Note: Descriptions are shown in the official language in which they were submitted.
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SYSTEM FOR REAL-TIME CHARACTERIZATION
OF RUMINANT FEED COMPONENTS
Cross-Reference to Related Application
This application is a continuatiori-in-part of US.S.N. 11/494,312 filed on
July 27,
2006, which is hereby incorporated by reference in its entirety.
Field of the Invention
The present invention relates to a system for screening a crop plant for the
plant's
starch and/or fiber digestion characteristics. Particularly, the present
invention is a
system for accurately predicting the starch and fiber digestion
characteristics of a crop
plant by Near Infrared Spectrometer ("NIRS") analysis and preserving the
identity of the
crop plants in order to create feed formulations that result in optimum
productivity of
ruminant animals.
Background of the Invention
Starch is a major component of ruminant diets, often comprising over 30% of
lactating dairy cow diets and over 60% of diets for beef feedlot finishing
diets on a dry
matter ("DM") basis. In ruminants, starch can be fermented to volatile fatty
acids in the
rumen, digested to glucose in the small intestine, or fermented to volatile
fatty acids in
the large intestine. Degradability of dietary starch affects site of digestion
and whole
tract digestibility. Site of digestion, in turn, affects fermentation acid
production, ruminal
pH,-microbial yield, and efficiency of microbial protein production. All such
factors can
affect the productivity of nuninant animals. Many factors affect site of
starch digestion
in'ruminants including DM intake, forage content of the diet, processing, and
conservation methods. Grain processing is costly but is often justified
economically to
increase degradability of starch. High moisture coin grain generally has
higher starch
degradability than dry corn grain. This is partly because vitreousness of com
endosperm
increases with maturity at harvest (Philippeau and Michalet-Doreau, 1997). In
addition,
ensiling corn increases starch degradability (Philippeau and Michalet-Doreau,
1999).
Stock et al. (1991) reported that solubility of endosperm proteins was highly
related to
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moisture level in high moisture. corn and solubility increased with time of
storage.
Endosperm proteins seem to decrease access of starch granules to
amylolytic.enzymes.
.Endosperm type also affects starch degradability, and it is well known that
the
proportion of vitreous and floury endosperm varies by corn hybrid. Dado and
Briggs
(1996) reported that in vitro starch digestibility ("IVSD") of seven hybrids
of corn with
floury endosperm was much higher than that for one yellow dent hybrid.
Philippeau et
al., (1996) reported much higher in situ ruminal starch degradation for dent
corn
compared to flint corn harvested at both the hard dough stage and mature (300
g kg' and
450 g kg'1 whole plant DM, respectively). Grain (grain refers broadly to a
harvested
commodity) processing increases the availability of starch in floury endosperm
much
more than starch in vitreous endosperm (Huntington, 1997). Cells in the floury
endosperm are completely disrupted when processed, releasing free starch
granules
(Watson and Ramstad, 1987). In contrast, there is little release of starch
granules during
processing for vitreous endosperm because the protein matrix is thicker and
stronger. It
is generally assumed"that com with a greater proportion of floury endosperm
might have
greater starch digestibility and be more responsive to processing.
Neutral detergent fiber ("NDF") from forage is an important component in many
ruminant diets. Forage NDF is needed to stimulate chewing and secretion of
salivary
buffers to neutralize fermentation acids in the rumen. Increasing the
concentration of
NDF in forage would mean that less NDF would have to be grown or purchased by
the
farmer. Thus, crops with higher than normal NDF concentrations would have
economic
value as a fiber source. However, that value would be reduced or eliminated if
the higher
NDF concentration resulted in lower digestibility and lower available energy
concentrations. Beck et al., WO/02096191, recognized the need for optimizing
starch
degradability by careful selection of corri having specific grain endosperm
type, in view
of the ruminal rate of starch degradation, moisture content, and conservation
methods
used, combined with selection of corn for silage production with specific
characteristics
for NDF content and NDF digestibility.
Selecting a plant based on its genetics for inclusion in a feed formulation
results
in inconsistent ruminant animal productivity. For example, selection of a corn
hybrid
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based on its grain endosperm type will yield inconsistent ruminant animal
productivity
over tiine. Thus, the present invention includes analyzing the starch and
fiber
digestibility characteristics of grain and a crop plant for use as forage in
real time. The
present invention also includes preserving the identity of the grain and the
crop plant used
for forage based on their starch and fiber digestibility characteristics. The
preserit
invention further includes using the grain and crop plant used for forage from
one or
more identity preserved crop plants to create feed formulations that result in
optimum
producfivity of the ruminant animal.
Summary of the Invention
A computer-based system for characterizing in real time the nutritional
components of one of more ingredients for a ruminant feed ration, including
dry matter,
NDF, NDFd, lignified NDF ratio, percent starch, IVSD, and particle size for a
forage
material; and IVSD and particle size for a starch grain material. The system
utilizes
proprietary NIRS equations based upon prior samplings of a variety of crop
species like
dual-purpose corri silage, leafy corn silage, brown midrib ("BMR' ) corn
silage, grass
(silage/dry), alfalfa (silage/dry); BMR forage sorghum, normal dent starch
grain, floury
endosperm starch grain, and vitreous endosperm grain, and applies those
equations to
current samplings of a corresponding crop to predict in real time the
characteristics of
such forage or grain material. The real-time characterization system may also
utilize the
predicted data to calculate a "ration fermentability index" value that takes
into account
the total NDFd and IVSD characteristics (including RAS and RBS) of the forage
and
starch ingredients to be used in a feed ration to ensure that the ration will
not contribute
too much or too little digestibility to the cow. Thus, using the real-time
characterization
system enables the proper formulation of a ruminant feed ration and the
reformulation of
that ration where warranted in the case that the NDFd and IVSD characteristics
of the
feed components change over time.
The associated method of the present invention takes into account
environmental
factors by measuring the starch and fiber degradation characteristics of a
variety of
genetically different crop plants.and grain from crop plants in real time to
determine how
the crop plants should be blended into a feed formulation that results in
optimum
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productivity of the ruminant animal. It includes providing a feed formulation
resulting in
optimum ruminant productivity comprising the steps of determining starch
digestibility
characteristics of a set of crop plant samples comprising grain of the crop
plant,
developing a prediction equation based on the starch digestibility
characteristics,
obtaining a grain sample from a crop plant, determining in real time starch
digestibility
characteristics by NIRS of the sample by inputting electronically recorded
near infrared
spectrum data from said NIRS into said equation, storing and/or milling said
grain on an
identity preserved basis, and determining the amount of the crop plant to
incorporate into
a feed formulation based on the starch digestibility characteristics.
The associated method of the present invention also includes providing a
ruminant diet resulting in optimum ruminant productivity comprising the steps
of,
determining starch digestibility characteristics of grain from genetically
different crop
plants, determining NDF digestibility ("NDFd") characteristics of genetically
different
crop plants for use as forage, developing prediction equations based on the
starch
digestibility and NDFd characteristics, obtaining grain samples for use as
feed
supplements and crop plants for use as forage, determining starch and NDFd
characteristics by NIRS of the grain samples and the crop plants by inputting
electronically recorded near infrared spectrum data relating to the
characteristics into the
equations and determining the amounts of the grain and the crop plants to
incorporate
into a feed formulation based on the starch and NDF digestibility
characteristics.
The'associated method of the present invention further includes providing a
ruminant diet resulting in optimum ruminant productivity comprising the steps
of,
determining in real time starch digestibility characteristics of grain from a
crop.plants,
determining in real time NDFd characteristics of crop plants for use as
forage, preserving
the grain. and the crop plants for use as forage on an identity preserved
basis, and
determining the amounts of the grain and the crop plants for use a forage to
incorporate
into a feed formulation based on the starch and NDFd characteristics.
The real-time chaiacterization method of the present invention enhances the
energy utilization of a feed formulation by mixing identity preserved grains
together in a
formulation to obtain a specified degree of rate and extent of digestion of
the feed
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formulation. It determines the quantity of the grain to be used in a feed
formulation
based on the compatibility and NDFd of a forage source and rate of starch
digestion of
the grain source. It further determines the quantity of the grain to be used
in a feed
formulation based on the level of forage NDF and the degree of rate and extent
of starch
digestion of grain to be used in the feed formulation.
Detailed Description of the Preferred Embodiment
A computer-based system for characterizing in real time the nutritional
components of one of more ingredients for a ruminant feed ration, including
dry matter,
NDF, NDFd, lignified NDF ratio, percent starch, IVSD, and particle size for a
forage
material; and VSD and particle size for a grain material. The system utilizes
proprietary
NIRS equations based upon prior samplings of a variety of crop species like
dual-purpose
corn silage, leafy com silage, brown midrib ("BMR") corn silage, grass
(silage/dry),
alfalfa (silage/dry), BMR forage sorghum, normal dent starch grain, floury
endosperm
sfacch grain, and vitreous endosperm grain, and applies those equations to
current
samplirigs of a corresponding crop to predict in real time the characteristics
of such
forage or grain material. The real-time characterization system may also
utilize the
predicted data to calculate a "ration fermentability index" value that takes
into account
the total NDFd and IVSD characteristics (including RAS and RBS) of the forage
and
starch ingredients to be used in a feed ration to ensure that the ration will
not contribute
too much or too little digestibility to the cow. Thus, using the real-time
characterization
system enables the proper formulation of a ruminant feed ration and the
reformulation of
that ration where warranted in the case that the NDFd and IVSD characteristics
of the
feed components change over time.
For purposes of the present invention, "ruminant animal" means any animal
having a multiple-compartment stomach for digesting feed ingredients ruminated
by the
animal, including but not limited to dairy cows, beef cows, sheep, goats,
yaks, water
buffalo, and camels. Examples of dairy cows particularly include Holstein,
Guernsey,
Ayshire, Brown Swiss, Jersey, and Milking Shorthom cows.
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In the context of the present invention, "lactation cycle" means the period of
time
during which a ruminant animal produces milk following the delivery of a new-
born
animal.
As used within this application, "milk production" means the volume of milk
produced by a lactating ruminant animal during a day, week, or other relevant
time
period.
For purposes of the present invention, "milk peak" means the highest level of
milk production achieved by a ruminant animal during the lactation cycle. ,
For purposes of this invention, "milk stability" means production by the
ruminant
animal of milk across the lactation cycle in a manner that approaches the
ideal lactation
voluine each day by achieving optimum milk peak and consistent milk
persistence curves
for the ruminant animal.
As used within this application, "nutritionist" means an individual
responsible for
specifying the composition of a feeding ration for a ruminant animal. Such
nutritionist
can be a dairyfarmer, employee of a dairy farm company, or consultant hired by
such a
farmer or company.
For purposes of this invention, "neutral detergent fiber" ("NDF") rrieans the
insoluble residue remaining after boiling a feed sample in neutral detergent.
The major
components are lignin, cellulose and hemicellulose, but NDF also contains
protein, bound
nitrogen, minerals, and cuticle. It is negatively related to feed intake and
digestibility by
ruminants.
As used within this application "NDF digestibility" ("NDFd") means the amount
of NDF that is fermented by rumen microbes at a fixed time point and is used
as an
indicator of forage quality. Common endpoints for fermentation are: 24, 30, or
48 hours.
NDFd is positively associated with feed intake, milk production, and body
weight gain in
dairy cattle.
For purposes of this invention, "lignified NDF" means the fraction of NDF that
is
protected from fermentation by its chemical and physical relationship with
lignin. It is
commonly referred to as indigestible NDF and is often estimated as (lignin x
2.4).
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As used within this application, "effective fiber," more commonly referred to
as
"physically effective fiber" ("peNDF"), means the fraction of NDF that
stimulates
rumination and forms the digesta mat in the rumen. It is measured as the
fraction of
particles retained on the 1.18-mm screen when a sample is dry sieved.
For the present invention, "dry matter intake" means the amount of feed (on a
moisture-free basis) that an animal consumes in a given period of time,
typically 24
hours. Calculated as feed offered-feed refused (all on a moisture-free basis).
For purposes of the present invention, "volatile fatty acids" ("VFA") are the
end
product of anaerobic microbial fermentation of feed ingredients in the rumen.
The
common VFA's are acetate, propionate, butyrate, isobutyrate, valerate, and
isovalerate.
The VFA's are absorbed by the rumen and used by the animal for energy and
lipid
synthesis.
The real-time characterization system and associated feeding method and feed
composition of the present invention is discussed within this application for
a dairy cow.
However, it should be understood that this invention can be applied to any
other ruminant
animal including ruminants that are not used to produce milk like beef steers
used for
meat production.
A number of different variables impact the effective delivery to and
utilization by
the dairy cow of nutritional ingredients contained in a feed ration. Called
the "GELT
Effect" by Applicant, the variables include genetics, environment, location,
and traits.
The specific genetics of the cow will directly influence its, ability to
digest and absorb the
nutritional ingredients. Likewise, the specific genetics of the forage and
grain
components of the feed components can directly influence their nutritional
content of
carbohydrates, protein, and fiber. Therefore, corn genetics used for corn
silage
production have a significant range of NDF content, NDFd, and percent starch
content.
Likewise, grain genetics have a wide range of oil, protein, starch
composition, and rate
and extent of starch digestibility. Thus, the seed genetics determines the
potential of each
forage and grain quality trait to deliver nutrition to the cow. Failure to use
appropriate
agronomic inputs (e.g., fertilizers, herbicides, fungicides, pesticides) and
levels thereof
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can also have a deleterious effect upon the quality trail characteristics of
the resulting
crop grown from the seed.
The environment and weather conditions under which a crop is grown is another
key source of variability. The weather is considered an uncontrollable event.
No one
growing season is the same from one year to the next in terms of temperature
and
moisture. This directly affects and adds a high degree of variation to forage
production,
forage quality, and starch digestibility that can create subsequent
inconsistencies in a
dairy cow's performance. For example temperature and rainfall patterns during
a
growing season can affect the level of fiber (NDF), the amount, and the effect
of lignin
on fiber digestibility (NDFd). This subsequently can affect how a forage
"feeds," and
can have an increase or decrease effect on dry matter intake (DMI) and energy
intake
with dairy cows, especially cows that are limited by fill and in early
lactation.
Starch digestibility within the kernels of a corn hybrid chopped for silage
and
corn grain used for energy supplementation can also be variable by a growing
season
environment. Both the content of starch and the rate and extent of digestion
can be
altered. Thus, supplement grain added to a diet and the corn grain within corn
silage can
positively and negatively affect dairy cow productivity. Hence the environment
determines the level and range of each forage and grain quality trait.
The temperature and other feeding conditions can also directly influence the
cow's willingness or ability to intake dry matter contained in feed rations.
Thus, this
environmental variation makes it almost impossible to predict and implement a
feed
programming strategy for a dairy cow in a given production year, or design a
cropping or
ingredient purchasing program for growing or procuring forage and grain feed
ingredients without utilization of some type of real-time adjustment mechanism
to
account for this uncontrolled variation factor.
Specific harvesting techniques can also have a-deleterious influence upon the
nutritional content of the feed ingredient. Poor storage techniques (e.g.,
packing and
storage) can also adversely impact the nutritional value of grain, forage or
silage.
Sampling protocols and laboratory testing errors arising during the analysis
of the
nutritional profile of a feed ingredient can interfere with construction of an
appropriate
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feed ration. Moreover, the inocularits used to facilitate forage fermentation
to produce
silage, and preservatives for silage and grain storage can adversely impact
the nutritional
trails of the silage or grain product. Harvest management techniques therefore
determine
the net of each forage and grain quality trait. Of course, poor formulation of
the feed
ration can also affect the proper delivery of nutritional values to the dairy
cow.
Therefore, it is important to appreciate that no two forage or grain samples
are
exactly the same in nutritional content, even if grown from the same seed
variety or
hybrid, and the nutritional content of different varieties and hybrids will
probably vary
significantly -- all because of this GELT Effect.
A feeding method associated with the real-time characterization system of the
present invention is disclosed in Applicant's U.S.S.N. 11/494,312 filed on
July 27, 2006,
and Applicant's co-pending application entitled "Method and Feed for Enhancing
Ruminant Animal Nutrition" filed on even date herewith, both of which are
incorporated
hereby in their entirety.
A feed delivery system associated with the real-time characterization system
of
the present invention is disclosed in Applicant's U.S.S.N. 11/494,3 12 filed
on July 27,
2006, and Applicant's co-pending application entitled "Feed Delivery System
for
Enhancing Ruminant Animal Nutrition" filed on even date herewith, both of
which are
incorporated hereby in their entirety.
I. Interactive Effect of a Plant Crop and the Environment
Six corn hybrids were grown in duplicate plots in 3 locations in the 1999
growing
seasori.- Locations were East Lansing, MI; Lincoln, NE; and University Park,
PA. The
six'hybrids included several endosperm types: I floury, I opaque-2, 1 waxy, 1
dent and 2
flint hybrids. Plots were 32 rows wide by 400' long (30" rows).
Each field was monitored once per week beginning September 15. Following
physiological maturity at black layer (BL), grain dry matter (DM) was
determined
weekly for all plots. Grain was harvested at 60%, 70% and 80% DM from all
plots. To
minirriize probability of cross-pollination, ten ears were harvested from each
of the
middle two rows of each plot (rows 16 and 17) for a total of 20 ears. Ears
were not
harvested from plants within 100' of the ends of the 400' long plots and were
taken
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approximately every 20' along the 200' remaining. Grain was shelled from the
ears by
hand. A 500 g sample of grain was taken for determination of DM, vitreousness,
and
density. The remainder of the grain was rolled and ensiled in duplicate 4" x
12" PVC
experimental silos. An additional sample (0.5 kg) was taken as a 0 time
sample.
One of each duplicate silo from each plot and maturity was opened at 35-d
after
harvest and the other was opened at 120-d after harvest. Contents of silos
were frozen for
subsequent analysis. Samples were ground with dry ice (Wiley mill, 1-mm
screen)
before analysis. In vitro starch degradation was determined after incubation
for 7 h in
buffered media with 20% rumen fluid.
All samples were characterized for starch, sugars, ether extract, crude
protein
content, and protein solubility in sequential buffers. Samples of intact
kernels taken at
harvest were analyzed for vitreousness and density in ethanol (Philippeau and
Michalet-
Doreau, 1997). Samples taken after rolling, that were not ensiled (n=72) were
dried at 55
C, dry sieved and analyzed for particle size. Starch degradability, also
referred to herein
as digestibility, was determined. by vitro starch digestion with rumen
microbes and
measuring starch disappearance over time. Other methods for measuring starch
digestion
known in include gas production, in vitro starch disappearance using enzymes,
and in situ
starch digestion.
Vitreousness of endosperm for the hybrids tested ranged from 4 to 62%. Table 1
shows that starch digestion was affected by the corn hybrid (49.8 to 60.3%,
P<"0.001).
Table 2 shows that starch digestion increased with moisture content (46.0 to
65.8%, P <
0:001). Table also shows that starch digestion was affected by ensiling (0
days vs. 35
days and 120 days, 46.3% vs. 59.3%, P 0.001), and time of ensiling (35 days
vs. 120
days, 57.4% vs. 61.25%, P < 0.001). .
Table 3 establishes that starch digestion is dependent on several interactions
between hybrid and the environment. A'ls-value of less than 0.05 is
significant for single
sources, whereas -a p-value of less than .1 is significant for interactions
between sources.
Thus, location, moisture, hybrid, day, all had a significant affect on starch
digestibility.
The results show that the interactions of Moisture x Day, Moisture x Location,
Moisture
x Hybrid, and Hybrid x Location were all significant. For example, the affect
of the
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hybrid on starch digestibility changed at different moisture levels. Table 3
also shows
that a hybrid's affect on starch digestibility depends on the location where
it was grown
and; therefore, starch digestibility of a particular hybrid varies across
different locations.
Tables 4, 5, 6 and 7 show the data for the interaction between hybrids and
their growth
environments and the affect these interactions have on starch digestibility of
the hybrids.
For example, Table 4 shows that the affect of Day x Moisture on starch
digestibility is
disproportionate to either environmental factor alone. Likewise, the
interactive effects of
Moisture x Location (Table 5), Moisture x Hybrid (Table 6), and Hybrid x
Location
(Table 7) all show strong interactive affects on starch digestibility.
TABLE 1: Corn hybrid means.for in-vitro starch digestibility (IVSD),
averaged over three stages of maturity, 3 post harvest intervals, 2
plots per location and 3 locations.
Effect of Hybrid on IVSD
Hybrid IVSD
N4342 wx 49.8
6409.GQ 50.9
W1698 54.3
N4640Bt 57.5
NX7219 57.5
H SL-53 60.3
SE - 1.26 .
TABLE 2: IVSD means for three moistures and three storage intervals.
Effect of Moisture % on IVSD Effect of Day on IVSD
Moisture % IVSD Day IVSD
46.0 0 46.3
53.1 35 57.4
65.8 120 61.2
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[SE= 1.03 SE=0.84
TABLE 3: Levels of significance for pertinent sources of variation in IVSD.
Treatment Effects on IV Starch Digestibility
Degrees -of
Source Freedom (DF) Prob > F
Location 2 0.19
Moisture 2 <0.0001
Hybrid 5 <0.0001
Day 2 <0.0001
Moisture x Day 4 <0.0001
Moisture x Location 4 0.07
Moisture x Hybrid 10. 0.08
Hybrid x Location 10 0.08
TABLE 4: IVSD Moisture x Day interaction means for three moistures and
three storage intervals
Moisture x Day
Moisture % Day
0 35 120
20 43.9 46.7 47.5
30 44.1 55.5 59.7
40 50.8 70.1 76.4
TABLE 5: IVSD Moisture x Location interaction means for three moistures
and three locations
Moisture x Location
Moisture % Location
#1 #2 #3
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20 46.1 46.8 45.2
30 51.5 54.6 53.3
40 63.8 63.2 70.3
TABLE 6: IVSD Moisture x Hybrid interaction means for three moistures
and six hybrids
Moisture x Hybrid
Hybrid Moisture %
20 30. 40
N4342wx 41.7 44.3 63.4
6409 GQ 40.9 52.8 58.9
W1698 44.6 52.7 65.8
N4640Bt 47.8 57.8 65.0
NX7219 49.9 52.5 70.2
SL-53 51.4 58.6 71.2
TABLE 7: IVSD Hybrid x Location interaction means for six hybrids and
three locations. The number in parentheses is the rank of the
hybrid within location.
Hybrid x Location
Hybrid Location
#1 #2 #3
N4342wx 51.1 (4) 51.4(5) 46.9(6).
6409 GQ 49.7 (6) 50.1(6) 52.8 (5)
W1698 50.0 (5) 54.2 (4) 58.7 (2)
N4640Bt 56.2 (3) 61.2 (2) 53.2 (4)
NX7219 56.4 (2) 58.9 (3) 57.3 (3)
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Hybrid x Location
Hybrid Location
SL-53 59.4 (1) 61:5 (1) 60.2 (1)
II. Measurement of Starch and Fiber Degradability Characteristics
The current inventory of forage and grain ingredients on farm, as well as any
new
forage and grain crops that may be planted by the dairy farm need to be
characterized in
real time. A representative sample of each field is obtained and scanned using
NIRS at
the wavelengths required by a corresponding prediction equation previously
developed.
Fiber digestion characteristics of the plants in each field are predicted
using this equation.
Moreover, the starch digestibility characteristics of the starch and forage
sources are also
predicted using this set of equations. The starch characterisitics are then
used to
determine the ruminal available starch (RAS) and ruminal by-pass starch (RBS)
of the
multiple sources in the feed ration.
The "Ration Fermentability Index" ("RFI") tool constitutes a series of
interrelated
calculations that evaluate the nutritional effectiveness of the feed ration,
and its ability to
safefly deliver nutritional value to the dairy cow for the pertinent
production stage. First,
it takes into account the total digestibility of the feed ration, compiling
the pounds of
digestible fiber contributed by the forage source and the pounds of digestible
starch
contributed by the grain and forage sources. A range should be specified for
this total
digestibility within the Nutritional Template 32 for each stage of production
of the cows.
By checking the NDFd and IVSD values of the various forage and grain starch
ingredients used within the feed ration using the real-time characterization
tool 98 on a
periodic basis, and plugging these values into the total digestibility
equation, the
nutritionist can determine whether the GELT Effect has caused one or more of
the feed
ingredients to provide too much or too little fiber and starch digestibility
to the cow that
is fed the feed ration.
Next, the NDFd and IVSD values should be measured for the individual feed
components. This data will tell the nutritionist which specific ingredients
are
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contributing the fiber and starch digestibility to the feed ration. For
different stages of
production, the cow may need different levels of NDFd and IVSD.
Next, the relative ruminal starch ("RAS") and ruminal bypass starch ("RBS")
values should be calculated to see whether the RAS/RBS ratio is within the
range
specified within the Nutritional Template. By controlling the RAS/RBS ratio,
maximum
healthy milk production may be obtained.
Finally, by comparing the total ration digestibility, individual component
digestibilities, and dry matter, NDF, NDFd, IVSD, and RAS/RBS ratio values for
the
total diet against the corresponding values specified within the Nutritional
Template, the
nutritionist can quickly and accurately determine in real time through this
RFI tool 220
whether the feed ration ingredients need to be adjusted to bring the diet into
conformity
with the specifications during the production stage. Not only can this lead to
enhanced
milk pioduction and stability, but also it can save the cows from serious
health issues
suffered from feed rations that are too "hot" because individual feed
components
exhibited unexpectedly high digestibility:
This NIRS analysis is done in a laboratory or in the field using a portable
NIRS
instrument. It is desirable that the methods to measure these traits are
relatively quick,
e.g., in real time. Real time refers to obtaining the starch and fiber
digestibility.results
within 48 hours from when the samples are obtained and tested, and more
preferably
within 24 hours from when the samples are obtained and tested.
The NIRS method includes obtaining a set of crop plant samples with known
characteristic such as starch and fiber degradability. These characteristics
are measured
according to the IVSD and NDFd measurement methods described below. Other
starch
and NDFd measurement methods known in the art can be used as well. These crop
plant
samples are scanned in the near infrared spectrum. Reflectance in the near-
infrared
spectrum is then recorded. A prediction equation for each trait is developed
by
regressing the known measured characteristics on reflectance across
wavelengths for each
set of samples.
For each trait, the prediction equation is validated by predicting the
characteristic
of interest for an independent set of samples. According to the present
invention, the
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measured characteristics of interest in grain include without limitation: %
IVSD in the
grain, corn silage, HMC or dry corn, and particle size. These values reflect
the rate and
extent of ruminal starch digestibility at a specified digestion period,
usually 7 hours.
IVSD should be measured at different particle sizes, such-as 6 mm, 4 mm, 2 mm,
2 UD,
and 1 UD. For the forage sources, characteristics of interest include without
limitation
dry matter content, NDF, fiber digestibility (NDFd), lignin content, in vitro
whole plant
digestibility (IVTD), corn silage starch digestibility (IVSD-CS), com silage
particle size
at different lengths of chop (peNDF) and conservation processing methods.
Finally,
separate equations should be developed for different crop species to be used
with the feed
rations, including but not limited to dual-purpose corn, leafy corn, BMR corn,
grass
(silage/dry), alfalfa (silage/dry), and BMR forage sorghum, normal dent corn
starch
grain, mutt corn starch grain, floury endosperm starch grain,. and vitreous
endosperm
starch grain. Furthermore, prediction equations can predict the fiber or
starch
digestibility characteristics of the forage or starch component for different
particle sizes.
Of significant value is the fact that an "as-is" wet crop sample can be
evaluated in real
time without the need to dry and grind it as conventional laboratory NIRS -
instruments
require.
Near-infrared reflectance spectroscopy (NIRS) is a nondestructive,
instrumental
method for rapid, accurate, and precise determination of the chemical
composition of
forages and feedstuffs. NIRS is an accepted technology for feed and forage
analysis, and
industrial uses. NIRS has several distinct advantages: the speed of analysis,
non-
destructive analysis'of the sample, sirriplicity of sample preparation, and
several analyses
can be completed with one sample. Since NIRS analysis is relatively simple to
perform,
operator-induced errors are reduced (Shenk- and Westerhaus, 1994).
To measure starch degradability in vitro, a set of crop plant samples
comprising a
number of genetically different crop plants are analyzed for starch
concentration before
and after incubation in media inoculated with rumen fluid containing ruminal
microbes
for various lengths of times. Starch degradability is calculated as the amount
of starch.
that disappeared as a percent of the total starch in the sample for each time
point of
interest. Starch concentration can be determined by analysis of glucose
concentration
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before and after hydrolysis using commercially available analysis kits.
Glucose
concentration may be determined enzymatically using glucose oxidase method or
by high
performance liquid chromatography. For general methods of measuring feed
digestibility
in vitro see Goering and Van Soest (1970). An alternative method is to
incubate feed
samples in porous bags in the rumen of cattle or sheep. (Philippeau and
Michalet -
Doreau, 1997).
To measure fiber digestibility in vitro, dried plant tissues were ground with
a
Wiley mill to pass a 1 mm screen. In vitro true digestibility (IVTD) and in
vitro neutral
detergent fiber digestibility was determined using 0.5 g samples using a
modification of
the method of Goering and Van Soest (1970) with an incubation time
representing the
rumen residence time of the animal of interest such as 30h. Undigested IVTD
residue
was subjected to the neutral detergent fiber (NDF) procedure (Goering and Van
Soest,
1970). A modification of the NDF procedure was the treatment of all samples
with 0.1
ml of alpha-amylase during refluxing and again during sample filtration, as
described by
Mertens (1991). Alpha-amylase was assayed for activity prior to use, according
to
Mertens (1991). NDF digestibility (dNDF) for each sample was computed by the
equation: 100 * [(NDF-( I 00-IVTD))/NDF] .
Accuracy of the laboratory values for defining the forage quality parameters
of
the forage and the starch digestibility profile of the grains is paramount to
value creation
from the invention. To maximize the synergy of the forage and grain specs, the
accuracy
of the forage template to capture the forage synergy of the forage sources,
and to properly
develop the Feeding Template requires accurate characterization. It is
therefore
important to use only analytical laboratories that are certified by the
National Forage
Testing Association (NFTA)' to maintain the accuracy and consistency of the
characterization process.
The invention requires an approved certified lab to characterize both. forage
and
grains to establish a historic baseline for each characterized trait. This
baseline can be
used to determine the hybrid genetic effect and the environmental effect
within a given
growing season on the forage quality traits and the potential feeding value of
both forages
and grains used in the Nutritional Template. Accurate adjustments can then be
made to
17. .
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the Nutritional Template to maintain the accuracy of the resulting Feeding
Template for
each stage of dairy cow production.
The same real-time characterization process is used in the genetic development
of
superior forage and grain genetics necessary for the feed ingredients. Real-
time
characterization measures the direction, progress and level of trait
enhancement of the
breeding process. It also is used as a database development toot for screening
and
identifying the top performing genetics for invention application.
. According to the present invention, databases are developed relating the NIR
spectram to the starch and fiber degradability characteristics of a number of
genetically
different crop plants. The NIR spectrums*of a given crop plant such as corn,
soybean, or
alfalfa are used to assess the crop plant's starch and fiber degradability
characteristics.
The NIRS method may be applied to various feed crops and the traits of those
crops.
NIRS requires a calibration to reference methods (Shenk and Westerhaus, 1994).
Each
constituent requires a separate calibration, and in general, the calibration
is valid for
sirriilar types of samples.
The NIRS method of analysis is based on the relationship that exists between.
infrared absorption characteristics and the major chemical components of a
sample
(Shenk and Westerhaus, 1994). The near infrared absorption characteristics can
be used
to differentiate the chemical components. Each of the significant organic
plant
components has absorption characteristics (due to vibrations originating from
the
stretching and bending of hydrogen bonds associated with carbon, oxygen and
nitrogen)
in the near infrared region that are specific to the component of interest.
The absorption
characteristics are the primary determinants of diffuse reflectance, which
provides the
means of assessing composition. The diffuse reflectance of a sample is a sum
of the
absorption properties combined with the radiation-scattering properties of the
sample. As
a consequence the near infrared diffuse reflectance signal contains
information about
sample composition. Appropriate mathematical treatment of the reflectance data
will
result in extraction of compositional information. (Osboure et al., 1986). The
most
rudimentary way to illustrate this would be to measure the reflectance at two
wavelengths, with one wavelength chosen to be at a maximum absorption point
and the
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WO 2008/013941 PCT/US2007/016912
other at.the minimum absorption point, for the compositional factor to be
analyzed. The
ratio of the two reflectance values, based on determination of two samples,
can be
associated, by correlation, to the concentration of the specific compositional
factor in
those samples. By use of the correlation.relationship, an equation can be
developed that
will predict the concentration of the compositional factors from their
reflectance
measurements (Osboure et al., 1986).
Spectra can be collected from the sample in its natural form, or as is often
the case
with plants or plant parts, they are ground, typically to pass through a 1-mm
screen. NIR
reflectance measurements are generally transformed by the logarithm of the
reverse
reflectance (log (1/R)) (Hruschka, 1987), other mathematical transformations
known in
the art- may be used as well. Transformed reflectance data are further
mathematically
treated by employment of first- or second-derivatives, derivatives of higher
order are not
commonly used (Shenk and Westerhaus, 1994).
The calibration techniques employed are multiple linear regression (MLR)
methods relating the NIR absorbance values (x variables) at selected
wavelengths to
reference values (y values), two commonly used methods are step-up and
stepwise
regression (Shenk and Westerhaus, 1994). Other calibration methods are
principal-
component regression (PCR) (Cowe and McNicol, 1985), partial least-squares
regression
(PLS) (Martens and Naes, 1989), and artificial neural networks (ANN) (Naes et
al.,
1993)..
The methods of calibration equation differ depending on the regression method
used. The procedure when using MLR is to randomly select samples from the
calibration
population, exclude them from the calibration process and then use them as a
validation
set to assess the calibration equation (Windham et al., 1989). The method of
equation
validation used for PCR or PLS regression is cross=validation, which involves
splitting
the calibration set into several groups and conducting calibration
incrementally on every
group until each sample has been used for both calibration and validation
(Jackson, 1991;
Martens and Naes, 1989; Shenk and Westerhaus, 1994).
In this instance, NIRS.involves the collection of spectra for a set of samples
with
known- characteristics. The spectra is collected from grain kernels, or other
plant parts,
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WO 2008/013941 PCT/US2007/016912
and mathematically transformed. A calibration equation is calculated using the
PLS
method, other regression methods known in the art may be used as well.
Criteria used to
select calibration equations are low standard errors of calibration and cross
validation and
high. coefficients of multiple determinations.
This tool can also be used to measure quality trains for crop plants other
than
NFDd.and IVSD, such as oil content, crude protein, and NDF.
The real-time characterization system of the present invention is a computer-
based tool. It comprises a general programmable computer having a central
processing
unit ("CPU") controlling a memory unit, a storage unit, an input/output
("I/O") control
unit, and at least one monitor. The computer operatively connects to a
database,
containing, e.g., dry matter, NDF, NDFd, IVSD, particle size, etc. data for a
variety of
hybrids and varieties for a variety of crop plants. It may also include clock
circuitry, a
data interface, a network controller, and an internal bus. One skilled in the
art will
recognize that other peripheral components such as printers, drives,
keyboards, mousse
and the like can also be used in conjunction with the programmable the
computer.
Additionally, one skilled in the art will recognize that the programmable
computer can
utilize known hardware, software, and the like configurations of varying
computer
components to optimize the storage and manipulatiori of the data and other
information
contained within the real-time characterization tool.
An NIRS reflectance apparatus is used to measure the reflected wavelength of
crop samples, and the resulting NIRS data is stored in the database. A
software program
may be designed to be an expression of an organized set of instructions in a
coded
language. These instructions are programmed to interact with proprietary
prediction
equations stored in the memory. When a crop sample in subjected to NIRS
analysis in
real time, the resulting NIRS data is used by the prediction equations to
predict the actual
true yalue of the associated characteristics of the real-time crop sample. As
mentioned
above, the prediction equations can further predict the fiber or starch
digestibility of the
forage or grain material at different particle sizes, which can be of great
assistance in
formulating feed rations.
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The computer system on which the system resides may be a standard PC, laptop,
mainframe, handheld wireless device, or any automated data processing
equipment
capable of running software for monitoring the progress of the transplantable
material.
The CPU controls the computer system and is capable of running the system
stored in
memory. The memory may include, for example, internal memory such RAM arid/or
ROM, external memory such as CD-ROMs, DVDs, flash drives, or any curreritly
existing
or future data storage means. The clock circuit may include any type of
circuitry'capable
of generating information indicating the present time and/or date. The clock
circuitry
may also be capable of being programmed to count down a predetermined or set
amount
of time. This may be particularly important if a particular type of tissue
needs to be
refrigerated or implanted in a predetermined amount of time.
The data interface allows for communication between one or more networks
which may be a LAN (local area network), WAN (wide area network), or any type
of
network that links each party handling the tissue. Different computer systems
such as,
for example, a laptop and a wireless device typically use different protocols
(i.e.,
different languages). To allow the disparate devices to communicate, the data
interface
may include or interact with a data conversion program or device to exchange
the data.
The data interface may also allow disparate devices to communicate through a
Public
Switched Telephone Network (PSTN), the Internet, and private or semi-private
networks.
Outputs produced by such real-time characterization system include the
predicted
characteristic values for the real-time sample. However, the system may also
be
programmed to run the various computations associated with the Ration
Fermentability
Index (RFI) discussed above, and wam the user if a feed ration formulated in
accordance
with the feed ingredients analyzed by the real-time characterization system
will lie
outside of the Nutritional Template specifications, and which ingredient
caused any
problems. This can assist a nutritionist with reformulating feed rations for
ruminant.
animals. The system can also produce and print a series of reports documenting
this
information.
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III. . Real-Time Feed Formulation Method
Crops about to be harvested are analyzed for starch and fiber degradation
characteristics before harvest to provide 'information needed for harvesting
decisions. A
representative sample of each field is obtained and scanned using an NIR
spectrophotometer at the wavelengths required by the prediction equation
previously
developed. Starch and/or fiber digestion characteristics of the plants in each
field are
predicted using this equation. Information provided is used to make harvest
decisions
such as the moisture concentration at harvest and particle size to grind for
high moisture
grain and the conservation method (high moisture grain or dry grain). This
gives
additional control over the resulting feed consumed by cattle and sheep, which
helps
optimize energy intake and nutrient utilization. The NIRS analysis is done in
a
laboratory or in the field using a portable NIRS instrument.
Stored feed samples are screened for starch and fiber digestibility
characteristics
to provide information to formulate diets for optimal energy intake and
nutrient
utilization. Feeds with highly degradable starch are limited in diets to
prevent ruminal
acidosis, lower fiber digestibility and efficiency of microbial protein
production, and
decrease energy intake. Feed with low starch degradability is limited to
optimize
microbial protein production, nutrient utilization and energy intake.
The present invention also includes using traditional real-time screening
techniques, such as wet chemistry, to determine the starch and/or fiber
digestibility
characteristics of a particular crop in the field or a crop that is stored on
an identity
preserved basis. The invention, therefore includes, analyzing the starch
and/or fiber
digestibility of an identity preserved crop in real-time, using techniques
described herein
or other techniques known in the art, and using that information to prepare
feed
formulations that optimize ruminant productivity.
The present invention also includes growing a crop at a particular location
and
determining the starch degradability characteristics of the crop plant used as
grain or
NDF digestibility if used as a forage in real time, before or after harvest,
by NIRS. The
crop plant or plant parts are stored on an identity preserved basis. Based on
specific diet
requirements, conservation methods such as high-moisture fermentation or
harvesting
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WO 2008/013941 PCT/US2007/016912
field dried, and processing including either.rolling or grinding, are used
to'alter measured
starch degradability. Once a specific starch degradability target /
requirement for'a
ruminant herd is determined, a blending process of mixing fast and slow starch
degradation properties that have been accurately measured according to the
present
invention are incorporated into a feed formulation for optimum ruminant
productivity.
It is understood that the present invention is applicable to corn, alfalfa,
and other
forage crops, and can also be used to characterize forage sources in real
time. Thus, the
term "crop plant" or "crop" is meant to include any plant that is used as
silage, grain or
other plant based feed ingredient for ruminant animals.
The plant characteristics, energy (digestibility), protein and fiber content
of both
corn grain and corn forage is affected by the interaction of genetics by
environment
(GxE). Thus, according to the present invention, real-time characterization of
each
source of starch (grain) and NDF (fiber) is necessary to accurately formulate
diets for
ruminates. Once an animal production target is determined, a total mixed
ration (TMR)
is designed by combining energy, protein, fiber, vitamins and mineral
ingredients into a
mixer wagon based on predetermined metabolizable energy (ME) targets, crude
protein
and meeting adequate and sufficient fiber requirements.
Meeting the total ration NDF target and the level of NDF as a percentage of
the
total forage in the diet determines the forage component of the base diet. An
adjusted
ME value for the forage sources is determined to account for the energy
contribution
(NDF digestibility) from the forage NDF.
.The production requirement of the diet and the forage / fiber composition of
the
diet will detercinine the optimal amount and source of supplemental starch,
with either a
fast; slow or mid-point of starch degradability needed to make the most feed
efficient,
productive and healthy diet formulation. The forage characteristics of the
diet also
determines the optimum moisture content of the starch, either dry grain
(15.5%) or high
moisture grain, such as high moisture com (HMC) at 28-32% by weight, and which
conservation and processing methods are advantageous to the production and
health
impact of the diet.
23. .
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It is understood, therefore, that the present invention is a system that
optimizes a
ruminant feed formulation by analysis of identity preserved feed components on
a real-
time basis. It is further understood that the present invention includes using
various
methods of measuring, in real time, crop plant characteristics.
The above specification, drawings, and data provide a complete description of
the
feeding method and resulting feed compositions of the present invention. Since
many
embodiments of the invention can be made without departing from the spirit and
scope of
the invention, the invention resides in the claims hereinafter appended.
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