Impact of Measurement Errors on Predicting Pork Carcass Composition: Within Sample Evaluation

Purdue University 2000 Swine Research Report. Regression equations for estimating fat-free lean mass are widely used in the pork industry to predict carcass composition, carcass value and nutrient requirements. These prediction equations are used to evaluate the differences between pigs of different genetic populations, sexes and experimental treatments. However, most prediction equations currently in use have not been evaluated for the extent to which they account for genetic population and sex differences. Two opinions exist to the best method to develop prediction equations. One opinion is that in the development of the prediction equations, carcass measurements should be collected by a commercial pork processor. The optical probe or carcass ultrasound measurements should be taken under the same conditions as the prediction equations are to be used. The second opinion, based on statistical theory, is that the carcass measurements should be taken carefully in a laboratory setting to minimize measurement errors. The objective of this study was to use simulation to examine the impact of measurement errors on the ability of commonly used prediction equations to accurately predict genetic population and sex differences in fat-free lean mass.