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Prediction of Future Carcass Traits in Stocker Cattle at the Conclusion of Grazing
Institution:2. Agricultural Research and Extension Center, Texas A&M University, Overton 75684-0200;3. Dale Bumpers Small Farms Research Center, USDA-ARS, Booneville, AR 72927;1. Department of Animal and Food Sciences, Oklahoma State University, Stillwater 74078;;2. Conservation and Production Research Laboratory, USDA-ARS, Bushland, TX 79012;;3. Livestock and Forestry Research Station, Division of Agriculture, University of Arkansas, Batesville 72501; and;4. Department of Animal Science, Division of Agriculture, University of Arkansas, Fayetteville 72701
Abstract:Prediction of eventual carcass traits in stocker cattle at the conclusion of grazing could be useful for culling, co-mingling of animals, feedlot pen assignments, and making management decisions in the feedyard. Ultrasound measures of 12th to 13th rib longissimus area (ULA) and fat thickness (UFAT), and off-pasture BW (OPBW) were collected from yearling cattle (n = 261) at the conclusion of grazing in two experiments that evaluated stocking rate and grazing management effects on rye (Secale cereale L.) annual ryegrass (Lolium multiflorum Lam.) pastures. Carcasss data were subsequently recorded at harvest following feedyard finishing to a visual 1-cm backfat. Correlations were analyzed to determine relationships between carcass traits and ULMA, UFAT, body condition measure (BCM), and OPBW. Ultrasound measures, breed type (BRDT; n = 4), gender (steers and heifers), and feedlot days on feed (DOF) were evaluated in multiple regression models to determine whether these variables influence eventual carcass percentage retail product, kilograms retail product (KRP), hot carcass weight (HCW), and marbling score. Ultrasound FAT and BCM were negatively correlated with percentage retail product, KRP, and HCW and were positively correlated with marbling score. All reduced regression models had R2 values of between 0.15 and 0.63, and models with inputs of UFAT and OPBW consistently had the numerically greatest R2 values and least RMSE. Multiple regression analyses indicated that prediction of carcass traits from stocker cattle ultrasonic measurements at the conclusion of grazing were possible, but improvement in the models will be necessary to reduce error and improve reliability.
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