Predicting Chemical Composition of Beef Carcasses from Easily Obtainable Carcass Variables

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Abstract
Carcasses from 41 beef animals varying widely in class, grade, weight and finish were physically separated into bone and fat-lean portions. Samples representing the edible portion of the carcass were chemically analyzed for moisture, fat and protein. Regression equations using various carcass measurements were computed for predicting edible carcass composition (EC). Fat thickness was the most important single factor in determining U.S.D.A. yield grade. It also had the highest correlation coefficient of the four yield grade factors with EC composition. Hot carcass weight, although significantly correlated, accounted for only approximately 30% of the variation in EC carcass composition. U.S.D.A. yield grade and carcass specific gravity were highly significantly correlated with EC composition. Correlation coefficients of 0.89, 0.89 and −.74 were computed between YG and EC moisture, fat and protein, respectively for the 41 carcasses. Correlations of 0.92, −.92 and 0.73 were obtained between CSG and carcass moisture, fat and protein, respectively. Copyright © 1973. American Society of Animal Science . Copyright 1973 by American Society of Animal Science.

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