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Predicting beef carcass meat, fat and bone proportions from carcass conformation and fat scores or hindquarter dissection

机译:从胴体构象和脂肪评分或后躯解剖预测牛肉胴体肉,脂肪和骨比例

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摘要

Equations for predicting the meat, fat and bone proportions in beef carcasses using the European Union carcass classificationscores for conformation and fatness, and hindquarter composition were developed and their accuracy was tested using data from 662cattle. The animals included bulls, steers and heifers, and comprised of Holstein–Friesian, early- and late-maturing breeds x Holstein–Friesian, early-maturing X early-maturing, late-maturing X early-maturing and genotypes with 0.75 or greater late-maturing ancestry. Bulls, heifers and steers were slaughtered at 15, 20 and 24 months of age, respectively. The diet offered before slaughter includes grass silage only, grass or maize silage plus supplementary concentrates, or concentrates offered ad libitum plus 1 kg of roughage drymatter per head daily. Following the slaughter, carcasses were classified mechanically for conformation and fatness (scale 1 to 15), and the right side of each carcass was dissected into meat, fat and bone. Carcass conformation score ranged from 4.7 to 14.4, 5.4 to 10.9 and 2.0 to 12.0 for bulls, heifers and steers, respectively; the corresponding ranges for fat score were 2.7 to 11.5, 3.2 to 11.3 and 2.8 to 13.3. Prediction equations for carcass meat, fat and bone proportions were developed using multiple regression, with carcass conformation and fat score both included as continuous independent variables. In a separate series of analyses, theindependent variable in the model was the proportion of the trait under investigation (meat, fat or bone) in the hindquarter. In both analyses, interactions between the independent variables and gender were tested. The predictive ability of the developed equations was assed using cross-validation on all 662 animals. Carcass classification scores accounted for 0.73, 0.67 and 0.71 of the total variation in carcass meat, fat and bone proportions, respectively, across all 662 animals. The corresponding values using hindquartermeat, fat and bone in the model were 0.93, 0.87 and 0.89, respectively. The bias of the prediction equations when applied across allanimals was not different from zero, but bias did exist among some of the genotypes of animals present. In conclusion, carcassclassification scores and hindquarter composition are accurate and efficient predictors of carcass meat, fat and bone proportions.
机译:建立了使用欧盟car体分类构象和脂肪分数以及后四分组成预测牛肉beef体中肉,脂肪和骨比例的方程式,并使用662牛的数据测试了其准确性。这些动物包括公牛,公牛和小母牛,并且由荷斯坦–弗里斯兰,早熟和后期成熟的品种x荷斯坦–弗里斯兰,早熟X早熟,后期成熟X早熟和具有0.75或更高后期的基因型组成成熟的祖先。公牛,小母牛和and牛分别在15、20和24个月大时被宰杀。屠宰前提供的饮食包括仅青贮草,青草或玉米青贮饲料以及补充浓缩物,或随意提供的浓缩物加上每人每天1公斤粗饲料。屠宰后,将cas体机械分类为构象和脂肪(等级1至15),并将每个,体的右侧切成肉,脂肪和骨头。公牛,小母牛和ste牛的体构象得分分别为4.7至14.4、5.4至10.9和2.0至12.0。脂肪评分的相应范围为2.7至11.5、3.2至11.3和2.8至13.3。 multiple体肉,脂肪和骨骼比例的预测方程式是使用多元回归方法开发的,car体构象和脂肪评分均作为连续的独立变量。在单独的一系列分析中,模型中的独立变量是被调查性状(肉,脂肪或骨骼)在后躯中所占的比例。在两项分析中,均测试了自变量与性别之间的相互作用。使用交叉验证对所有662只动物评估了所开发方程的预测能力。在所有662只动物中,体分类分数分别占car体肉,脂肪和骨骼比例总变化的0.73、0.67和0.71。在模型中,使用后四肢肉,脂肪和骨骼的相应值分别为0.93、0.87和0.89。当将预测方程式应用于动物身上时,其偏倚与零无异,但存在的某些动物基因型中确实存在偏倚。总之,car体分类评分和后肢组成是are体肉,脂肪和骨骼比例的准确有效预测指标。

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