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Estimation of Carcass Chemical Composition From Wholesale Cut Composition and Certain Carcass Traits of Feedlot Steers^1,2,

University of Arizona, Tucson 85721

Abstract

Data from 261 feedlot steers that varied in genetic background, feeding regimen and management were used to evaluate the chemical composition (lipid, protein and moisture) of the carcass wholesale cuts and carcass traits (USDA quality and yield grade factors) as predictors of carcass chemical composition. After 72 h of chill (3 C), the wholesale cuts (chuck, rib, plate, shank and brisket, loin, round, flank) were removed from the left portion of the carcass and separated into bone and soft tissue. The soft tissue portion was ground and sampled for chemical analysis (lipid, protein and moisture). Prediction equations for carcass lipid, protein and moisture were developed using chemical composition data from each wholesale cut and carcass traits as independent variables. Equations were tested for accuracy of prediction using data from a set of 15 carcasses of known chemical composition. Comparisons of the actual with the predicted value for carcass fat revealed that the equations for all wholesale cuts, with exception of the chuck, gave accurate predictions. For prediction of percentage carcass protein, all wholesale cut equations provided accurate methods of estimation, with the exception of the round. The equations from the chuck and rib produced predicted values that were different (P>.05) from the actual for carcass moisture content. The equations derived for the flank and plate provided predicted values for lipid, protein and moisture that were similar to the actual value. Furthermore, the low economic value of these cuts and their easy accessibility enhance the practical value of this method for accurately estimating carcass composition.

¹ Arizona Agr. Exp. Journal Paper 3585.

² Contributing data to Western Regional Project W-145.

³ Dept. of Anim., Dairy and Vet. Sci., Utah State Univ., Logan.

⁴ Dept. of Agr. Econ., New Mexico State Univ., Las Cruces.