Browsing Food Chemistry & Technology by Subject "Beef Cattle"
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Live animal measurements, carcass composition and plasma hormone and metabolite concentrations in male progeny of sires differing in genetic merit for beef productionIn genetic improvement programmes for beef cattle, the effect of selecting for a given trait or index on other economically important traits, or their predictors, must be quantified to ensure no deleterious consequential effects go unnoticed. The objective was to compare live animal measurements, carcass composition and plasma hormone and metabolite concentrations of male progeny of sires selected on an economic index in Ireland. This beef carcass index (BCI) is expressed in euros and based on weaning weight, feed intake, carcass weight and carcass conformation and fat scores. The index is used to aid in the genetic comparison of animals for the expected profitability of their progeny at slaughter. A total of 107 progeny from beef sires of high (n = 11) or low (n = 11) genetic merit for the BCI were compared in either a bull (slaughtered at 16 months of age) or steer (slaughtered at 24 months of age) production system, following purchase after weaning (8 months of age) from commercial beef herds. Data were analysed as a 2 × 2 factorial design (two levels of genetic merit by two production systems). Progeny of high BCI sires had heavier carcasses, greater (P < 0.01) muscularity scores after weaning, greater (P < 0.05) skeletal scores and scanned muscle depth pre-slaughter, higher (P < 0.05) plasma insulin concentrations and greater (P < 0.01) animal value (obtained by multiplying carcass weight by carcass value, which was based on the weight of meat in each cut by its commercial value) than progeny of low BCI sires. Regression of progeny performance on sire genetic merit was also undertaken across the entire data set. In steers, the effect of BCI on carcass meat proportion, calculated carcass value (c/kg) and animal value was positive (P < 0.01), while a negative association was observed for scanned fat depth pre-slaughter and carcass fat proportion (P < 0.01), but there was no effect in bulls. The effect of sire expected progeny difference (EPD) for carcass weight followed the same trends as BCI. Muscularity scores, carcass meat proportion and calculated carcass value increased, whereas scanned fat depth, carcass fat and bone proportions decreased with increasing sire EPD for conformation score. The opposite association was observed for sire EPD for fat score. Results from this study show that selection using the BCI had positive effects on live animal muscularity, carcass meat proportion, proportions of high-value cuts and carcass value in steer progeny, which are desirable traits in beef production.
Predicting beef carcass meat, fat and bone proportions from carcass conformation and fat scores or hindquarter dissectionEquations 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 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 dry matter 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, the independent 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 hindquarter meat, fat and bone in the model were 0.93, 0.87 and 0.89, respectively. The bias of the prediction equations when applied across all animals was not different from zero, but bias did exist among some of the genotypes of animals present. In conclusion, carcass classification scores and hindquarter composition are accurate and efficient predictors of carcass meat, fat and bone proportions.