RESUMEN
Data of sixty finished, crossbred lambs were used to develop prediction equations of total weight of retail-ready cuts (SUM). These cuts were the leg, sirloin, loin, rack, shoulder, neck, riblets, shank, and lean trim (85/15). Measurements were taken on live lambs and on both hot and cold carcasses. A four-terminal bioelectrical impedance analyzer (BIA) was used to measure resistance (Rs, ohms) and reactance (Xc, ohms). Distances between detector terminals (L, centimeters) were recorded. Carcass temperatures (T, degrees C) at time of BIA readings were also recorded. The equation predicting SUM from cold carcass measurements (n = 53, R2 = .97) was .093 + .621 x weight-.0219 x Rs + .0248 x Xc + .182 x L-.338 x T. Resistance accounted for variability in SUM over and above weight and L (P = .0016). The above equation was used to rank cold carcasses in descending order of predicted SUM. An analogous ranking was obtained from a prediction equation that used weight only (R2 = .88). These rankings were divided into five categories: top 25%, middle 50%, bottom 25%, top 50%, and bottom 50%. Within-category differences in average fat cover, yield grade, and SUM as a percentage of cold carcass weight of carcasses not placed in the same category by both prediction equations were quantified with independent t-tests. These differences were statistically significant for all categories except middle 50%. This shows that BIA located those lambs that could more efficiently contribute to SUM because a higher portion of their weight was lean.