Increasing feed efficiency in beef cattle is critical for meeting the growing global demand for beef while managing rising feed costs and environmental impacts. Challenges in recording feed intake and combining genomic and nutritional models hinder improvements in feed efficiency for sustainable beef production. This review examines the progression from traditional data collection methods to modern genetic and nutritional approaches that enhance feed efficiency. We first discuss the technological advancements that allow precise measurement of individual feed intake and efficiency, providing valuable insights for research and industry. The role of genomic selection in identifying and breeding feed-efficient animals is then explored, emphasizing the benefits of combining data from multiple populations to enhance genomic prediction accuracy. Additionally, the paper highlights the importance of nutritional models that could be used synergistically with genomic selection. Together, these tools allow for optimized feed management in diverse production systems. Combining these approaches also provides a roadmap for reducing input costs and promoting a more sustainable beef industry.

Increasing feed efficiency in beef cattle is critical for meeting the growing global demand for beef while managing rising feed costs and environmental impacts. This review examines the progression from traditional data collection methods to modern genetic and nutritional approaches that enhance feed efficiency. We first discuss the technological advancements that allow precise measurement of individual feed intake and efficiency, providing valuable insights for research and industry. The role of genomic selection in identifying and breeding feed-efficient animals is then explored, emphasizing the benefits of integrating multi-population data to improve prediction accuracy. Additionally, the paper highlights the importance of nutritional models that could be used synergistically with genomic selection, allowing for optimized feed management in diverse production systems. Combining these approaches provides a roadmap for reducing input costs and promoting a more sustainable beef industry.

The 8th revised edition of the Nutrient Requirements of Beef Cattle was released in 2016, with the recommendations provided in the publication being used extensively in both research and production settings. In the context of research needs identified in that publication, our objective was to review research on beef cattle nutrient requirements published since 2016 and identify knowledge gaps that should be addressed. Relative to energy requirements, the effects of environmental temperature and grazing activity, along with stress and disease, on maintenance requirements are inadequately characterized or defined. In addition, relationships between retained energy and protein should be more fully elucidated, and additional guidance on body weight at a target compositional endpoint is needed. Areas of continuing concern include accurately and precisely predicting microbial protein supply, predicting N recycling, and the metabolizable protein requirements for maintenance. Mineral and vitamin requirements are often challenging because of a lack of consistency in models used to determine requirements and potential effects of unique production settings on requirements. Based on recent research with feedlot cattle, zinc and chromium requirements should be examined more closely. Because predictions of dry matter intake are critical to supplying nutrients, additional development of prediction equations is needed, especially for beef cows and grazing beef cattle in general. Given considerable research in prediction of greenhouse gases, reevaluation of 2016 recommendations is warranted, along with a need for the updating of equations to predict excretions of N and P. Composition of feeds, particularly byproducts from ethanol production or other industrial streams, represents a knowledge gap, with obtaining reliable energy values of these feeds being a notable challenge. Nutritional models provide the means to integrate nutrient requirement recommendations into practice, and moving towards mechanistic models that take advantage of artificial intelligence and precision livestock farming technologies will be critical to developing future modeling systems.

To remain competitive in the industry, beef and dairy producers in the Midwest need to adapt to the use of alternative feeds and take advantage of the expected abundance and favorable pricing of biofuel coproducts. Integrating the coproducts as feed ingredients could make the livestock industry significantly more attractive and competitive in domestic and global markets. A survey instrument was created to inventory resources that currently limit (or enable) the use of biofuel coproducts by small and medium-sized beef and dairy producers in the state of Indiana. Seventy-eight of Indiana's 92 counties were represented in the survey results.