Recent advances in estimating protein and energy requirements of ruminants

Authors: TEDESCHI, LUIS - Texas A&M University; GALYEAN, MICHAEL - Texas Tech University; Hales Paxton, Kristin

Submitted to: Animal Production Science
Publication Type: Peer Reviewed Journal
Publication Acceptance Date: 7/18/2017
Publication Date: 8/18/2017
Publication URL: http://handle.nal.usda.gov/10113/5808390
Citation: Tedeschi, L.O., Galyean, M.L., Hales, K.E. 2017. Recent advances in estimating protein and energy requirements of ruminants. Animal Production Science. 57:2237-2249. https://doi.org/10.1017/AN17341.

Interpretive Summary: Considerable efforts have been made in gathering scientific data and developing feeding systems for ruminant animals in the last 50 years. Future endeavours should target the assessment, interpretation, and integration of the accumulated knowledge in developing nutrition models. Nutrition models must change faster to follow the pace of a rapidly evolving planet. We highlight some of the areas that need improvement. A fixed metabolisable-to-digestible energy ratio is an oversimplification and it does not represent the diversity of the existing feedstock, but at the same time, we must guarantee internal consistency and dependency of the energy system. For grazing animals, although data exist to compute energy expenditure of walking in different terrains, nutrition models must incorporate the main factors that control grazing. New equations have been developed to predict the microbial crude protein, but efforts must be made to account for the diversity of the rumen microbiome. Despite the data and knowledge of partitioning of retained energy into fat and protein, the prediction of retained protein remains unsatisfactory, and the prediction is worsened when literature data for efficiency of use of amino acid are employed. The integrative manner used in developing empirical-mechanistic nutrition models has forced submodels to be interconnected, and changing submodels independently can potentially destabilize the predictability of the model.

Technical Abstract: Considerable efforts have been made in gathering scientific data and developing feeding systems for ruminant animals in the last 50 years. Future endeavours should target the assessment, interpretation, and integration of the accumulated knowledge to develop nutrition models in a holistic and pragmatic manner. We highlight some of the areas that need improvement. A fixed metabolisable-to-digestible energy ratio is an oversimplification and does not represent the diversity of the existing feedstock, but at the same time, we must ensure the internal consistency and dependency of the energy system in models. For grazing animals, although data exist to compute energy expenditure associated with walking in different terrains, nutrition models must incorporate the main factors that initiate and control grazing. New equations have been developed to predict the microbial crude protein (MCP), but efforts must be made to account for the diversity of the rumen microbiome. There is a large unexplained variation in the efficiency of MCP synthesis (9.81-16.3 g MCP/100 g of fermentable organic matter). Given the uncertainties in the determination MCP, current estimates of metabolisable protein required for maintenance are biased. The use of empirical equations to predict MCP, which, in turn, are used to estimate metabolisable protein intake, is risky because it establishes a dependency between these estimates and creates a specificity that is not appropriate for mechanistic systems. Despite the existence of data and knowledge of partitioning of retained energy into fat and protein, the prediction of retained protein remains unsatisfactory, and is even less accurate when reported data for efficiency of use of amino acid are employed in the predictive equations. The integrative approach to develop empirical mechanistic nutrition models has introduced interconnected submodels, which can destabilize the predictability of the model if changed independently.