
practices associated with the sale group positioned to be readily
accessible to a user of the one or more electronic interfaces. In
certain embodiments, the online genetic merit scorecard may further
include one or more of source and age identification of the sale
group through an USDA approved process positioned to be readily
accessible to a user of the one or more electronic interfaces.
[0127] As illustrated by using an example in FIG. 4B, the methods
of determining the relative market value of a sale group as
discussed above can be driven by a computer 41 that can include,
according to various exemplary embodiments of the present
invention, at least a memory 42, a processor, and an input/output
device. As used herein, the processor can include, for example, one
or more microprocessors, microcontrollers, and other analog or
digital circuit components configured to perform the functions
described herein. The processor is the "brain" of the respective
computer, and as such, can execute one or more computer program
product or products. For example, the processor in the genetic
merit scorecard system can execute a computer program product or
instructions 43 stored in memory 42 of the computer 41, including,
for example, a product to facilitate the generation of a genetic
merit scorecard. Such a product can include a set of instructions
to display 44 a genetic merit interface at a remote computer that
would allow a user to input genetic merit estimates of an animal or
a plurality of animals. Such a product can also include
instructions to calculate 45 economic outcomes responsive to these
genetic merit estimates, and utilize 46 all genetic merit estimates
and associated economic weighting factors to determine 47 a
relative market value of a sale group. In an embodiment, one can
also generate 48 a genetic merit scorecard based on the relative
market value and the genetic merit estimates. Such a genetic merit
scorecard may contain a relative market value along with a star
ranking of the genetic merits of the animals on a percentile basis.
An example of a genetic merit scorecard 65 is provided in FIG.
6.
[0128] The processor can be any commercially available terminal
processor, or plurality of terminal processors, adapted for use in
or with the computer 41 or system 401. A processor may be any
suitable processor capable of executing/performing instructions. A
processor may include a central processing unit (CPU) that carries
out program instructions to perform the basic arithmetical,
logical, and input/output operations of the computer 41 or system
401. A processor may include code (e.g., processor firmware, a
protocol stack, a database management system, an operating system,
or a combination thereof) that creates an execution environment for
program instructions. A processor may include a programmable
processor. A processor may include general and/or special purpose
microprocessors. The processor can be, for example, the Intel.RTM.
Xeon.RTM. multicore terminal processors, Intel.RTM.
micro-architecture Nehalem, and AMD Opteron.TM. multicore terminal
processors, Intel.RTM. Core.RTM. multicore processors, Intel.RTM.
Core iSeries.RTM. multicore processors, and other processors with
single or multiple cores as is known and understood by those
skilled in the art. The processor can be operated by operating
system software installed on memory, such as Windows Vista, Windows
NT, Windows XP, UNIX or UNIX-like family of systems, including BSD
and GNU/Linux, and Mac OS X. The processor can also be, for
example, the TI OMAP 3430, Arm Cortex A8, Samsung S5PC100, or Apple
A4. The operating system for the processor can further be, for
example, the Symbian OS, Apple iOS, Blackberry OS, Android,
Microsoft Windows CE, Microsoft Phone 7, or PalmOS. Computer system
401 may be a uni-processor system including one processor (e.g.,
processor 403a), or a multi-processor system including any number
of suitable processors (e.g., 403a-403n). Multiple processors may
be employed to provide for parallel and/or sequential execution of
one or more portions of the techniques described herein. Processes
and logic flows described herein may be performed by one or more
programmable processors executing one or more computer programs to
perform functions by operating on input data and generating
corresponding output. Processes and logic flows described herein
may be performed by, and apparatus can also be implemented as,
special purpose logic circuitry, e.g., an FPGA (field programmable
gate array) or an ASIC (application specific integrated circuit).
Computer system 1000 may include a computer system employing a
plurality of computer systems (e.g., distributed computer systems)
to implement various processing functions.
[0129] A computer 41 as illustrated in the example described in
FIG. 4B can further include a non-transitory memory or more than
one non-transitory memories (referred to as memory 42 herein).
Memory 42 can be configured, for example, to store data, including
computer program product or products, which include instructions
for execution on the processor. Memory can include, for example,
both non-volatile memory, e.g., hard disks, flash memory, optical
disks, and the like, and volatile memory, e.g., SRAM, DRAM, and
SDRAM as required to support embodiments of the instant invention.
As one skilled in the art will appreciate, though the memory 42 is
depicted on, e.g., a motherboard, of the computer 41, the memory 42
can also be a separate component or device, e.g., flash memory,
connected to the computer 41 through an input/output unit or a
transceiver. As one skilled in the art will understand, the program
product or products, along with one or more databases, data
libraries, data tables, data fields, or other data records can be
stored either in memory 42 or in separate memory (also
non-transitory), for example, associated with a storage medium such
as a database (not pictured) locally accessible to the computer 41,
positioned in communication with the computer 41 through the I/O
device. Non-transitory memory further can include drivers, modules,
libraries, or engines allowing the genetic merit scorecard computer
to function as a dedicated software/hardware system (i.e., a
software service running on a dedicated computer) such as an
application server, web server, database server, file server, home
server, standalone server. For example, non-transitory memory can
include a server-side markup language processor (e.g., a PHP
processor) to interpret server-side markup language and generate
dynamic web content (e.g., a web page document) to serve to client
devices over a communications network.
[0130] Embodiments of the present invention include generating a
genetic merit interface for acquiring the information associated
with the sale group, for example, genetic merit estimates,
management information, environmental conditions, nutritional
conditions, and other information relevant to the assessment of the
sale group. In an exemplary embodiment of the present invention,
the genetic merit interface is generated by a computer program
product in communication with a computer associated with a genetic
merit scorecard system. As is perhaps best illustrated by FIG. 5,
exemplary embodiments of the present invention include a genetic
merit interface. As used herein, a genetic merit interface is a
graphical user interface facilitating the acquisition of data from
the user to determine the relative market value of an animal or a
plurality of animals. This electronic interface can also display
the genetic merit scorecard. The graphical user interface device
can include, for example, a CRT monitor, a LCD monitor, a LED
monitor, a plasma monitor, an OLED screen, a television, a DLP
monitor, a video projection, a three-dimensional projection, a
holograph, a touch screen, or any other type of user interface
which allows a user to interact with one of the plurality of remote
computers using images as is known and understood by those skilled
in the art. FIG. 5 for example illustrates a genetic merit
interface 51 that can be displayed on one or more display devices
of remote computers used by the users according to an exemplary
embodiment of the present invention.
[0131] The genetic merit interface Si can include, by way of
example, a user information form that facilitates the acquisition
of data like user name 52, user address 53, and a description of
the herd 54. The genetic merit interface may contain user login and
user verification features. The description of the herd field 54
may be modified to include the description of one animal or of a
plurality of animals or of a sale group. The genetic merit
interface 51 can also include mechanisms 55 to allow the user to
input genetic merit estimates. These mechanisms can include, for
example, a drop-down selection tool to facilitate the selection of
values already available in the genetic merit scorecard system by
using a "Choose EPD" option. These mechanisms can also include, for
example, manual input by the user of EPD values by choosing the
"Enter EPD" option. The genetic merit interface Si can also include
user navigation buttons, like a button to allow the user to input
more genetic merit estimates by using the "Click to add more
Genetic Merit Estimates" option 56. The user navigation buttons can
also include buttons such as "Submit" that allow the user to submit
the data to the merit scorecard system, and the system can generate
relative market values and display the values such as relative
market value/head 57 or relative market value/cwt 58. The genetic
merit interface 51 can also include buttons to generate a genetic
merit scorecard 59. For example, a button such as "Click to
generate Genetic Merit Scorecard" would allow the user to access a
relative market value and the genetic merit estimates in the
format, for example, as provided in the illustration in FIG. 6. The
genetic merit interface Si can also include button or navigation
options for the user to add more information to the genetic merit
scorecard system, including but not limited to, performance
information from an individual animal, or from its contemporary
group, or its relatives. The genetic merit interface 51 can also
include button or navigation options for the user to add more
information to the genetic merit scorecard system, including but
not limited to, environmental conditions, management information,
nutritional information, or combinations thereof. The genetic merit
interface 51 can include, by way of example, links to other
services available for the user. These links can be, for example,
hyper-text markup language ("HTML") links or any other kind of
linking interface as known and understood by those skilled in the
art. The user input and navigation options available on the genetic
merit interface may be used by means of input devices, such as a
mouse or a keyboard. The keyboard can include, for example, an
alphanumeric keyboard, an IBM PC keyboard, an Apple keyboard, a
chorded keyboard, a brail keyboard, a numeric keypad, a stenograph,
a QWERTY keyboard, and any other electronic keyboard as is known
and understood by those skilled in the art. The mouse can include,
for example, a mechanical mouse, an optical mouse, a
three-dimensional mouse, a gyroscopic mouse, an inertial mouse, a
double mouse system, a track ball, a laser mouse, or any other
pointing device that detects motion relative to a supporting
surface as is known and understood by those skilled in the art.
Moreover, according to various embodiments of the present
invention, the graphical user interface 51 can be an Internet
website, accessible by a communications network, and can include a
graphical user interface title (not shown), a graphical user
interface subtitle (not shown), and one or more graphical user
interface input components as known and understood by those skilled
in the art.
[0132] FIG. 6 is a schematic diagram of a genetic merit interface
51 displayed at a remote computer, along with an exemplary
representation of an output, a genetic merit scorecard 65,
according to an exemplary embodiment of the present invention. The
genetic merit scorecard 65 can include information 61 about the
user and/or owner of the animal or the plurality of animals. It 61
can also include a description of the animal or the plurality of
animals, it can also include the number of animals and their base
weight as illustrated in section 62. The genetic merit scorecard 65
can also include the genetic merit estimates provided by the user
through the genetic merit interface 51. The genetic merit scorecard
65 also includes the relative market value 64 of the sale group
displayed as a relative market value/head or relative market
value/cwt. The genetic merit scorecard may include a star ranking
63 of the genetic merits of the sale group as compared to the
national or industry values on a percentile basis. As understood by
those having skill in the art, there are numerous ways and
variations for implementing the comparison of the genetic merits of
the sale group to the national or industry values. For example,
instead of using stars, the ranking system may utilize alphabets,
numerals, characters, symbols, or combinations thereof.
[0133] The star rankings as described in Table 2 reveal where a
particular sale group rank on a percentile basis within the
industry. Values of genetic merit estimates <20.sup.th
percentile is one star, 20-40.sup.th percentile is two stars,
40-60.sup.th percentile is three stars, 60-80.sup.th percentile is
four stars, >80.sup.th percentile is five stars. The ancestral
EPD, for example, the sire's and maternal grandsire's EPD of
genetic merits may be used to estimate the rank of the sale group.
In an embodiment, the sale group's rank is then compared to values
within a proprietary database to derive the percentile rank. In
other embodiments, the sale group's rank may be compared to values
within public databases to derive the percentile rank.
TABLE-US-00004 TABLE 2 Percentile Rank within Star Ranking the
industry .star-solid. <20.sup.th percentile
.star-solid..star-solid. 20-40.sup.th percentile
.star-solid..star-solid..star-solid. 40-60.sup.th percentile
.star-solid..star-solid..star-solid..star-solid. 60-80.sup.th
percentile
.star-solid..star-solid..star-solid..star-solid..star-solid.
>80.sup.th percentile
[0134] The star rankings as described in Table 2 tell the potential
buyer of the sale group why this group is worth more or less than
the average. These component genetic merits drive the value of the
relative market prediction. The genetic merit scorecard 65 also
includes the relative market value 64 of the sale group displayed
as a relative market value/head or relative market value/cwt. As
understood by those having skill in the art, there are numerous
ways and variations for implementing the present invention.
[0135] Historically, cattle buyers have placed significantly higher
value fir feeder cattle with a known history of prior animal health
and management. Age and Source-verified cattle have attracted a
premium in the export market for the past several years. Age and
Source verification continues to provide value through specific
market channels and as the foundation for niche market products
and/or export markets. In certain embodiments, the genetic merit
scorecard system may be part of a livestock certification program.
For example, the genetic merit scorecard system can be used by
feedyards as part of a livestock certification program, like the
"Reputation Feeder Cattle" (RFC) program, as illustrated in FIGS.
7A and 7B. Using third party audited programs, for example RFC,
feedyards and buyers can identify cattle quality based on several
principles, like genetic merit, calf management practices, age and
source verification, compliance with non-hormone treatment, and
cattle care and handling guidelines. In an embodiment shown in FIG.
7A, this exemplary program consists of several parts to aid in
marketing and procurement decisions, for example: 1) Genetic Merit
Scorecard, 2) Calf Management certification, and 3) Age and Source
verification. In another embodiment shown in FIG. 7B, the RFC
program consists of several parts to aid in marketing and
procurement decisions, for example: 1) Genetic Merit Scorecard, 2)
Calf Management certification, 3) Age and Source verification, 4)
Non-hormone Treated Cattle certification, and 5) Cattle Care and
Handling verification. Once quality feeder cattle are identified,
sustaining them at the right nutritional and management framework
is important to achieve the most economic value. The genetic merit
of a sale group cannot be realized without proper health and
management practices. Without proper documentation of health and
other management practices, buyers will discount the realizable
value of the genetic merit of the animals due to the risk of
sickness and death. Documented animal health and management
programs, like weaning and vaccination programs enhance the revenue
available to cow-calf producers. The most valuable cattle are the
ones with a strong nutritional foundation, solid health history and
the genetic background to perform both in the feedlot and at the
packing plant. In certain embodiments, the sale group has
documented vaccination, mineral, and managerial processes. For
example, as illustrated in FIGS. 7A and 7B, the sample sale group
has its prescribed veterinary practices audited to show compliance
with vaccination protocols. The certificate illustrated in FIG. 7B
also provides documentation regarding both an USDA audit fir
compliance with the NHTC program, and a third party audit to show
compliance of the cattle care and handling protocols in compliance
with specific portions of the National Beef Quality Assurance
guidelines.
[0136] Documentation such as those discussed above and in FIGS. 7A
and 79 helps the buyer ascertain the costs and risk associated with
realizing the economic potential of the sale group as predicted by
the relative market value. In certain embodiments, the sale group
is composed of young animals, selected by age and source. Source
and age verification helps ensure that the buyer is receiving the
sale group for which the Genetic Merit Scorecard was generated.
Verification of source and age and Non-Hormone Treated Cattle
(NHTC) must be documented and verified through a recognized USDA
program. The USDA Agricultural Marketing Service's Non-Hormone
Treated Cattle (NHTC) Program controls the quality measures in the
trade and export of non-hormone treated beef between the European
Union (EU) and the United States. USDA's Audit, Review, and
Compliance (ARC) Branch conducts assessments to verify that the
production of non-hormone treated cattle meet the specified product
requirements of the NHTC Program guidelines for export to the EU.
Production companies that would like to be certified as an approved
NHTC Program provider must submit a written quality management
system manual outlining the policies and procedures employed to
ensure effective quality control compliance in the beef production
process of non-hormone treated cattle. The compliance program is
reviewed and certified through independent, third party audits
conducted by the ARC Branch.
[0137] Other optional USDA audited certifications include the NE3
and the Grass Fed program. Through the Never Ever 3 (NE3) program,
the cattle meet a niche consumer demand for beef that is certified
as never being given antibiotics, growth promoting hormones and/or
feed ingredients containing animal by-products. Certain consumers
desire to consume beef which has not been fed grain from birth to
harvest. Through the Grass Fed program, an operator in the beef
production process can get the "Grass Fed" marketing claim by
demonstrating that only grass and forage have been consumed by the
animal, with the exception of milk consumed prior to weaning. This
program provides verification necessary to meet the demands of this
market channel. The genetic scorecard may contain verification of
compliance with other USDA programs like NE3 and Grass Fed
programs. In other embodiments, the genetic scorecard may be
included as part of the NE3 and Grass Fed program verification
process.
[0138] The genetic scorecard may contain the age and source
verification and NHTC information. In other embodiments, the
genetic scorecard may be included as part of the age and source
verification process, as illustrated in FIG. 7A. In other
embodiments, the genetic scorecard may be included along with
verification of age and source, calf management practices,
non-hormone treatment protocols, appropriate care and handling
guidelines, as illustrated in FIG. 7B. In an embodiment of the
genetic merit scorecard system, a genetic merit scorecard may be
generated that includes a recommended feed regimen for the sale
group to maintain the relative market value based on the plurality
of genetic merit estimates and other information provided by the
user.
[0139] As is perhaps best illustrated by FIG. 8, various exemplary
embodiments of the present invention beneficially can include a
genetic merit scorecard system to determine a relative market value
of a plurality of animals, for example, a herd of calves of
livestock. The genetic merit scorecard system can include one or
more processors and a non-transitory computer-readable medium
having computer program stored thereon, including a set of
instructions, that when executed by one or more processors cause
the one or more processors to perform operations of generating a
genetic merit interface to display at one or more of the plurality
of remote computers, the genetic merit interface allowing an input
of a plurality of genetic merit estimates for an animal or a
plurality of animals and to transmit from the respective remote
computer the plurality of genetic merit estimates to the genetic
merit scorecard system; determining a relative market value for the
an animal or the plurality of animals responsive to receiving the
plurality of genetic merit estimates at a respective remote
computer; and outputting a genetic merit scorecard for an animal or
a plurality of animals responsive to determining the relative
market value.
[0140] Such a system can include, for example, a communications
network 710, a plurality of remote computers 720, a genetic merit
scorecard computer 702, associated servers 701, and a database 730.
One or more entities may control the genetic merit scorecard
administration 700 that includes a genetic merit scorecard computer
702, and associated servers 701, with communication to a database
730, and a plurality of remote computers 720. The communications
network 710 can include a telephony network, a wireline network, a
wireless network, a wide area network, a local area network, an
infrared network, a radio-frequency network, an optical network, or
any other communications network now or hereinafter created as is
known and understood by those skilled in the art. Each of the
plurality of remote computers 720 allows a human user, such as a
livestock owner, to interact with the genetic merit scorecard
system. The human user can be, for example, an owner of livestock
or an employee or agent thereof. The human user, however, is not
limited to owners of livestock or livestock producers. Any human
being can be a human user. That is, according to other exemplary
embodiments of the present invention, the human user can be an
insurer, a livestock purchaser, a livestock seller, a rancher, a
cow-calf operations owner, a feedlot operator, a member of a breed
association, a breed association, an insurance issuing entity, or
any other person working with livestock and other animals as is
known and understood by those skilled in the art. Each of the
remote computers 720 allows such a human user, for example, to
input information associated to a sale group as is described herein
with respect to the genetic merit scorecard system. Each of the
remote computers 720 allows such a human user, for example, to
receive the relative market value of a sale group, and to receive a
genetic merit scorecard.
[0141] Each of the plurality of remote computers 720 can be, for
example, any type of stationary or portable personal computing
device such as a desktop computer, laptop computer, micro computer,
mini computer, netbook computer, ultra-mobile computer, tablet
computer, handheld computer, mobile telephone, personal digital
assistant (PDA), so-called "smartphone," or any other computing
device intended to be operated directly by an end user with no
intervening computer operator as is known and understood by those
skilled in the art. Each of the plurality of remote computers 720
can include, for example, a keyboard, a mouse, a graphical user
interface device, a display, a microphone, electronic speakers, a
modern, a LAN card, a computer graphics card, a printer, a scanner,
a disk drive, a tape drive, a camera, a Wi-Fi card, a PCMCIA card,
or any other peripheral device as is known and understood by those
skilled in the art. If the remote computer is a mobile device, as
is known and understood by those skilled in the art, the mobile
device can include, but is not limited to, a cellphone device, a
handheld device, a handheld computer, a palmtop, a handheld device,
or any other mobile computing device. Such a mobile device can also
include, for example, a display screen with a touch input user
interface or a miniature keyboard, or a touch-screen interface. A
PDA can include, for example, a processor, memory, an input device,
and an output device. Additionally, a PDA, for instance, can
include a palmtop computer, a smartphone, a palm device, a portable
media player, a Wi-Fi enabled device, a global positioning system
device, or any other handheld computing device now or hereinafter
developed as is known and understood by those skilled in the art.
Embodiments having one or more computers as a laptop computer
include, for example, the Apple MacBook, MacBook Air, and MacBook
Pro product families; the Dell Inspiron and Latitude product
families; the Lenovo ThinkPad and IdeaPad product families; the
Panasonic Toughbook product families; and the Toshiba Satellite
product families. Examples of embodiments having one or more remote
computers 720 as a smartphone include, for example, the iPhone
series by Apple Computer, Inc. of Cupertino, Calif. and the Droid
devices by Motorola, Inc. of Schaumburg, Ill.
[0142] Each of the remote computers 720 allows such a human user,
for example, to receive the relative market value of a sale group,
and to receive a genetic merit scorecard. The relative market value
of a sale group and the genetic merit scorecard may be received by
a user in a variety of formats, including but not limited to, paper
print-outs, graphical or text displays on a computer or mobile
device, electronic messages like an e-mail or text, online formats,
and other equivalent formats. The output from a genetic merit
scorecard system can include other techniques including updating a
record in a database, updating a spreadsheet, and sending
instructions and/or data to specialized software, such as an
application on a mobile device, or combinations thereof. In other
embodiments, the output from a genetic merit scorecard system may
include formats and reports stored on computer readable medium
(such as a CD, USB flash drive or other removable storage device,
computer hard drive, or computer network server, etc.). The output
from a genetic merit scorecard system, particularly those stored on
computer readable medium, can be part of a database, which may
optionally be accessible via the internet, such as a database of
relative market values or genetic merit estimates associated to one
or more sale groups stored on a computer network server. The
database may be a secure database with security features that limit
access to the relative market values or genetic merit scorecards,
such as to allow only authorized users to view them. The output
from a genetic merit scorecard system may be transmitted to a
plurality of potential buyers of the livestock sale groups. The
output from a genetic merit scorecard system may be transmitted to
web-based public or private livestock sales and marketing systems.
Such sales and marketing systems may include online auctions, live
auctions, individualized cattle purchases, broker mediated cattle
purchases, video marketing, online marketing, and other
combinations thereof. In other embodiments, the output from a
genetic merit scorecard system may accompany the description of a
sale group, and may be marketed or distributed in different
formats, including but not limited to, written catalogs, websites,
specialized sales software, or satellite television.
[0143] According to various exemplary embodiments of the present
invention, the database 730 can be any database structure as is
known and understood by those skilled in the art. The databases
discussed herein, including database 730, can be, for example, any
sort of organized collection of data in digital form. Databases,
including database 730, can include the database structure as well
as the computer programs that provide database services to other
computer programs or computers, as defined by the client-server
model, and any computer dedicated to running such computer programs
(i.e., a database server). An exemplary database model, for
example, is Microsoft SQL Server 2008 R2. Databases can include a
database management system (DBMS) consisting of software that
operates the database, provides storage, access, security, backup
and other facilities. DBMS can support multiple query languages,
including, for example, SQL, XQuery, OQL, LINQ, JDOQL, and JPAQL.
Databases can implement any known database model or database
models, including, for example, a relational model, a hierarchical
model, a network model, or an object-oriented model. The DBMS can
include Data Definition Language (DDL) for defining the structure
of the database, Data Control Language (DCL) for defining
security/access controls, and Data Manipulation Language (DML) for
querying and updating data. The DBMS can further include interface
drivers, which are code libraries that provide methods to prepare
statements, execute statements, fetch results, etc. Examples of
interface drivers include ODBC, JDBC, MySQL/PHP, FireBird/Python.
DBMS can further include a SQL engine to interpret and execute the
DDL, DCL, and DML statements, which includes a compiler, optimizer,
and executor. DBMS can further include a transaction engine to
ensure that multiple SQL statements either succeed or fail as a
group, according to application dictates. DBMS can further include
a relational engine to implement relational objects such as Table,
Index, and Referential integrity constraints. DBMS can further
include a storage engine to store and retrieve data from secondary
storage, as well as managing transaction commit and rollback,
backup and recovery, etc.
[0144] Data stored in fields of the databases can be updated as
needed, for example, by a user with administrative access to the
database to add new data to the libraries in the database as they
become supported. It will be appreciated by those having skill in
the art that data described herein as being stored in the databases
can also be stored or maintained in non-transitory memory and
accessed among subroutines, functions, modules, objects, program
products, or processes, fir example, according to objects and/or
variables of such subroutines, functions, modules, objects, program
products or processes. Any of the fields of the records, tables,
libraries, and so on of the database can be multi-dimensional
structures resembling an array or matrix and can include values or
references to other fields, records, tables, or libraries. Any of
the foregoing fields can contain either actual values or a link, a
join, a reference, or a pointer to other local or remote sources
for such values.
[0145] Database 730 can be, for example, a single database,
multiple databases, or a virtual database, including data from
multiple sources, for example, servers on the World Wide Web. The
genetic merit database 730 can contain several types of data,
including but not limited to, genetic merit estimates, economic
weighting factors, animal performance information, relatives'
performance information, performance information from contemporary
groups, historical sales data, sales projection data, and real-time
market values for animals and operational expenses, like feed,
labor, interest, and health. Database 730 can also contain genetic
merit estimates, including but not limited to, EPD from relatives,
and contemporary groups for average daily gain, carcass weight,
marbling, back fat thickness, feed to gain ratio, ribeye area,
yield grade, tenderness, percentage of choice, pedigree, breed
effects, feed intake, animal health, weaning weight, post-weaning
weight gain, maintenance energy, maternal merit, birth weight, or
residual feed intake, residual average daily gain, or any linear or
non-linear combination of any two or more of these traits. Database
730 can be the inventors' proprietary database (e.g., the Leachman
database) or one populated with data from publicly available
databases.
[0146] According to various exemplary embodiments of the present
invention, for example, and as illustrated by FIG. 9, the genetic
merit database 730 can be part of a data warehouse 931. Such a data
warehouse may include other databases, for example a user database
932, an administration database 933, content from or links to other
public databases 934, an auction database 936, and/or a broker
database 935. The user database 932 can be configured, for example,
to store any data related to user information, including user
names, user addresses, membership information, payment records,
data related to user's herd or livestock, and any other information
related to a user and his sale group, as is known and understood by
those skilled in the art. The administration database 933 can be
configured, for example, to store any data related to determining
relative market values and generating genetic merit scorecards,
like data related to the number of users, the animals and/or herds
used, payment records, system and access updates, database updates,
and any other information related to maintenance and operation of
the genetic merit scorecard system, as is known and understood by
those skilled in the art. The public databases 934 can contain
several types of data, including but not limited to, genetic merit
estimates, animal performance information, performance information
from relatives, performance information from contemporary groups,
historical sales data, sales projection data, and real-time market
values for animals and operational expenses, like feed, labor,
interest, and health. Database 934 can also contain publicly
available information related to the sale of livestock, for
example, genetic merit estimates obtained from relatives of the
animal or the sale group. Such genetic merit estimates would
include EPD of at least two of the following: average daily gain,
carcass weight, marbling, back fat thickness, feed to gain ratio,
ribeye area, yield grade, tenderness, percentage of choice,
pedigree, breed effects, feed intake, weaning weight, post-weaning
weight gain, maintenance energy, maternal merit, birth weight,
residual feed intake, animal health, residual average daily gain,
or any linear or non-linear combination of any two or more of these
traits. The broker database 935 can be configured, for example, to
store any data related to livestock sales. For example, such data
may include data related to buyers of livestock, sellers of
livestock, past purchasing and selling behaviors, past purchases,
past sales, and related geographic information. The auction
database 936 can be configured, for example, to store any data
related to livestock auctions. For example, such data may include
data related to buyers of livestock, sellers of livestock, past
bidding and purchasing behaviors, past purchases, and related
geographic information. The auction database 936 can be configured
to store historical auction data, such as the characteristics of
the sale groups and the final sale prices. Databases can be, for
example, a Microsoft SQL server providing database services as an
enterprise-class server that providing reliable capabilities when
used to support web applications. Microsoft SQL can store, for
example, all data required by the genetic merit scorecard system
for administration, user, and application support.
[0147] FIG. 9 is a schematic block diagram of a system,
computer-implemented method, and non-transitory, computer-readable
medium configured to run on the internet to determine relative
market value of a sale group, according to an exemplary embodiment
of the present invention. Such exemplary embodiments of the present
invention can provide a home page 901 that facilitates selection,
confirmation, and purchase of genetic merit scorecards via the
Internet 900. Genetic Merit Scorecard computers 700 would launch a
home page 901 at remote computers 720 or at buyer computers 740.
The home page can be operably configured to interface with a user
interface 911, an online business administration portal 921, and a
data warehouse 931. The user interface 911 can include, for
example, at least one or more of several modules, including but not
limited to, a genetic merit scorecard information module 912, a
genetic merit interface module 913, a genetic merit scorecard
generating module 914, a cattle certification module 915, an
auction module 916, a broker module 917, and a payment center
module 918. Whereas the user interface 911 can be, for example, the
face of the system to the user, the online business administration
portal 921 can be, for example, the face of the system to the
entity that is operating the genetic merit scorecard system. The
business administration portal 921 can therefore include, for
example, a user administration module 922, a database
administration module 923, a financial administration module 924,
and an application administration module 925. The financial
administration module 924 can be configured to communicate with the
payment center 918, and accept different mechanisms of payment.
Payment mechanisms, include for example, electronic checks (ACH),
paper checks by U.S. mail, debit cards, credit cards, gift cards,
coupon card, coupon, debit cards by U.S. mail, credit cards by U.S.
mail, Internet cash, Internet payment mechanisms such as PayPal,
and any other payment mechanism now known or herein after developed
as is known and understood by those skilled in the art.
[0148] Although the various computer program product modules,
including the a genetic merit scorecard information module 912, a
genetic merit interface module 913, a genetic merit scorecard
generating module 914, a cattle certification module 915, an
auction module 916, a broker module 917, a payment center module
918, a user administration module 922, a database administration
module 923, a financial administration module 924, and an
application administration module 925, are described herein as
individual computer program product modules, those having skill in
the art will appreciate that these computer program product modules
may exist as combinations and may comprise other modules or
sub-modules that perform functions described of these computer
program product modules. In large-scale implementations or
operations, these computer program product modules may comprise
several sub-modules according to techniques or programming
conventions known to those having skill in the art. The following
description will be understood by those having skill in the art to
not limit the invention to using any particular type, style, or
number of Objects, classes, functions, or subroutines over any
other object, class, function, or subroutines that will achieve the
functions described herein.
[0149] FIG. 10 is a schematic block diagram of a system,
computer-implemented method, and non-transitory, computer-readable
medium configured to run on the internet to determine relative
market value of a sale group and utilize this as part of an auction
system, according to an exemplary embodiment of the present
invention. The auction computer 750 is configured to be in
communication with the genetic merit scorecard computer 700. While
FIG. 10 shows two individual systems, the two systems may be a
single computer designed to carry out all functions contemplated by
this embodiment of the invention. The auction computer 750 is
configured to have an input/output device 752, supported by several
processors or servers 751. A buyer wishing to access the auction
through buyer computers 740 is directed through the genetic merit
interface to an auction module. In certain embodiments, the genetic
merit interface may have a specialized buyer interface that allows
the acquisition of all information from the buyer. The buyer
interface allows a buyer to view at least the genetic merit
scorecard and to submit bids on price of the sale group. The
buyer's information is relayed and compared to the data in an
auction database 936 that is in communication with the genetic
merit database and is configured to store any data related to
livestock auctions. For example, such data may include data related
to buyers of livestock, sellers of livestock, past bidding and
purchasing behaviors, past purchases, and related geographic
information. The auction database 936 can be configured to store
historical auction data, such as the characteristics of the sale
groups and the final sale prices.
[0150] In another embodiment, the genetic merit scorecard system
can be accessed through a buyer computer at a live auction. In this
embodiment, the buyer accesses the genetic merit scorecard of the
sale groups that he is interested in at the live auction. Here, the
buyer is using the genetic merit scorecard system only to access
information regarding the relative market value of the sale groups
and the genetic merit rankings. He is not using the online auction
options of the system.
[0151] The buyer computer 740 can be any device, including but not
limited to, a desktop computer, laptop computer, microcomputer,
minicomputer, netbook computer, ultra-mobile computer, tablet
computer, handheld computer, mobile telephone, personal digital
assistant (PDA), so-called "smartphone," or any other computing
device intended to be operated directly by an end user with no
intervening computer operator as is known and understood by those
skilled in the art.
[0152] FIG. 11 is a schematic block diagram of a system,
computer-implemented method, and non-transitory, computer-readable
medium configured to run on the internet to determine relative
market value of a sale group and utilize the genetic merit
scorecard as part of a brokering system to facilitate transactions
between interested buyers and sellers of sale groups, according to
an exemplary embodiment of the present invention. The broker
computer 770 is configured to be in communication with the genetic
merit scorecard computer 700. While FIG. 10 shows two individual
systems, the two systems may be a single computer designed to carry
out all functions contemplated by this embodiment of the invention.
The broker computer 770 is configured to have an input/output
device 772, supported by several processors or servers 771. A buyer
wishing to access the system through buyer computers 740 is
directed through the genetic merit interface to a broker module. In
certain embodiments, the genetic merit interface may have a
specialized buyer interface that allows the acquisition of all
information from the buyer. The buyer interface allows a buyer to
input a plurality of purchasing requirements. The buyer's
information is relayed and compared to the data in a broker
database 935 that is in communication with the genetic merit
database 730 and is configured to store any data related to sale
groups available for purchase and purchasing requirements of
prospective buyers. The broker database 935 may store any
information required by the system to allow selection,
customization, and purchase of a sale group that meets the
particular buyer's requirements.
[0153] Embodiments of the present invention include generating a
broker module for acquiring information from the buyer regarding
his purchasing requirements. The buyer is also allowed to view the
sale groups available for purchase and other information associated
with the sale group, for example, genetic merit estimates,
environmental conditions, nutritional conditions, and other
information relevant to the assessment of the sale group. The
genetic merit interface is the graphical user interface
facilitating the acquisition of data from the user, who may be a
seller, buyer, or seeker of information related to sale groups.
[0154] The genetic merit scorecard system allows for users to pay
for the genetic merit score card and relative market value
determination for the sale groups. As described through an
illustration of an exemplary method in FIG. 9, the genetic merit
scorecard system generates a genetic merit scorecard and determines
the relative market value for a sale group. This system can be
configured to accept payment in return for these services. In the
auction system, described through an illustration of an exemplary
method in FIG. 10, the genetic merit interface allows for payments
from the buyer, to the entity generating the genetic scorecard, or
to the auctioneering entity, or to the seller. In the brokering
system, described through an illustration of an exemplary method in
FIG. 11, the buyer through the genetic merit interface on the buyer
computer, and the seller of the sale group, through the genetic
merit interface on the remote computers, can access payment
mechanisms to the genetic merit scorecard system. Payment
mechanisms, include for example, electronic checks (ACH), paper
checks by U.S. mail, debit cards, credit cards, gift cards, coupon
card, coupon, debit cards by U.S. mail, credit cards by U.S. mail,
Internet cash, Internet payment mechanisms such as PayPal, and any
other payment mechanism now known or herein after developed as is
known and understood by those skilled in the art.
[0155] According to exemplary embodiments of the present invention,
the genetic merit scorecard system can include, for example, a
payment receiver. The payment receiver can, for example, be
configured to receive notice of, and confirm payment for, a user's
customized genetic merit scorecard or relative market value
determination for a sale group. The payment receiver can, for
example, be configured to receive notice of a payment, and confirm
payment, for a sale group by a buyer using the auction system or
the brokering system. For example, the payment receiver can be
adapted to interface with computer or servers associated with a
bank, an Automated Clearing House (ACH) network or processor, a
pre-paid card processor, a credit-card processor, a debit-card
processor, a generalized payment processor, an Internet or e-cash
payment processor, or any other payment processor as is known and
understood by those skilled in the art. As is known and understood
by those skilled in the art, ACH is the name of an electronic
network for financial transactions in the United States and is
regulated by the Federal Reserve. Responsive to such interfacing
with a payment processor, the payment receiver can confirm that
payment for the customized genetic merit scorecard or relative
market value determination for a sale group has been received from
the user and store a record of such payment in the database.
Responsive to the payment receiver confirming payment, the genetic
merit scorecard system can, for example, generate the customized
genetic merit scorecard or relative market value for the sale group
and store any information related to the customized products in the
respective database.
[0156] According to various exemplary embodiments of the present
invention, the genetic merit scorecard computer 700 can be a server
and can include, for example, any type of mainframe, physical
appliance, or personal computing device such as rack server,
mainframe, desktop computer, or laptop computer, dedicated in whole
or in part to running one or more services to serve the needs or
requests of client programs which may or may not be running on the
same computer. The genetic merit scorecard computer 700 can be, for
example, a dedicated software/hardware system (i.e., a software
service running on a dedicated computer) such as an application
server, web server, database server, file server, home server, or
standalone server. As one skilled in the art will appreciate,
though the genetic merit scorecard computer 700 is shown in some of
the diagrams as a single server, it is possible for remote
computers 720, auction computers 750, and buyer computers 740 to
interface with a separate web server, application server, or
network server to access the functionality of the genetic merit
scorecard computer 700, for example, through the communications
network 710 or other network options, and such a configuration may
be preferred for certain large-scale implementations. According to
various exemplary embodiments of the present invention, the auction
computer 750 can be a server and can include, for example, any type
of mainframe, physical appliance, or personal computing device such
as rack server, mainframe, desktop computer, or laptop computer,
dedicated in whole or in part to running one or more services to
serve the needs or requests of client programs which may or may not
be running on the same computer. As one skilled in the art will
appreciate, though the auction computer 750 is shown in some of the
diagrams as a single server, it is possible for remote computers
720, the genetic merit scorecard computer 700, and buyer computers
740 to interface with a separate web server, application server, or
network server to access the functionality of the auction computer
750, for example, through the communications network 710 or other
network options, and such a configuration may be preferred for
certain large-scale implementations.
[0157] In order to provide the ability to host multiple web and
database servers in a web farm, the genetic merit scorecard system
can include a local traffic manager (LTM), such as the Big-IP LTM
from F5, to serve as a web-platform core. The LTM can deliver high
availability, improved performance, application security, and
access control services to applications served by the genetic merit
scorecard server. The LTM removes single points of failure and
virtualizes the network and applications using industry-leading L7
intelligence. The LTM can include, for example, rich static and
dynamic load balancing methods, dynamic ratio, least connections,
and observed load balancing. The LTM can further ensure always-on
status, provide scalability, and provide management ease.
[0158] The genetic merit scorecard computer 700 and the auction
computers 750 can further include a non-transitory memory or more
than one non-transitory memories. Non-transitory memory can be
configured to store data, including computer program product or
products, which include instructions for execution on the
processor. Non-transitory memory can include both non-volatile
memory, e.g., hard disks, flash memory, optical disks, and the
like, and volatile memory, e.g., SRAM, DRAM, and SDRAM as required
to support embodiments of the instant invention. As one skilled in
the art will appreciate, though the non-transitory memory is
depicted on, e.g., a motherboard, of the genetic merit scorecard
computer 700 or the auction computers 750, the non-transitory
memory may also be a separate component or device, e.g., flash
memory, connected to the genetic merit scorecard computer 700 or
the auction computers 750 through the input/output units. As one
skilled in the art will understand, the program product or
products, along with one or more databases, data libraries, data
tables, data fields, or other data records can be stored either in
non-transitory memory or in separate memory (also non-transitory),
for example, associated with a storage medium such as database,
positioned in communication with the livestock insurance computer
through the I/O devices. Non-transitory memory can further include
drivers, modules, libraries, or engines allowing livestock
insurance computer to function as a dedicated software/hardware
system (i.e., a software service running on a dedicated computer)
such as an application server, web server, database server, file
server, home server, standalone server.
[0159] The memory of a remote computer, a buyer computer, and other
computers used in embodiments of the invention, for example, can
further include applications, drivers, modules, libraries, or
engines that allow the computers to have interactive client-side
interface capabilities, including, for example, a web browser
application, such as Microsoft.RTM. Internet Explorer.RTM. by
Microsoft Corporation of Redmond, Wash., having capabilities for
processing interactive content, such as Java, JavaScript, or Flash
plug-ins or scripts. Those having skill in the art will appreciate
that interactive interfaces, such as the genetic merit interface,
the buyer interface, and the payment graphical user interface, may
be in whole or in part dynamically generated at a server computer,
such as the genetic merit computer, or at one of the one or more
remote computers adapted to be in communication with the genetic
merit computer, using server-side processing (such as PHP, ASP,
ASP.NET) and delivered to the producer computer in static mark-up
language, such as HTML, for display at the remote computer using
the web browser and a display peripheral device. Those having skill
in the art will further appreciate that interactive interfaces,
such as the genetic merit interface, the buyer interface, and the
payment graphical user interface, may be in whole or in part
statically generated at a server, such as the genetic merit
computer, or at one of the one or more computers adapted to be in
communication with the genetic merit computer, and delivered to the
remote computer or the buyer computer for processing by the remote
computer or the buyer computer using client-side processing (such
as Java, JavaScript, or Flash) for display at the remote computer
using the web browser and the display peripheral device.
[0160] As one skilled in the art will appreciate, and is perhaps
best illustrated by FIGS. 9, 10, and 11, both memory and the
processor can also include, for example, components (e.g., drivers,
libraries, and supporting hardware connections) that allow the
computers to be connected to a display peripheral device and an
input peripheral device that allow a user direct access to the
processor and the memory. The display peripheral device can be, for
example, a computer monitor, which may also be known in the art as
a display or a visual display unit. The display peripheral device
also can include, for example, a display device, which in modern
monitors is typically a thin film transistor liquid crystal display
(TFT-LCD) thin panel, while older monitors use a cathode ray tube.
The display peripheral device can include the display device, the
circuitry, and the physical enclosure. The display peripheral
device can be used, in connection with interactive client-side
interface capabilities residing in memory, to display interactive
interfaces to a user at the remote computer or the buyer computer,
such as the genetic merit interface, the buyer interface, and the
payment graphical user interface. As discussed in greater detail
above, the display peripheral device can also be a PDA and can
function, at the same time, as a display peripheral device, an
input peripheral device, and an output peripheral device.
[0161] The input peripheral device can be, for example, a computer
keyboard, computer mouse, a touch screen (such as a touch screen
device comprising display peripheral device), a pen device,
character recognition device, voice recognition device, or a
similar input device that will be known to those having skill in
the art that allows the user at the remote computer or the buyer
computer, through mechanical, electrical, or mechanical and
electrical means to send discrete or continuous signals to the
processor. A status or other output associated with input
peripheral device can be displayed at the display peripheral
device, such as, for example, mouse pointer or a keyboard prompt.
The output of input peripheral device can be received by the
processor, for example, as a selection or a command associated with
an interactive client-side interface, such as the genetic merit
interface, the buyer interface, and the payment graphical user
interface. An interactive client-side interface may be configured,
for example, to receive a selection or a command from the input
peripheral and, responsive thereto, transmit data, including
content input by the user at the input peripheral device, as well
as other content as directed by the client-side interface, to other
servers or systems through the input/output unit.
[0162] According to various exemplary embodiments of the present
invention, the communications network 710 can connect the genetic
merit scorecard computer to the remote computers, the buyer
computers, and can connect other various networked components
together. As one skilled in the art will appreciate, the
communications network 710 can connect all of the system components
using a local area network ("LAN") or wide area network ("WAN"), or
a combination thereof. For example, the genetic merit scorecard
computer 700, its servers and the genetic merit database 730 can be
privately networked, or privately tunneled over a public network,
to allow for faster, more secure communication and better data
synchronization between computing nodes. For example genetic merit
scorecard computer 700, its servers and the genetic merit database
730 or database server can be networked using a LAN, with or one of
the one or more auction computers 750 adapted to be in
communication with the genetic merit scorecard computer 700 using a
WAN. Accordingly, though not all such configurations are depicted,
all are within the scope of various exemplary embodiments of the
present invention.
[0163] Communications network 710 can include, for example, any
public or private network communication paths to support the
communications sent and received among various components of the
genetic merit scorecard system, including but not limited to the
genetic merit scorecard computer 700, the remote computers 720, and
the buyer computers. Such networks include the public Internet, a
private intranet, a virtual private network (VPN) tunneled across
the public Intranet, for example, using a network security
protocol, such as Netscape's Secure Socket Layer (SSL) protocol.
The communications network 710 can be, for example, a
telecommunication network including a wire-based telephone network,
pager network, cellular network, or a combination thereof, and a
computer network. Accordingly, the communications network 710 can
be implemented, in whole or in part, over wireless communications
network. In addition, according to various exemplary embodiments of
the present invention, the wireless communications network can be
implemented over any of various wireless communication
technologies, for example: code division multiplexed access
("CDMA"), time division multiplexed access ("TDMA"), frequency
division multiplexed access ("FDMA"), orthogonal frequency division
multiplexed access ("OFDMA"), global system for mobile
communications ("GSM"), Analog Advanced Mobile Phone System
("AMPS"), Universal Mobile Telecommunications System ("UMTS"),
802.11a/b/g/n ("WiFi"), World Interoperability for Microwave Access
("WiMAX"), or Bluetooth.
[0164] FIGS. 12A, 12B, 12C, and 12D are a series of flow charts
depicting components of an exemplary computer program used in the
genetic merit scorecard system according to an exemplary embodiment
of the present invention. As illustrated by an exemplary embodiment
in FIG. 12A, the computer program generates 101 a genetic merit
interface at the remote computers. Through this interface, a user
can login to the genetic merit scorecard system 102 if he is
already a registered user. If he is not a registered user, a new
user record 103 is created. The user can then proceed to access his
choices 104 of accessing an existing genetic merit scorecard 105 or
of generating a new scorecard. A user can access an existing
genetic merit scorecard 106 and exit the system. If he wishes to
obtain a genetic merit scorecard for a sale group, he is presented
107 with options of either entering the EN) 110 for the sale group
or choosing 108 from the EPD. If he elects 109 to choose EPD from
the genetic merit database 730, he is presented with various
genetic merits and their corresponding EPD applicable to the sale
group, in certain embodiments of the invention, a user may fill out
a release form authorizing the release of information on registered
animals in the sale group. This form is usually specific to each
breed. The breed organization will then send a list of the
registered animals with the corresponding EPD, and this information
may be used to calculate the relative market value of the sale
group. The user may be presented with a series of potential sires
as the ancestors of the sale group from the genetic merit database
730 and the user can make appropriate selections. In certain
embodiments of the invention, the user is asked to provide more
information 111 regarding the sale group, like environmental
information 112, management information 114, nutritional
information 116, and performance information 118. The user can
either skip the step or provide the relevant environmental
information 113, management information 115, nutritional
information 117, and performance information 119. This is only an
exemplary embodiment. The computer program can be designed to
accommodate more inputs, including but not limited to, the DNA
information associated with the sale group, source of the sale
group, or age of the sale group. As illustrated by an exemplary
embodiment in FIG. 12C, once the user inputs all this information,
the program is configured to run simulation models responsive to
these inputs and calculate economic outcomes 149. The program may
use 150 current and historical data from the genetic merit
database, as described elsewhere in this application. In certain
embodiments of the invention, steps 149 and 151 may not be executed
during the calculation of the relative market value for a
particular sale group. The multivariate regression is used to
estimate the .beta. periodically but not necessarily on every sale
group. In certain embodiments of the invention, steps 149, 150,
151, and 152 may be replaced with steps from FIGS. 3B-3F. FIGS.
3B-3F describe other exemplary computer implemented methods to
determine the relative market value of a sale group. In other
embodiments of the invention, the genetic merit may be directly
utilized in the simulation model. In certain embodiments of the
invention, the genetic merit estimates and other information are
utilized in steps 150 and 152, and the relative market value and
the genetic merit scorecard are calculated for the sale group. The
program then determines the relative market value 152, as shown by
an illustrative example. Then the genetic merit scorecard is
generated 153 and the user is notified about its availability 154.
The user is then offered an agreement 155 and a list of payment
options 156 to pay for the service. Once the user sends his
acceptance 157 and a payment 158, the system verifies the payment
and accepts it 159. The genetic merit scorecard is sent to the user
160 in any output format of his choice. The relative market value
of a sale group and the genetic merit scorecard may be received by
a user in a variety of formats, including but not limited to, paper
print-outs, graphical or text displays on a computer or mobile
device, electronic messages like an e-mail or text, online formats,
and other equivalent formats.
[0165] As illustrated by an exemplary embodiment in FIG. 12B, the
user of the genetic merit scorecard system can purchase a sale
group 120 through one of two exemplary non-limiting ways. If the
user is interested in purchasing a sale group through an online
auction 121, he can view 122 all available sale groups, the
associated genetic merit scorecards, and relative market values.
The program allows the user to place a bid 123 on a sale group of
his choice. If the bid is valid, 124 in that it meets the
requirements set by the auctioneering entity, then the bid is
accepted and placed 126 in the auction database. If the bid is not
valid, then the user is notified 125. The valid bid in the database
is then compared to the other bids 128 in the database. If the bid
is lower than other bids or the seller's reserve price 129, the
user is given an option 161 of purchasing the sale group at a fixed
price set by the seller or the system, also known as the "buy now"
price. In case of these unsuccessful bids, and if the user is not
interested in purchasing the sale group at the fixed price, the
user is notified 130. If user is willing to pay the fixed price set
161 by the seller or the system, then bidding closes and the user
is notified that his bid was successful 132, and a transaction with
the seller of the sale group is initiated (145 on FIG. 12C). If the
bid is the highest bid for the sale group 131, but the time period
thr submitting bids 162 is not over, then the bid is back placed
for consideration. But if the bid is the highest for the sale group
and the time period for bidding is over, then the user is notified
that his bid was successful 132, and a transaction with the seller
of the sale group is initiated (145 on FIG. 12C). The user is
offered an agreement 145 and a list of payment options 146 to pay
for the service and/or for the purchase of the sale group. Once the
user sends his acceptance and a payment 147, the system verifies
the payment and sends it to the seller for his acceptance 148, and
the deal is consummated. The agreements, the relative market value
of a sale group, and the genetic merit scorecard may be received by
a user in a variety of formats, including but not limited to, paper
print-outs, graphical or text displays on a computer or mobile
device, electronic messages like an e-mail or text, and other
equivalent formats. The genetic merit scorecard system according to
various exemplary embodiments of the present invention can also be
adapted to distribute payments to the sellers of the sale groups
responsive to receiving payments from the buyers.
[0166] The exemplary embodiment illustrated in FIG. 12B also allows
for a user to purchase a sale group without the auction process.
Here the user is presented with the choice of entering
individualized purchasing requirements 133 or choosing requirements
set in the system 136. If the user chooses to input his own
requirements, then the program allows for the creation of a user
profile 134 and the input of purchasing requirements for the sale
group from the user 135. The user can also choose existing
purchasing requirements present in the system 137. Once data is
received in the broker database regarding the purchasing
requirements from the user 138, then the data is compared against
the information for the sale groups present in the genetic merit
database 139. Once available sale groups meeting the user's
purchasing requirements are identified 140, a confirmation process
is initiated to verify that the sale group is still available 141.
If the sale group is no longer available for sale, then the user is
notified regarding the unsuccessful process and his requirements
are stored for future notification 144, for example, if a sale
group becomes available. A notification is sent to the seller to
confirm the continued availability of one or more sale groups 142
and if availability is confirmed by the seller 143, then a
transaction with the seller of the sale group is initiated (145 in
FIG. 12C). In certain embodiments of the invention, the seller is
notified of the interest from the user, and the system may not
contain modules facilitating the sales of the sale groups. In other
embodiments of the invention, for example as shown in FIG. 12C, the
user is offered an agreement 145 and a list of payment options 146
to pay for the service and/or for the purchase of the sale group.
Once the user sends his acceptance and a payment 147, the system
verifies the payment and sends it to the seller for his acceptance
148, and the deal is consummated. The agreements, the relative
market value of a sale group and the genetic merit scorecard may be
received by a user in a variety of formats, including but not
limited to, paper print-outs, graphical or text displays on a
computer or mobile device, electronic messages like an e-mail or
text, and other equivalent formats. The genetic merit scorecard
system according to various exemplary embodiments of the present
invention can also be adapted to distribute payments to the sellers
of the sale groups responsive to receiving payments from the
buyers.
[0167] In certain embodiments of the invention, if the user does
not wish to enter individualized purchasing requirements 133 or
choose requirements set in the system 136, he can view 163 all the
available sale groups and their associated information, including
the genetic merit scorecards, and relative market value in FIG.
12D. In certain embodiments of the invention, the users may be
buyers, who have registered with the genetic merit scorecard
system. These registered users may view a "show list" of all
available sale groups and their associated information, including
the genetic merit scorecards, and relative market value. These
lists provide information associated with the sale group, for
example the genetic merit scorecard 65, shown in FIG. 6, and
Reputation Feeder Cattle Certificate, shown in FIG. 7. In the
exemplary embodiment illustrated in FIG. 12D, upon viewing
information related to the sale groups, the user can choose to
purchase 164 one or more sale groups, and the system will provide
further information 165 regarding location, time and other details
regarding the sale of the particular sale groups. The user can then
choose to initiate purchase transaction 166 with the seller, or
exit the system. As shown in an exemplary embodiment in FIG. 12C,
the user is then offered an agreement and a list of payment options
146 to pay for the service and/or for the purchase of the sale
group. Once the user sends his acceptance and a payment 147, the
system verifies the payment and sends it to the seller for his
acceptance 148, and the deal is consummated. The agreements, the
relative market value of a sale group, and the genetic merit
scorecard may be received by a user in a variety of formats,
including but not limited to, paper print-outs, graphical or text
displays on a computer or mobile device, electronic messages like
an e-mail or text, and other equivalent formats. The genetic merit
scorecard system according to various exemplary embodiments of the
present invention can also be adapted to distribute payments to the
sellers of the sale groups responsive to receiving payments from
the buyers.
[0168] It is important to note that while embodiments of the
present invention have been described in the context of a fully
functional system, those skilled in the art will appreciate that
the mechanism of at least portions of the present invention or
aspects thereof are capable of being distributed in the form of a
computer-readable program product stored in a tangible computer
medium and a computer-readable medium of instructions in a variety
of forms for execution on a processor, processors, or the like, and
that the present invention applies equally regardless of the
particular type of signal-bearing media used to actually carry out
the distribution. Note, the computer readable program product can
be in the form of microcode, programs, routines, and symbolic
languages that provide a specific set or sets of ordered operations
that control the functioning of the hardware and direct its
operation, as known and understood by those skilled in the art.
Examples of computer readable media include, but are not limited
to: nonvolatile hard-coded type media such as read only memories
(ROMs), CD-ROMs, and DVD-ROMs, or erasable, electrically
programmable read only memories (EEPROMs), recordable type media
such as floppy disks, hard disk drives, CD-R/RWs, DVD-RAMs,
DVD-R/RWs, DVD+RIRWs, flash drives, memory sticks, HD-DVDs, mini
disks, laser disks, Blu-ray disks, and other newer types of
memories, and transmission type media such as digital and analog
communication links.
[0169] The disclosures of U.S. Nonprovisional application Ser. No.
14/152,845 filed on Jan. 10, 2014, U.S. Nonprovisional application
Ser. No. 14/011,304 filed on Aug. 27, 2013, now U.S. Pat. No.
8,660,888 issued on Feb. 25, 2014, and U.S. Provisional Patent
Application Ser. Nos. 61/811,720, filed on Apr. 13, 2013,
61/822,736, filed on May 13, 2013, and 61/860,686 filed on Jul. 31,
2013, are all incorporated herein by reference in their
entireties.
[0170] Moreover, the foregoing has broadly outlined certain
objectives, features, and technical advantages of the present
invention and a detailed description of the invention so that
embodiments of the invention may be better understood in light of
features and advantages of the invention as described herein, which
form the subject of certain claims of the invention. It should be
appreciated that the conception and specific embodiment disclosed
may be readily utilized as a basis for modifying or designing other
structures for carrying out the same purposes of the present
invention. It should also be realized that such equivalent
constructions do not depart from the invention as set forth in the
appended claims. The novel features which are believed to be
characteristic of the invention, both as to its organization and
method of operation, together with further objects and advantages
are better understood from the description above when considered in
connection with the accompanying figures. It is to be expressly
understood, however, that such description and figures are provided
for the purpose of illustration and description only and are not
intended as a definition of the limits of the present invention, it
will be apparent to those skilled in the art that various
modifications and changes can be made within the spirit and scope
of the invention as described in the foregoing specification.
* * * * *