The potential of the composition of the forerib measured by X-ray computed tomography (CT) as a predictor of carcass composition was evaluated using data recorded on 30 Aberdeen Angus and 43 Limousin crossbred heifers and steers. The left sides of the carcasses were split into 20 cuts, which were CT scanned and fully dissected into fat, muscle and bone. Carcass and forerib tissue weights were assessed by dissection and CT. Carcass composition was assessed very accurately by CT scanning of the primal cuts (adj-R250.97 for the three tissues). CT scanning predicted weights of fat, muscle and bone of the forerib with adj-R2 of 0.95, 0.91 and 0.75, respectively. Single regression models with the weights of fat, muscle or bone in the forerib measured by CT as the only predictors to estimate fat, muscle or bone of the left carcass obtained by CT showed adjusted coefficients of determination (adj-R2) of 0.79, 0.60 and 0.52, respectively. By additionally fitting breed and sex, accuracy increased to 0.85, 0.73 and 0.67. Using carcass and forerib weights in addition to the previous predictors improved significantly the prediction accuracy of carcass fat and muscle weights to adj-R2 values of 0.92 and 0.96, respectively, while the highest value for carcass bone weight was 0.77. In general, equations derived using CT data had lower adj-R2 values for bone, but better accuracies for fat and muscle compared to those obtained using dissection. CT scanning could be considered as an alternative very accurate and fast method to assess beef carcass composition that could be very useful for breeding programmes and research studies involving a large number of animals, including the calibration of other indirect methods (e.g. in vivo and carcass video image analysis).
- Carcass composition
- Primal composition
Navajas, EA., Richardson, RI., Fisher, AV., Hyslop, JJ., Ross, DW., Prieto, N., Simm, G., & Roehe, R. (2010). Predicting beef carcass composition using tissue weights of a primal cut assessed by computed tomography. Animal, 4(11), 1810 - 1817. https://doi.org/10.1017/S1751731110001096