Development and evaluation of models to estimate body chemical composition of young Nellore bulls


ABSTRACT The objective of this study was to develop accurate regression equations to predict body composition of Nellore cattle using chemical composition of the 9th, 10th, and 11th ribs and to evaluate the models proposed by analyzing mean and linear bias. Sixty-seven Nellore bulls were slaughtered and slaughter body weight (SBW), hot carcass weight (HCW), and 9th-, 10th-, and 11th-rib-cut weight (RCW) were measured. Empty body composition was obtained after grinding, homogenizing, sampling, chemical analysis, and pooling (blood, skin, head + feet, viscera, and carcass). Chemical components were determined in rib cut, carcass, and empty body: protein (RCP, HCP, and EBP), fat (RCF, HCF, and EBF), ash (RCA, HCA, and EBA), and water (RCWt, HCWt, and EBWt). Stepwise options were used to determine variables to be included and excluded from regressions. Predictive ability of equations was verified using standard error of prediction, coefficient of determination, and Cp statistic. Regression estimates were tested to evaluate the models in a database different from that used for equation development. The best equations found to predict carcass components, in kg, were: HCF = -0.994 + 0.123 × SBW - 9.201 × RCW + 34.249 × RCF (R² = 0.86) and HCWt = 2.733 - 0.172 × SBW + 0.821 × HCW - 23.939 × RCF + 12.186 × RCWt (R² = 0.96). For empty body, the best equations, in kg, were: EBF = -1.4 + 0.166 × SBW - 10.073 × RCW + 40.202 × RCF (R² = 0.90) and EBWt = 3.524 + 0.272 × SBW + 0.373 × HCW - 11.727 × RCW + 31.079 × RCWt (R² = 0.98). Body weight has a high predictive power and should be included in equations to estimate body composition of Nellore cattle. Unbiased models are valid as an indirect method for determining body composition in beef cattle.



beef cattle, feedlot, indirect determination