Prediction of tissue composition of live dairy calves and carcasses by computed tomography

Computed tomography (CT) is a non-destructive technique, based on X-rays, that has been used in several livestock species to evaluate carcass composition. The objective of this study was construct predictive equations estimate and viscera composition for preweaning calves using CT. For purpose, 24 Holstein male (4 ± 0.9 d age; 40 2.2 kg body weight) were fed milk replacer (MR; 23% CP; 15% fat) either 4 L/d or 8 MR at the rate 125 g/L water ensure different levels fat protein accretion generate sufficient variation obtain calibration. Then, 30 2.4 age, 3 from each feeding program, 50 1.9 9 program CT-scanned, humanly sacrificed. Carcasses also CT scanned h post mortem. Images analysed predict content carcasses, red white viscera. models rendered residual deviation between 1.1 (protein viscera) 2.6 (fat live animal images (carcass moisture) 4.5 images. root mean square error prediction relative ranged 1.32 17.3% 1.38 17.3 coefficient determination 0.19 0.88 0.26 protein) 0.98 In conclusion, it possible technique by means computed could be studies estimation would relevant.