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Prediction Equations for Estimating Lean and Fat in Meat of Carcasses from Cull Cows^1,2,

Auburn University, AL 36849-5415

Abstract

Prediction equations for estimating lean and fat in meat from sow carcasses were developed from measurements on 104 crossbred sows from three farrowing groups. Fourth-parity Duroc-Landrace, Hampshire-Landrace and Yorkshire-Landrace sows were slaughtered at a processing plant that manufacturers whole-hog sausage using hot-boning procedures. Measurements recorded on each live sow were BW at the plant (WTPLANT), ultrasound fat thickness at the shoulder (US), the last-rib (ULR) and the last lumbar region (ULL) and a subjective body condition score (BCS) (1 = thin; 2 = average; 3 = fat). Carcass measurements were: skin weight including the ears and teats (SKIN); fat thickness measured 5.08 cm off the midline at the first rib (OFR), last rib (OLR), and last lumbar vertebra (OLL); and weight of the ribs (RIBS). Random samples of meat were collected from each carcass and analyzed for moisture and fat percentages; from these, kilograms of fat and the ratio between lean and fat were calculated. The sows averaged 224.7 kg upon arrival at the slaughter facility and meat from their carcasses averaged 26.53% fat in the separable carcass tissue. After accounting for variation associated with breeds and farrowing groups, prediction equations were developed using maximum R² multiple regression procedures. The most efficient equation for estimating fat percentage in meat using measurements from live sows was: Fat = 7.71 + 2.37 (ULR) + 5.29 (ULL) (R² = .713). Using carcass fat measured 5.08 cm off the midline, the prediction equation for fat percentage of meat was: Fat = 9.38 + 2.41 (BCS) + 1.99 (OFR) + 2.37 (OLR) + 2.34 (OLL) (R² = .757).

¹ Contribution from the Alabama Agric. Exp. Sta., Journal Series No. 4-881870P.

² The authors wish to express their appreciation to Gary Shirley, manager of Dean's Sausage Company, Attalla, AL and his employees for slaughtering the sows in this project. A sincere appreciation is extended to William R. Egbert and Ray Johnson for assisting in collection of the data.

³ Dept. of Anim. and Dairy Sci.

⁴ Lower Coastal Plain Substation, Alabama Agric. Exp. Sta.