Development of an equation to predict net protein requirements for the growth of Zebu beef cattle

• Published in: Animal (Cambridge, England) England), 2020-05, Vol.14 (5), p.963-972
• Main Authors: Costa E Silva, L F, Filho, S de Campos Valadares, Del Bianco Benedeti, P, Detmann, E, Menezes, A C Baião, Silva, T Eder, de Sales Silva, F A
• Format: Article
• Language: English
• Subjects: Agricultural research; Animals; Beef; Beef cattle; Body composition; Cattle; Correlation coefficient; Correlation coefficients; diet formulation; Economics; Energy; Environmental impact; Equivalence; Estimates; Experiments; Livestock; Meta-analysis; modeling; Nellore; Nutrient requirements; Nutrients; Profitability; Proteins; Regression analysis; Regression models
• ISSN: 1751-7311; 1751-732X
• DOI: 10.1017/S1751731119002684

The accurate estimation of protein requirements for beef cattle is a key factor in increasing livestock profitability and decreasing the environmental impacts of excessive N excretion due to mismatching between assumed requirements and diet formulation. A meta-analysis was conducted to evaluate and validate a new equation to predict the net protein requirements for growth (NPg) of Zebu beef cattle. For the development of the new approach, a database of 552 observations comprised of bulls, steers, and heifers of different genetic groups (Zebu, beef crossbreed, and dairy crossbreed) was assembled. The new approach was evaluated and compared to current models devised by the international nutrient requirements system committees (Agricultural Research Council, 1980; Beef Cattle Nutrient Requirements Model, 2016; BR-CORTE, 2016) to predict NPg. The model evaluation was performed through the model evaluation system (version 3.1.16) using an independent data set (n = 177 observations). An equation was considered the best estimator of NPg if the following conditions were met: (1) the intercept and slope of the regression between ordinary residues and/or predicted NPg values must have been equal to zero and one, respectively; and (2) the greatest concordance correlation coefficient (CCC) and determination coefficient (R), and lowest mean squared error of prediction (MSEP) were attained. Based on the regression models of the observed v. predicted NPg of Zebu beef cattle, both the new approach and that of the ARC (1980) correctly estimated NPg, since the intercept and slope were not different (P > 0.05) from zero and one, respectively. Additionally, the new approach's determination coefficient was the greatest and the closest to one. The fact that the new model achieved a higher CCC and lower MSEP than the existing models indicated its superior reproducibility and accuracy. The equations proposed by BR-CORTE (2016) and the BCNRM (2016) did not correctly estimate NPg in that the intercept and slope were different (P < 0.01) from zero and one, respectively. Thus, the equations proposed by the new approach and the ARC (1980) accurately and precisely estimated NPg and are recommended for Zebu cattle. Furthermore, the inclusion of equivalent empty BW (EQEBW) in the new approach improves the estimation of NPg. We suggest the use of the following equation to calculate NPg for Zebu beef cattle: NPg = 176.01 × EBG - 0.381 × EQEBW0.75 × EBG1.035 (R = 0.80 and CCC = 0.75); where