A cull sow carcass lean mass prediction equation using hot carcass weight and backfat depth could be used by processors to improve the efficiency of brat and sausage production and the development of other products.

One of the objectives of a study at Iowa State University was to examine the actual weight and percentage of lean and fat from each primal cut and cull sow weight category commonly used by processors. USDA cull sow live weight categories are: Class 1 – 300 to 450 lb.; Class 2 – 451 to 500 lb.; Class 3 – 501 to 550 lb.; and Class 4 – 551 lb. and heavier.

Sows were purchased from the four weight categories or a mix of the categories that resulted in the best lean-to-fat ratio required to produce the desired processed pork products.

Prior to harvest, sows were weighed and ultrasound backfat and loin muscle estimates were obtained. At slaughter, sows were bled and eviscerated, and the carcass split into equal halves. One half was weighed and divided into primal cuts, including loin, belly, ham, shoulder and ribs. Primal cuts were then divided into knife-separable bone, lean, fat and skin tissue components. These individual components were weighed and percentages of primal, carcass and live weight calculated. This information was used to determine the lean and fat percentage by primal cut within each of the four USDA cull sow live-weight classes. Data was collected on 212 cull sows.

Differences among the lean, fat, skin and bone weight from sows in different weight categories were observed. The percent lean and fat by carcass and total body weight for each of the primal cuts by weight class were calculated.

There were percent lean and percent fat differences when each primal was evaluated across USDA cull sow weight category. However, the percent lean and percent fat expected for market weight classes MWC 1 and 2 were not significantly different for each primal cut (Table 1 [3]), and the same was true for MWC 3 and MWC 4. Therefore, the carcass lean mass prediction equations were divided into two categories — one from USDA cull sow weight Classes 1 and 2, another for Classes 3 and 4.

In general, the two lighter market-weight classes had a higher percent lean and lower percent fat than the two heavier weight classes. Typically, processors do not purchase sows from all four USDA classes, instead buying either thin sows or heavy sows.

Equations predicting carcass lean mass were developed within each USDA cull sow weight class and across classes (ignoring USDA class). Models utilized backfat, hot carcass weight and loin muscle area measured ultrasonically on live animals and manually on carcasses. It appeared that either the ultrasonic values or the carcass measures could be used to develop lean mass prediction equations for cull sow carcasses and arrive at similar endpoints.

Hot carcass weight and backfat were the two best variables for predicting carcass lean content. Based on these results, pounds of lean can be predicted using the equation: 23.20 + 0.60 (HCW) – 44.51 (BF), where HCW is the hot carcass weight in pounds and BF is ultrasonic backfat depth measured in inches. From this prediction, the expected percent lean on the carcass can be calculated by dividing pounds of lean by HCW.

The information gathered in this study could be used by processors to better identify cull sows that are more likely to have appropriate lean-to-fat ratios, from individual primal or from entire carcasses, to more closely meet the lean-to-fat ratios of food products they manufacture (brats, sausage, etc.).

In this study, hot carcass weight and backfat are the drivers to predict lean mass. In practice, measuring loin muscle area at line processing speeds would likely be impractical and cost-prohibitive. Therefore, the choice would be to implement a cull sow carcass lean mass equation using only hot carcass weight and backfat. This equation would accurately predict the variation in carcass lean content.

Researchers: Caitlyn Abell and Ken Stalder, Iowa State University. For more information, contact Abell by e-mail, [email protected]; or Stalder by phone at (515) 294-4683 or e-mail [email protected] [4].