Development of a procedure to reproduce the variances and relationships among carcass measurements and the weight of primal and subprimal lean cuts

Abstract

<h2>ABSTRACT</h2> Barrows (n = 2,178) and gilts (n = 2,274) were fed either high-energy or low-energy diets from 27 kg of BW to target BW of 118, 127, 131.5, and 140.6 kg over 12 monthly replicates. Carcass primal cut and subprimal cut weights as well as optical probe backfat and loin depth measurements were collected on each pig. The cut weights and carcass measurements for each pig were fitted to allometric functions (Y = A · CW^B) of carcass weight (CW), where A is a scalar parameter and B is the allometric coefficient. The final models were weight or measurement=random effect of replicate + (1 + b_DD) · (A · CW^B) + error, where b_D is the regression coefficient, D (diet) = −0.5 for the low-energy and 0.5 for high-energy diets, and A and B are sire line–sex specific parameters. Linear regressions of backfat and loin depth residuals from the model were included at P < 0.05 to the cut weight equations but had little effect to reduce the residual variance. The residuals among the primal and subprimal cuts were correlated, and a Cholesky decomposition procedure was used on the variance–covariance matrix of the residuals. By using these procedures, a stochastic model can be used to evaluate the effect of alternative management, marketing, and carcass sorting strategies on the mean and distribution of pork primal and subprimal cut weights to increase pork processor profitability.