Plant waxes provide a marker profile of individual plants that, when sufficiently distinct, can be used to estimate the diet composition of grazing cattle. They also may provide a tool for reliably predicting feed intake. The traditional method (nonnegative least squares) to use these markers to predict diet composition has limitations. A newer statistical approach (Bayesian linear unmixing) deemed more efficient was tested with simulation. Samples from 8 forage species in Nebraska were analyzed for their plant- wax marker contents. Those concentrations were used to simulate 1000 diets for 4 mixtures containing 2, 3, 5 or 8 plants. The efficiency of the two methods to predict diet composition was compared. The newer approach outperformed the traditional one in all of the mixtures considered. However, predictions were considerably worse when the number of plants in the mixture was 5 or 8. When forage mixtures are complex, additional steps will be needed to predict diet composition, and thereby feed intake, in grazing cattle

Hamilton, Hannah C.

Lewis, Ronald M.

Vargas Jurado, Napoleón

English

UNL | Libraries

University of Nebraska - Lincoln
DigitalCommons@University of Nebraska - Lincoln
Nebraska Beef Cattle Reports Animal Science Department
2017
Delineating Complex Forage Mixtures Using Plant-
Wax Markers
Napoleón Vargas Jurado
University of Nebraska - Lincoln
Hannah C. Hamilton
University of Nebraska - Lincoln
Ronald M. Lewis
University of Nebraska-Lincoln, ron.lewis@unl.edu
Follow this and additional works at: http://digitalcommons.unl.edu/animalscinbcr
Part of the Large or Food Animal and Equine Medicine Commons, Meat Science Commons, and
the Veterinary Preventive Medicine, Epidemiology, and Public Health Commons
This Article is brought to you for free and open access by the Animal Science Department at DigitalCommons@University of Nebraska - Lincoln. It has
been accepted for inclusion in Nebraska Beef Cattle Reports by an authorized administrator of DigitalCommons@University of Nebraska - Lincoln.
Vargas Jurado, Napoleón; Hamilton, Hannah C.; and Lewis, Ronald M., "Delineating Complex Forage Mixtures Using Plant-Wax
Markers" (2017). Nebraska Beef Cattle Reports. 1001.
http://digitalcommons.unl.edu/animalscinbcr/1001
2017 Nebraska Beef Cattle Report · 73 
©  Th e Board Regents of the University of 
Nebraska. All rights reserved.
(leadplant (Amorpha canescens); sweet clo-
ver (Melilotus offi  cinalis)).
Plant- wax marker concentrations (mg 
/ kg) were measured using gas chromatog-
raphy at two development stages (at peak 
vegetative and maturity). Four mixtures 
were simulated using i) sweet clover and 
cheatgrass, ii) sweet clover, cheatgrass and 
blue grama, iii) sweet clover, cheatgrass, 
blue grama, sideoats grama and west-
ern wheatgrass, and iv) all 8 species. For 
all mixtures, 1000 diets were simulated. 
Analyses were performed using both the 
traditional and the newer method.
Th e ability (effi  ciency) to delineate 
the mixtures for each of the methods was 
assessed based on 4 statistics. Firstly, the 
discrepancy between the true (simulated) 
values and their estimates, or the estimation 
error (EE), was assessed. Lower EE corre-
spond with improved effi  ciency. Secondly, 
the proportion of times that the estimates 
were within a fi xed distance of the true 
values was determined (FD). For reliable 
predictions, FD should be between 0.93 and 
0.97. Th irdly, the importance (signifi cance) 
of a particular plant- wax marker to separate 
plants into distinct categories was evalu-
ated. Lastly, procedures that graphically 
cluster plants depending on similarities in 
their plant- wax marker contents were used.
the botanical makeup of the diet needs 
to be estimated fi rst. Given that botanical 
mixtures are compositional in nature (i.e., 
are positive and sum to one), constraints 
have to be imposed during estimation. Tra-
ditional methods, do not address some of 
these constraints. Conversely, more recent 
statistical methods do and have successfully 
been used to estimate the composition of 
mixtures in, for instance, image analy-
sis and geochemistry but, as of yet, not 
in animal diets. Th e proposed approach 
would directly account for such constraints. 
However, validating the methodology is 
necessary to make sure it performs (at 
least) as well as the traditional technique. 
Th is validation was performed through a 
simulation study.
Procedure
As described elsewhere (2017 Nebras-
ka Beef Report, pp. 69–72), 8 plant spe-
cies commonly found in Nebraska were 
collected. Th ese forages were 3 cool- season 
(C3) grasses (cheatgrass (Bromus tecto-
rum); needle- and- thread (Hesperostipa 
comata); western wheatgrass (Pascopyrum 
smithii)), 3 warm- season (C4) grasses (blue 
grama (Bouteloua gracilis); little bluestem 
(Schizachyrium scoparium); sideoats grama 
(Bouteloua curtipendula)), and 2 legumes 
Napoleón Vargas Jurado
Hannah C. Hamilton
Ronald M. Lewis
Summary with Implications
Plant waxes provide a marker profi le 
of individual plants that, when suffi  ciently 
distinct, can be used to estimate the diet 
composition of grazing cattle. Th ey also may 
provide a tool for reliably predicting feed 
intake. Th e traditional method (nonnegative 
least squares) to use these markers to predict 
diet composition has limitations. A newer 
statistical approach (Bayesian linear unmix-
ing) deemed more effi  cient was tested with 
simulation. Samples from 8 forage species in 
Nebraska were analyzed for their plant- wax 
marker contents. Th ose concentrations were 
used to simulate 1000 diets for 4 mixtures 
containing 2, 3, 5 or 8 plants. Th e effi  ciency 
of the two methods to predict diet compo-
sition was compared. Th e newer approach 
outperformed the traditional one in all of the 
mixtures considered. However, predictions 
were considerably worse when the number 
of plants in the mixture was 5 or 8. When 
forage mixtures are complex, additional steps 
will be needed to predict diet composition, 
and thereby feed intake, in grazing cattle.
Introduction
Estimating diet composition and feed 
intake under grazing conditions is chal-
lenging but necessary to determine feed 
effi  ciency. Plant- wax markers, particularly 
n- alkanes (ALK) and long- chain alcohols 
(LCOH), have been used successfully to 
estimate the botanical composition of the 
diet in grazing conditions. Th e ability of 
ALK and LCOH to delineate the plants in 
the diet depends on their marker profi les 
being suffi  ciently diff erent among the plants 
on off er. Importantly, to estimate feed in-
take using the plant- wax marker technique, 
 Delineating Complex Forage Mixtures 
Using Plant- Wax Markers
Table 1.  Effi  ciency of a newer (Bayesian linear hierarchical unmixing) and a traditional 
(non- negative least squares) method to estimate diet composition.
Statistic1 Plant mixture Newer Traditional
EE 2 0.018 0.033
3 0.034 0.052
5 0.094 0.175
8 0.216 0.485
FD 2 0.907 0.698
3 0.923 0.818
5 0.652 0.518
8 0.669 0.491
1 Statistics: estimation error (EE) and the proportion of times that the estimates were within a fi xed distance of the 
true values (FD).
74 · 2017 Nebraska Beef Cattle Report
Figure 1. Plant- wax marker importance for 8 plant species at their early (vegetative) stage of growth) 
based on concentrations of 5 n- alkanes (C27, C29, C31, C33 and C35) and 5 long- chain alcohols (C24OH, 
C26OH, C28OH, C30OH and C32OH).
Results
Mean ALK and LCOH concentrations 
for the 8 plant species were presented in 
2017 Nebraska Beef Report, pp. 69–72. In 
general, ALK concentrations are lower than 
those of LCOH, which is in accordance with 
other studies.
With regards to the effi  ciency of de-
lineating forage mixtures, for the 2- plant 
mixture the newer method was clearly more 
effi  cient, with EE of 0.018 compared to that 
of traditional method of 0.033 (Table 1). 
Th at represented a 50% improvement in 
effi  ciency. Th e FD also was better with the 
new method, although somewhat lower 
than the expected range. For the 3- plant 
mixture similar results were obtained 
although the reduction in EE was smaller, 
0.034 and 0.052 for the new and traditional 
method, respectively. Still the diff erence 
between the two methods represented a 
35% improvement in effi  ciency. In addition, 
the FD for the new method was close to the 
range expected, while that for the tradition-
al method was well below.
For the 5- plant mixtures, the EE were 
0.094 and 0.175 for the new and traditional 
method, respectively; however, FD was 
considerably reduced for both methods 
to 0.652 (new) and 0.518 (traditional). A 
similar result was obtained for the 8- plant 
mixture, with lower effi  ciencies for both 
methods: the estimation errors increased 
substantially and the proportion of times 
true and estimated values coincided 
decreased considerably. However, the new 
method was still around 50% more effi  cient 
than the traditional. One likely reason for 
this signifi cant decline in ability to deter-
mine diet composition may be insuffi  cient 
diff erences in the ALK and LCOH profi les 
among the plants when more and similar 
species were combined.
With this particular set of plant species, 
delineating relatively simple mixtures (2 
or 3 plants) using the new method is quite 
feasible. However, increasing the number of 
plants in the mixture dramatically reduced 
the effi  ciency of the both methods. As 
shown in Figure 1, the C32OH and C24OH 
help the least in species delineation, pos-
sibly due to many of the plant species not 
having these two markers present. When 
evaluating the similarities in plant- waxes 
profi les for the diff erent plants, C31, C33, 
C35 and C28OH were common to the cool- 
2017 Nebraska Beef Cattle Report · 75 
Conclusion
In conclusion, the reliability of predic-
tions of diet composition was improved 
by using a more sophisticated statistical 
approach in the evaluation. However, fur-
ther developments in the application of the 
plant- wax marker technique are still needed 
to determine the dietary choices and feed 
intakes of cattle grazing complex swards 
typical to western rangelands.
Napoleón Vargas Jurado, graduate Student
Hannah C. Hamilton, graduate student
Ronald M. Lewis, full professor, animal 
science, Lincoln
and warm- season grasses, while C26OH 
was important to distinguish the legumes. 
Although the C32OH was less important 
than many other markers to delineate plant 
species generally, in was unique to C4 
grasses; therefore, it facilitated separating 
the cool- and warm- season grasses.
One possible way to increase the effi  -
ciency of the plant- wax methodology, when 
considering mixtures of more plants, is to 
add other plant markers such as long- chain 
fatty acids and alkenes. Additionally, plants 
could be grouped based on their taxonomy 
or function to simplify the complexity of 
the sward being characterized. Such an ap-
proach may be particularly valuable when 
the primary aim is to predict feed intake.


Delineating Complex Forage Mixtures Using Plant-Wax Markers

DigitalCommons@University of Nebraska

University of Nebraska - LincolnDigitalCommons@University of Nebraska - LincolnNebraska Beef Cattle Reports Animal Science Department2017Delineating Complex Forage Mixtures Using Plant-Wax MarkersNapoleón Vargas JuradoUniversity of Nebraska - LincolnHannah C. HamiltonUniversity of Nebraska - LincolnRonald M. LewisUniversity of Nebraska-Lincoln, ron.lewis@unl.eduFollow this and additional works at: http://digitalcommons.unl.edu/animalscinbcrPart of the Large or Food Animal and Equine Medicine Commons, Meat Science Commons, andthe Veterinary Preventive Medicine, Epidemiology, and Public Health CommonsThis Article is brought to you for free and open access by the Animal Science Department at DigitalCommons@University of Nebraska - Lincoln. It hasbeen accepted for inclusion in Nebraska Beef Cattle Reports by an authorized administrator of DigitalCommons@University of Nebraska - Lincoln.Vargas Jurado, Napoleón; Hamilton, Hannah C.; and Lewis, Ronald M., "Delineating Complex Forage Mixtures Using Plant-WaxMarkers" (2017). Nebraska Beef Cattle Reports. 1001.http://digitalcommons.unl.edu/animalscinbcr/10012017 Nebraska Beef Cattle Report · 73 ©  Th e Board Regents of the University of Nebraska. All rights reserved.(leadplant (Amorpha canescens); sweet clo-ver (Melilotus offi  cinalis)).Plant- wax marker concentrations (mg / kg) were measured using gas chromatog-raphy at two development stages (at peak vegetative and maturity). Four mixtures were simulated using i) sweet clover and cheatgrass, ii) sweet clover, cheatgrass and blue grama, iii) sweet clover, cheatgrass, blue grama, sideoats grama and west-ern wheatgrass, and iv) all 8 species. For all mixtures, 1000 diets were simulated. Analyses were performed using both the traditional and the newer method.Th e ability (effi  ciency) to delineate the mixtures for each of the methods was assessed based on 4 statistics. Firstly, the discrepancy between the true (simulated) values and their estimates, or the estimation error (EE), was assessed. Lower EE corre-spond with improved effi  ciency. Secondly, the proportion of times that the estimates were within a fi xed distance of the true values was determined (FD). For reliable predictions, FD should be between 0.93 and 0.97. Th irdly, the importance (signifi cance) of a particular plant- wax marker to separate plants into distinct categories was evalu-ated. Lastly, procedures that graphically cluster plants depending on similarities in their plant- wax marker contents were used.the botanical makeup of the diet needs to be estimated fi rst. Given that botanical mixtures are compositional in nature (i.e., are positive and sum to one), constraints have to be imposed during estimation. Tra-ditional methods, do not address some of these constraints. Conversely, more recent statistical methods do and have successfully been used to estimate the composition of mixtures in, for instance, image analy-sis and geochemistry but, as of yet, not in animal diets. Th e proposed approach would directly account for such constraints. However, validating the methodology is necessary to make sure it performs (at least) as well as the traditional technique. Th is validation was performed through a simulation study.ProcedureAs described elsewhere (2017 Nebras-ka Beef Report, pp. 69–72), 8 plant spe-cies commonly found in Nebraska were collected. Th ese forages were 3 cool- season (C3) grasses (cheatgrass (Bromus tecto-rum); needle- and- thread (Hesperostipa comata); western wheatgrass (Pascopyrum smithii)), 3 warm- season (C4) grasses (blue grama (Bouteloua gracilis); little bluestem (Schizachyrium scoparium); sideoats grama (Bouteloua curtipendula)), and 2 legumes Napoleón Vargas JuradoHannah C. HamiltonRonald M. LewisSummary with ImplicationsPlant waxes provide a marker profi le of individual plants that, when suffi  ciently distinct, can be used to estimate the diet composition of grazing cattle. Th ey also may provide a tool for reliably predicting feed intake. Th e traditional method (nonnegative least squares) to use these markers to predict diet composition has limitations. A newer statistical approach (Bayesian linear unmix-ing) deemed more effi  cient was tested with simulation. Samples from 8 forage species in Nebraska were analyzed for their plant- wax marker contents. Th ose concentrations were used to simulate 1000 diets for 4 mixtures containing 2, 3, 5 or 8 plants. Th e effi  ciency of the two methods to predict diet compo-sition was compared. Th e newer approach outperformed the traditional one in all of the mixtures considered. However, predictions were considerably worse when the number of plants in the mixture was 5 or 8. When forage mixtures are complex, additional steps will be needed to predict diet composition, and thereby feed intake, in grazing cattle.IntroductionEstimating diet composition and feed intake under grazing conditions is chal-lenging but necessary to determine feed effi  ciency. Plant- wax markers, particularly n- alkanes (ALK) and long- chain alcohols (LCOH), have been used successfully to estimate the botanical composition of the diet in grazing conditions. Th e ability of ALK and LCOH to delineate the plants in the diet depends on their marker profi les being suffi  ciently diff erent among the plants on off er. Importantly, to estimate feed in-take using the plant- wax marker technique,  Delineating Complex Forage Mixtures Using Plant- Wax MarkersTable 1.  Effi  ciency of a newer (Bayesian linear hierarchical unmixing) and a traditional (non- negative least squares) method to estimate diet composition.Statistic1 Plant mixture Newer TraditionalEE 2 0.018 0.0333 0.034 0.0525 0.094 0.1758 0.216 0.485FD 2 0.907 0.6983 0.923 0.8185 0.652 0.5188 0.669 0.4911 Statistics: estimation error (EE) and the proportion of times that the estimates were within a fi xed distance of the true values (FD).74 · 2017 Nebraska Beef Cattle ReportFigure 1. Plant- wax marker importance for 8 plant species at their early (vegetative) stage of growth) based on concentrations of 5 n- alkanes (C27, C29, C31, C33 and C35) and 5 long- chain alcohols (C24OH, C26OH, C28OH, C30OH and C32OH).ResultsMean ALK and LCOH concentrations for the 8 plant species were presented in 2017 Nebraska Beef Report, pp. 69–72. In general, ALK concentrations are lower than those of LCOH, which is in accordance with other studies.With regards to the effi  ciency of de-lineating forage mixtures, for the 2- plant mixture the newer method was clearly more effi  cient, with EE of 0.018 compared to that of traditional method of 0.033 (Table 1). Th at represented a 50% improvement in effi  ciency. Th e FD also was better with the new method, although somewhat lower than the expected range. For the 3- plant mixture similar results were obtained although the reduction in EE was smaller, 0.034 and 0.052 for the new and traditional method, respectively. Still the diff erence between the two methods represented a 35% improvement in effi  ciency. In addition, the FD for the new method was close to the range expected, while that for the tradition-al method was well below.For the 5- plant mixtures, the EE were 0.094 and 0.175 for the new and traditional method, respectively; however, FD was considerably reduced for both methods to 0.652 (new) and 0.518 (traditional). A similar result was obtained for the 8- plant mixture, with lower effi  ciencies for both methods: the estimation errors increased substantially and the proportion of times true and estimated values coincided decreased considerably. However, the new method was still around 50% more effi  cient than the traditional. One likely reason for this signifi cant decline in ability to deter-mine diet composition may be insuffi  cient diff erences in the ALK and LCOH profi les among the plants when more and similar species were combined.With this particular set of plant species, delineating relatively simple mixtures (2 or 3 plants) using the new method is quite feasible. However, increasing the number of plants in the mixture dramatically reduced the effi  ciency of the both methods. As shown in Figure 1, the C32OH and C24OH help the least in species delineation, pos-sibly due to many of the plant species not having these two markers present. When evaluating the similarities in plant- waxes profi les for the diff erent plants, C31, C33, C35 and C28OH were common to the cool- 2017 Nebraska Beef Cattle Report · 75 ConclusionIn conclusion, the reliability of predic-tions of diet composition was improved by using a more sophisticated statistical approach in the evaluation. However, fur-ther developments in the application of the plant- wax marker technique are still needed to determine the dietary choices and feed intakes of cattle grazing complex swards typical to western rangelands.Napoleón Vargas Jurado, graduate StudentHannah C. Hamilton, graduate studentRonald M. Lewis, full professor, animal science, Lincolnand warm- season grasses, while C26OH was important to distinguish the legumes. Although the C32OH was less important than many other markers to delineate plant species generally, in was unique to C4 grasses; therefore, it facilitated separating the cool- and warm- season grasses.One possible way to increase the effi  -ciency of the plant- wax methodology, when considering mixtures of more plants, is to add other plant markers such as long- chain fatty acids and alkenes. Additionally, plants could be grouped based on their taxonomy or function to simplify the complexity of the sward being characterized. Such an ap-proach may be particularly valuable when the primary aim is to predict feed intake.

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Delineating Complex Forage Mixtures Using Plant-Wax Markers

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