AI Summary & Key Takeaways
AI InsightHowever, for greater accuracy, joint dissection and various carcass characteristics and measurements should be combined.
📌 3 Key Takeaways
Abstract
The aim of the study was to test the possibility of using carcass measurements and joint tissue composition to predict the half-carcass tissue composition of lambs more accurately. With this purpose in mind, 6 different carcass joints (neck, flank, shoulder, ribs, hind limb, and tail) from 42 Kıvırcık male lambs were dissected. In addition, various carcass characteristics were recorded. When carcass characteristics and measurements were used alone in the prediction equations, accuracy (between 37%–68%) was similar to the equations that included only joint dissections (36%–75%). However, when joint dissection and various carcass traits were combined, half-carcass tissue composition was predicted more accurately (65%–90%) than in measures using either joint dissection or various carcass traits alone. Flank was the most successful predictive joint for prediction of muscle weight, when combined with some carcass traits, while the equation built with hind limb and various carcass traits was most successful for predicting total fat weight. Carcass traits yielded accuracy that was similar to joint dissection results, especially for muscle and total fat weights. Therefore, for these parameters, carcass traits are preferred as this measure is cost-effective, noninvasive, and practical. However, for greater accuracy, joint dissection and various carcass characteristics and measurements should be combined.