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Prediction of Body Weight and other Linear Body Measurement of Two Commercial Layer Strain Chickens

机译:两只商业层应变鸡的体重预测和其他线性体测量

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A total of 509 birds comprising 249 Nera Black (NB) and 260 Brown Shaver (BR) were used for this study. Data were collected on the birds from week one to twenty. Prediction of Body Weight (BW), Chest Girth (CG), Keel Length (KL), Body Length (BL) andShank Length (SL) were highly significant (p<0.001). The coefficient of determination (R2) varied from 85 to 99% for CG and KL. In both genotypes, the relationship between BW and other body measurements were higher in CG and KL traits and best describedby cubic model. Cubic function (R2 = 99%) predicted BW more accurately than quadratic and linear functions. The phenotypic correlation coefficients at day old m NB between BW and BL were positive, medium and highly significant (p<0.01), the phenotypic correlation coefficients for BW and BL in BR was low, negative and highly significant (p<0.01). Lower correlation values were obtained between BW and BL and significant (p<0.05) in NB strain at 4 weeks old. Also, negative highly significant was achieved between BW and SL. At 8 weeks old, low to medium correlation coefficients were observed between BW and SL, BW and KL, BW and CG in NB strain. Significant correlations were achieved between BW and SL, BW and CG traits in BR strain. At 12 weeks old, high, positive and significant (p<0.01) values were observed between BW and other traits in NB. The phenotypic correlation coefficients were of medium to high in NB between BW and KL, BW and BL at 16 weeks old. There were highly significant differences (p<0.01)between BW and other traits measured in BR strain. At 20 weeks old, the correlation values obtained were low to high in NB, lower values were also obtained for BR at the same age. As a result of these observations, it was considered possible to use the body weight in determining BL, SL, KL and CG.
机译:这项研究总共使用了509只鸟,其中包括249只Nera Black(NB)和260只Brown Shaver(BR)。从第一周到第二十周收集有关鸟类的数据。体重(BW),胸围(CG),龙骨长度(KL),体长(BL)和胫骨长度(SL)的预测非常显着(p <0.001)。 CG和KL的测定系数(R2)从85%到99%不等。在这两种基因型中,体重和其他身体测量值之间的关系在CG和KL性状中均较高,最好用三次模型来描述。三次函数(R2 = 99%)比二次函数和线性函数更准确地预测体重。 BW和BL之间的日龄m NB的表型相关系数为正,中和高度显着(p <0.01),BR中BW和BL的表型相关系数为低,负和高度显着(p <0.01)。在BW和BL之间获得较低的相关值,在4周龄的NB菌株中具有显着性(p <0.05)。此外,在BW和SL之间获得了负的高度显着性。在8周龄时,在NB菌株中观察到BW与SL,BW与KL,BW与CG之间的低至中等相关系数。 BR菌株的BW和SL,BW和CG性状之间实现了显着的相关性。在12周龄时,观察到BW和NB中其他特征之间的高,阳性和显着(p <0.01)值。表型相关系数在16周龄时BW与KL,BW与BL之间的NB中至中高。在BR菌株中测得的BW与其他性状之间存在极显着差异(p <0.01)。在20周龄时,NB的相关值从低到高,在相同年龄的BR的相关值也较低。作为这些观察结果,认为可以使用体重来确定BL,SL,KL和CG。

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