Prediction of the Carcass Value of Young Holstein-Friesian Bulls Based on Live Body Measurements

Paulina Pogorzelska-Przybyłek 1 , Zenon Nogalski 1 , Zofia Wielgosz-Groth 1 , Rafał Winarski 2 , Monika Sobczuk-Szul 1 , Patrycja Łapińska 1  and Cezary Purwin 3
  • 1 Department of Cattle Breeding and Milk Quality Evaluation University of Warmia and Mazury in Olsztyn, Oczapowskiego 5, 10-719 Olsztyn, Poland
  • 2 Department of Commodity Science of Animal Raw Materials University of Warmia and Mazury in Olsztyn, Oczapowskiego 5, 10-719 Olsztyn, Poland
  • 3 Department of Animal Nutrition and Feed Management University of Warmia and Mazury in Olsztyn, Oczapowskiego 5, 10-719 Olsztyn, Poland


The aim of this study was to determine the suitability of ultrasound and zoometric measurements and visual muscle scoring for predicting the carcass value of 167 young Holstein-Friesian (HF) bulls. Zoometric and ultrasound measurements were performed and live muscle scoring was estimated before slaughter. After slaughter, hot carcass weight (HCW) was determined and carcasses were assigned to conformation and fat classes according to the EUROP system. Multiple regression equations were derived to estimate the weight, conformation and fatness of carcasses. HCW was estimated using the following equations: Ŷ = 1.507x1 + 1.103x2 + 4.043x3 + 5.53x4 + 0.379x5 + + 8.076x6 - 678.93 (R2=0.892; Sy = 16.28) and Ŷ = 2.525x4 + 0.579x7 + 0.451x8 - 134.17 (R2=0.943; Sy = 11.84); independent variables x1 - height at sacrum (cm); x2 - chest girth (cm); x3 - pelvic width (cm); x4 - pelvic length (cm); x5 - thickness of M. gluteo-biceps (mm); x6 - intravital muscle scoring (points); x7 - thickness of M. longissimus dorsi (mm); x8 - live weight (kg). Validation of the first regression equation revealed overestimation of HCW by 1.25% on average, while validation of the second equation revealed its underestimation by 1.85% on average. It was found that intravital muscle scoring and selected ultrasound and zoometric measurements of HF bulls can be used in formulating regression equations for predicting the carcass value of live animals. The proposed models enable predicting the carcass value of young bulls with satisfactory accuracy, thus contributing to an objective live beef cattle assessment

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