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Ovine Carcass Cutability

Texas A&M University,² College Station

Abstract

Closely trimmed primal cuts from 577 carcasses were utilized for the development of multiple regression equations for use under varying conditions of feasibility. Eighteen equations were selected to achieve maximum accuracy for prescribed data collection conditions. Simple correlation coefficients of approximately –.74 and –.85 between measures of internal fat deposition and fat thickness over the l. dorsi, respectively, evidenced the profound influence of excessive fatness on percent of lean primal cuts. Attempts to predict trimmed primal cuts weight without the inclusion of carcass weight as an independent variable were unsuccessful. l. dorsi area contributed little to prediction equations unless body wall thickness (singly or combined) was used as the fatness index. The most accurate equations for predicting either percent or weight of trimmed primal cuts consisted of measures of carcass weight, internal fat, total fat thickness and l. dorsi area. However, subsets of independent variables including carcass weight, estimated percent of internal fat, body wall thickness and fat cover score did not require that the carcass be ribbed yet were nearly as accurate. Equations for predicting weight of trimmed cuts have higher coefficients of determination than those predicting percent, but their reliability outside the parent population is subject to question. In general, equations employing carcass weight, internal fat weight or percent and fat thickness measurements, where the latter two traits are either measured or estimated, can be expected to predict weight or percent of lean primal cuts with greater than 80% accuracy. A comparison of equations for the prediction of percent lean primal cuts indicates that those of Johnston et al. (1967), U.S.D.A. (1969) and Field and Riley (1968) most accurately related the differences inherent to the population of lamb carcasses used in the present study.

¹ Present address: Washington State University, Pullman.

² Department of Animal Science, Texas Agricultural Experiment Station.