Abstract

Data on 359 pork carcasses were divided into four groups based on ranges in carcass fatness (average backfat thickness). Independent variables included carcass weight (CW), carcass length (CL), average backfat thickness (ABF), USDA muscling score (MS), fat depth 3/4 the lateral length of the longissimus muscle at the 10th rib (FD), longissimus muscle area at the 10th rib (LMA) and seam fat scores in the blade (SFB) and sirloin (SFS) ends of the loin. Dependent variables were percentage of lean (PCLN) and kilograms (KGLN) of lean in the four lean cuts. Regression equations were computed to identify the best equations containing two or three independent variables for predicting PCLN and KGLN. All measures of fatness wee negatively correlated with both PCLN and KGLN. When only those variables available from the intact carcass (CW, CL, MS, ABF) were used, the best two-variable equations for predicting PCLN included MS and ABF, while the best equation for predicting KGLN included CW and ABF in two of the four fat ranges. R2 values were generally low when only intact carcass measurements were included. When all available variables were included, the best two-variable equation for predicting PCLN was that including LMA and FD. Two-variable equations including CW and FD most accurately predicted KGLN. LMA, FD and SFS combined to give the best three-variable equation for predicting PCLN (coefficient of determination, [CD] = 89.2). The best three-variable equation for predicting KGLN included CW, LMA and FD (CD = 91.8). Findings suggest that the independent variables used in the National Pork Producers Council procedure for estimating muscle in carcasses are the appropriate indices for such estimation across a wide range in fatness of pork carcasses.

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