PREDICTION OF SLAUGHTER COW COMPOSITION USING LIVE ANIMAL AND CARCASSTRAITS

Slaughter cows (n = 120), representing four genotypes (British, contin ental, Bos indicus, and dairy) and three body condition classes (thin, moderate, and fat), n = 10 per subclass, were used to identify practi cal and accurate prediction equations for the yield of boneless manufa cturing beef of specific fat percentages. Cows and their carcasses wer e weighed and evaluated for USDA yield and quality grade factors and f or physical muscle and fat indicators. Carcass sides were fabricated; total fat percentage (TFP) was calculated as total fat (trimmed and ch emical) divided by side weight, and tissue lean percentage (TLP) wa ca lculated as boneless fat-free lean divided by soft tissue weight. Data were analyzed using maximum R-2 multiple regression. The best live tr ait prediction model for TFP included live preliminary yield grade (LP YG), body condition score (LCOND), visual live muscle score (LMUSC), a nd live weight (LWT), R-2 = .83. The best carcass trait TFP prediction model included adjusted preliminary yield grade (CPYGA); kidney, pelv ic, and heart fat adjustment (CKPHADJ); marbling score (CMARB); and ho t carcass weight (HCW), R-2 = .92. The best live trait TLP prediction model included LPYG, LCOND, LMUSC, and LWT, R-2 = .82. The best carcas s trait TLP prediction model included CPYGA, CKPHADJ, CMARB, and lean maturity, R-2 = .91. These data indicate that TFP and TLP of slaughter cows can be accurately and practically predicted using live animal an d carcass traits.