Based on principles of the California Net Energy System, the dry matter intake (DMI) by feedlot cattle can be subdivided into DMI required for maintenance and DMI required for gain. Thus, if DMI along with body weight at a compositional endpoint and shrunk weight gain are known, dietary concentrations of net energy for maintenance and gain (NEm and NEg, respectively) can be calculated from growth performance data. Close agreement between growth performance-predicted and tabular NEm and NEg values implies the system can be used to accurately predict growth performance and be used to evaluate marketing and management decisions. We used 747 pen means from 21 research studies conducted at Texas Tech University and South Dakota State University to assess the agreement between growth performance-predicted NEm and NEg values and those calculated from tabular energy values for feeds reported by the 2016 National Academies of Science, Engineering, and Medicine publication on beef cattle nutrient requirements. Regression of growth performance-predicted values on tabular values with adjustment for random effects of study indicated that the intercepts of the two regressions did not differ from zero, and the slopes did not differ from one. Residuals (tabular minus growth performance-predicted values) for NEm and NEg averaged -0.003 and -0.005, respectively. Nonetheless, the precision of growth performance-predicted values was low, with approximately 40.3% of performance-predicted NEm values and 30.9% of NEg values falling within 2.5% of the corresponding tabular value. Residuals for NEm were divided into quintiles to evaluate dietary, growth performance, carcass, and energetics variables that might help explain lack of precision in growth performance-predicted values. Among the variables considered, gain:feed ratio was the most discriminating, with differences (P < 0.05) among each of the quintiles. Despite these differences, however, gain:feed ratio did not explain important percentages of variation in components of growth performance-predicted NEm values like maintenance energy requirements (r2 = 0.112) and retained energy (r2 = 0.003). Further research with large datasets that include dietary composition, growth performance and carcass data, and environmental variables, along with fundamental research on maintenance requirements and energy retention, will be required to identify ways to improve the precision of growth performance-predicted NE values.

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http://www.ncbi.nlm.nih.gov/pmc/articles/PMC10355367PMC
http://dx.doi.org/10.1093/jas/skad230DOI Listing

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