Carcass traits have been successfully used to determine body composition of steers. Body composition, in turn, has been used to predict energy content of ADG to compute feed requirements of individual animals fed in groups. This information is used in the Cornell value discovery system (CVDS) to predict DM required (DMR) for the observed animal performance. In this experiment, the prediction of individual DMR for the observed performance of group-fed yearling bulls was evaluated using energy content of gain, which was based on ultrasound measurements to estimate carcass traits and energy content of ADG. One hundred eighteen spring-born purebred and crossbred bulls (BW = 288 +/- 4.3 kg) were sorted visually into 3 marketing groups based on estimated days to reach USDA low Choice quality grade. The bulls were fed a common high-concentrate diet in 12 slatted-floor pens (9 to 10 head/pen). Ultrasound measurements including back-fat (uBF), rump fat, LM area (uLMA), and intramuscular fat were taken at approximately 1 yr of age. Carcass measurements including HCW, backfat over the 12th to 13th rib (BF), marbling score (MRB), and LM area (LMA) were collected for comparison with ultrasound data for predicting carcass composition. The 9th to 11th-rib section was removed and dissected into soft tissue and bone for determination of chemical composition, which was used to predict carcass fat and empty body fat (EBF). The predicted EBF averaged 23.7 +/- 4.0%. Multiple regression analysis indicated that carcass traits explained 72% of the variation in predicted EBF (EBF = 16.0583 + 5.6352 x BF + 0.01781 x HCW + 1.0486 x MRB - 0.1239 x LMA). Because carcass traits are not available on bulls intended for use as herd sires, another equation using predicted HCW (pHCW) and ultrasound measurements was developed (EBF = 39.9535 x uBF - 0.1384 x uLMA + 0.0867 x pHCW - 0.0897 x uBF x pHCW - 1.3690). This equation accounted for 62% of the variation in EBF. The use of an equation to predict EBF developed with steer composition data overpredicted the EBF predicted in these experiments (28.7 vs. 23.7%, respectively). In a validation study with 37 individually fed bulls, the use of the ultrasound-based equation in the CVDS to predict energy content of gain accounted for 60% of the variation in the observed efficiency of gain, with 1.5% bias, and identified 3 of the 4 most efficient bulls.
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