TY - JOUR
T1 - Predicting forage intake in extensive grazing systems
AU - Galyean, M. L.
AU - Gunter, S. A.
N1 - Publisher Copyright:
© 2016 American Society of Animal Science. All rights reserved.
PY - 2016/11
Y1 - 2016/11
N2 - Voluntary intake by cattle and other ruminants is controlled by a complex mix of physical and physiological factors that interact with a variety of environmental, geo-spatial, and experiential influences external to the animal. These factors are intensified in grazing ruminants, where selective grazing and potential variability in dietary options also affect eating decisions. As a result of the complexity of intake control and associated interacting factors, developing methods that yield accurate and precise predictions of voluntary intake by grazing cattle has been a long-standing challenge for animal scientists. Nonetheless, reliable estimates of intake are necessary to make informed management decisions related to sustainable management of grazing lands and to provide economically sustainable quantities of supplemental nutrients to maintain desired production levels. Currently available empirical regression equations to predict intake include independent variables like BW and energy concentration (or digestibility). Adding production variables (e.g., ADG for growing cattle or calf ADG/weaning weight for cows) seems to improve the accuracy and precision of these regression models, but to be applied in practice, these production variables must be estimated from historical data, which adds another source of variation and could decrease the predictive ability of these equations. Similarly, intake can be predicted from estimates of energy requirements and energy concentration of the diet selected (the DMI required approach), but this method also involves forecasting of requirements. For all empirical methods, estimates of forage digestibility or energy concentration are essential, but obtaining accurate estimates is difficult with grazing livestock. More complex mechanistic or quasi-mechanistic models have been developed, but the application of these models has been too limited to determine whether they offer significant advantages over traditional empirical models. Because our knowledge base of how, in a quantitative sense, both intake control mechanisms and external factors influence voluntary intake by grazing ruminants is limited, development of tools for predicting intake is likely to be a long-term process.
AB - Voluntary intake by cattle and other ruminants is controlled by a complex mix of physical and physiological factors that interact with a variety of environmental, geo-spatial, and experiential influences external to the animal. These factors are intensified in grazing ruminants, where selective grazing and potential variability in dietary options also affect eating decisions. As a result of the complexity of intake control and associated interacting factors, developing methods that yield accurate and precise predictions of voluntary intake by grazing cattle has been a long-standing challenge for animal scientists. Nonetheless, reliable estimates of intake are necessary to make informed management decisions related to sustainable management of grazing lands and to provide economically sustainable quantities of supplemental nutrients to maintain desired production levels. Currently available empirical regression equations to predict intake include independent variables like BW and energy concentration (or digestibility). Adding production variables (e.g., ADG for growing cattle or calf ADG/weaning weight for cows) seems to improve the accuracy and precision of these regression models, but to be applied in practice, these production variables must be estimated from historical data, which adds another source of variation and could decrease the predictive ability of these equations. Similarly, intake can be predicted from estimates of energy requirements and energy concentration of the diet selected (the DMI required approach), but this method also involves forecasting of requirements. For all empirical methods, estimates of forage digestibility or energy concentration are essential, but obtaining accurate estimates is difficult with grazing livestock. More complex mechanistic or quasi-mechanistic models have been developed, but the application of these models has been too limited to determine whether they offer significant advantages over traditional empirical models. Because our knowledge base of how, in a quantitative sense, both intake control mechanisms and external factors influence voluntary intake by grazing ruminants is limited, development of tools for predicting intake is likely to be a long-term process.
KW - Cattle
KW - Empirical models
KW - Forages
KW - Grazing
KW - Voluntary intake
UR - http://www.scopus.com/inward/record.url?scp=84994841541&partnerID=8YFLogxK
U2 - 10.2527/jas.2016-0523
DO - 10.2527/jas.2016-0523
M3 - Article
AN - SCOPUS:84994841541
SN - 0021-8812
VL - 94
SP - 26
EP - 43
JO - Journal of animal science
JF - Journal of animal science
ER -