Evaluation of predictive models of carcass tissue composition in Black Belly sheep

This study aimed to evaluate the adequacy of predictive models of carcass tissue composition in Black Belly sheep using an independent database of sixteen male sheep aged six months and weighing 31.99±2.38 kg. The animals were slaughtered, and the carcasses were refrigerated at 1°C for a 24-hour period. The carcass was then split along the dorsal midline and 9–11 rib section was removed from the left half. The remainder of the left half of the carcass was dissected into muscle (TCM), fat (TFC) and bone (TCB), and the weight of each component was adjusted to account for the total carcass weight. Regression analysis showed that the intercept (β₀) differed from 0 in all models (P > 0.05). However, the slope (β1) did not differ from 1 (P > 0.05). All models showed moderate to high precision (0.59 ≤ r² ≤ 0.82). The TMC and TCB models were highly accurate (bias correction factor: 0.94 ≤ Cb ≤ 0.99) and moderately to highly reproducible (0.76 ≤ CCC ≤ 0.90). In contrast, the TCF model had low Cb and CCC values. These results suggest that the TCM and TCB models could be used to predict muscle and bone content in Black Belly sheep with moderate precision and very high accuracy.