中国黄牛及其杂交牛产肉量和产肉率预测

将102头中国黄牛及其杂交牛(热胴体重平均值为299.722kg)按现代工艺流程屠宰、冷却并分割,测定肉牛胴体热胴体重(HCW)、眼肌面积(REA)和背膘厚(FT),并预测胴体产肉量和产肉率。热胴体重(HCW)与总体零售切块产量(TRC)、高档零售切块产量(TGRC)以及优质零售切块产量(PRC)三者极显著正相关(p<0.01),和总体零售切块产率(TRC)显著正相关(p<0.05);HCW与高档零售切块产率(TGRC)以及优质零售切块产率(PRC)两者没有显著相关性(p>0.05)。REA与TRC、TGRC和PRC极显著正相关(p<0.01),与TRC也呈极显著正相关(p<0.01),REA与TGRC和PRC没有显著相关性(p>0.05)。在所有回归模型中,3因子共同预测总体零售切块产肉量的方程,预测准确度最高(R2=0.974,SE=3.892),方程中HCW解释了大部分变异(SC=0.665),而FT的作用很小(SC=-0.044);以3因子预测总体零售切块产率方程解释了63.1%的变异(R=0.794,SE=1.67),其中眼肌面积的作用最大(SC=1.033)。FT无论在预测零售切块产量还是产率,作用最小。

Prediction of Weight and Percent of Retail Cuts of Chinese Yellow Cattle and its Hybrids

102 Chinese yellow cattle and its hybrids(mean of hot carcass weight was 299.722?kg) were slaughtered, chilled and fragmented according to modern technology.The hot carcass weight (HCW, kg), fat thickness (FT, cm) and rib eye area (REA, cm~2) were measured to predict the weight and percent of retail cuts. Simple correlation coefficients among 9 variables showed that HCW was positively and significantly correlated with the weight of total retail cuts (TRC, kg), the weight of top grade retail cuts(TGRC, kg) and the weight of prime retail cuts (PRC, kg) (p<0.01). HCW was correlated with the percent of total retail cuts (TRC, %) (p<0.05). REA was positively and significantly correlated with TRC, kg, TGRC, kg, PRC, kg and TRC,% (p<0.01). There was not significantly correlation between HCW and the percent of top grade retail cuts (TGRC, %) and the percent of prime retail cuts (PRC, %) (p>0.05), so did REA (p>0.05). In all regression equations predicting weight and percent of retail cuts, equation predicting weight of total retail cuts using HCW, REA and FT had the highest R square (0.974), when two predictors were held constant in equations which utilized three predictors. HCW explained the most amount of variation while FT explained the least, and the Standardized Coefficients was 0.665 vs. -0.044. Using three predictors predicting the percent of total retail cuts explained 63.1% of the variation (R=0.794, SE=1.67), in which, REA was the most valuable predictor. (SC=1.033). FT was the least valuable predictor of weight of retail cuts (p>0.05) when HCW and REA were held constant or not.