Genetic Prediction for Cow Maintenance Energy Requirements

Beef cattle are biologically less efficient than other species such as pork and poultry, and they require higher dietary energy intake in comparison to these other meat animal species. However, because they are ruminants, they can consume and utilize forages that monogastrics are unable to digest. It is important, therefore, to select and produce cattle that will convert these forage resources to high-quality protein.

To raise profitable cattle, it is important to reduce feed expenses in order to increase revenue. Research has shown that approximately 70% of a cow’s feed expenses go toward her maintenance energy requirements.

John Evans, Oklahoma State University animal scientist, told attendees of the 34th annual meeting of the Beef Improvement Federation (BIF) that his research has shown maintenance energy requirements to be a heritable trait, with differences across breeds.

Because of its direct effect on the profitability to the cow-calf enterprise, Evans suggested the development of an expected progeny difference (EPD) to predict the difference in feed energy requirements of mature cows. 

Studies completed at Colorado State University and the USDA-ARC Fort Keogh Laboratory, Miles City, Mont., included mature weights and milk expected progeny differences (EPDs) in their equations to predict maintenance requirements. These two traits were used, Evans explained, because mature weight and weaning weight data was readily available, and the milk EPD adequately represents the differences in actual milk yield. The genetic merit of an individual for higher or lower milk production would affect their prediction for cow maintenance energy requirements. Consequently, animals that have the same mature size, but different levels of milk production would have different maintenance requirements. 

Evans said the benefits of a maintenance energy requirement EPD include improving the selection of animals that are more feed efficient, improving the selection of animals for certain production environments, and getting a straightforward value estimation, which can be especially useful in years with poor feed conditions.
— by Stephanie Veldman