Predicting beef carcass meat, fat and bone proportions from carcass conformation and fat scores or hindquarter dissection
نویسندگان
چکیده
منابع مشابه
Predicting beef carcass meat, fat and bone proportions from carcass conformation and fat scores or hindquarter dissection.
Equations for predicting the meat, fat and bone proportions in beef carcasses using the European Union carcass classification scores for conformation and fatness, and hindquarter composition were developed and their accuracy was tested using data from 662 cattle. The animals included bulls, steers and heifers, and comprised of Holstein-Friesian, early- and late-maturing breeds × Holstein-Friesi...
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Predicting beef carcass cutability.
Analyses were conducted to develop and test the efficacy of beef carcass cutability prediction equations. Data from 1,602 calf-fed steer carcasses (Germplasm Utilization Project; GPU) were used to develop the equations and an additional 1,160 calf-fed steer carcasses (Germplasm Evaluation Project; GPE) were used to validate the equations. In both experimental groups, USDA yield grade ranged fro...
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In this study, a total of 163 young-bull carcasses belonging to seven Spanish native beef cattle breeds showing substantial carcass variation were photographed in order to obtain digital assessments of carcass dimensions and profiles. This dataset was then analysed using machine learning (ML) methodologies to ascertain the influence of carcass profiles on the grade obtained using the SEUROP sys...
متن کاملPredicting carcass and body fat composition using biometric measurements of grazing beef cattle.
This study was conducted to develop equations to predict carcass and body fat compositions using biometric measures (BM) and body postmortem measurements and to determine the relationships between BM and carcass fat and empty body fat compositions of 44 crossbred bulls under tropical grazing conditions. The bulls were serially slaughtered in 4 groups at approximately 0 d (n = 4), 84 d (n = 4), ...
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ژورنال
عنوان ژورنال: Animal
سال: 2010
ISSN: 1751-7311
DOI: 10.1017/s1751731109991121