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通过比较不同杂交组合优质冷鲜鸡体重、体尺和屠宰性能等性状,初步筛选杂交组合,并通过分析体尺性状与屠宰性能的相关性,建立最佳回归方程,提高育种效率。对63日龄三个杂交组合(ABC、ABD、AEB)优质冷鲜鸡体重、体尺及屠宰性能指标进行测定,利用SPSS 16.0软件进行相关及回归分析,采用逐步回归法构建屠宰性能与体尺性状的多元回归方程。结果表明:三个杂交组合63日龄母鸡体重均超过1.8 kg,公鸡体重均超过2.2 kg。公母鸡的屠宰率均超过86%,全净膛率均超过68%。ABC母鸡的全净膛率、胸肌率均显著高于其它杂交组合(P<0.05)。三个组合体斜长、龙骨长、胸宽、胸深、胫长和胫围均显著大于母鸡。ABC和AEB公、母鸡的体斜长均显著大于ABD公、母鸡;ABC公、母鸡胸深显著大于AEB公、母鸡;ABC母鸡胫围大于AEB母鸡。屠宰性能与某些体尺性状间存在显著或极显著相关(P<0.05或P<0.01),其中活体重、屠体重、全净膛重、半净膛重、单侧腿肌重与胫长极显著相关(P<0.01),且相关系数最大,分别为0.740、0.770、0.742、0.693、0.651。建立活体重、屠体重、全净膛重、腿肌重与某些体尺性状的最佳线性回归方程,将对屠宰性能影响显著的相关体尺性状代入回归方程,可预测相应的屠宰性能。
By comparing the body weight, body size and slaughter performance of different quality cold-cured chickens, we initially screened the hybrid combinations and established the best regression equation to improve the breeding efficiency by analyzing the correlation between body size and slaughter performance. The body weight, body size and slaughter performance of three chilled chickens aged 63 days old (ABC, ABD, AEB) were determined. Correlation and regression analysis were conducted by using SPSS 16.0 software. The stepwise regression method was used to construct the slaughter performance and body size Multiple regression equations of traits. The results showed that the body weight of the three-day-old 63-day-old hens exceeded 1.8 kg and the body weight of the roosters exceeded 2.2 kg. The slaughter rate of males and hens exceeded 86% and the total eviscerated rate was over 68%. The net evisceration rate and breast muscle percentage of ABC hens were significantly higher than those of other hybrid combinations (P <0.05). The length of the keel, chest width, chest depth, tibia length and tibia circumference of the three combinations were significantly larger than that of the hen. ABC and AEB male and female body slant length were significantly greater than the ABD male and female; ABC male hen chest depth was significantly greater than the AEB male and hens; ABC hen tibia circumference greater than AEB hens. There were significant or very significant correlations between slaughter performance and some body size traits (P <0.05 or P <0.01), including live weight, carcass weight, total eviscerated weight, semi-eviscerated weight, unilateral leg weight and shin length (P <0.01), and the correlation coefficient was the highest, which were 0.740, 0.770, 0.742, 0.693 and 0.651 respectively. The optimal linear regression equation of living weight, carcass weight, total eviscerated weight, leg muscle weight and some body size traits was fitted into the regression equation, and the corresponding slaughter performance was predicted.