关键词: 体重, 随机回归模型, 遗传力, 特征值, 蛋鸡

Abstract:

【Objective】 This study was to assess the effect of the orders of Legendre polynominals on the size of the maximum likelihood and the error, to optimize the random regression model, to evaluate the genetic potential and selection knot of layer resource population and to provide parameters for optimal layer breeding scheme for resource population. 【Method】The data set consisted of 26 532 items collected from the layer resource population, which set up by White Leghorn reciprocal crossing with the blue eggshell chickens. The pedigree consisted of 5 871 individuals, including 4 147 chickens with 5 records, 802 chickens with 4 records and 128 chickens without records. The standard of data cleaning included: i. removing outlier; ii. eliminating repeated individuals; iii. getting rid of unknown sexed individuals; iv. individuals with less than 4 records were also excluded. After data cleaning procedures, 25 483 records on body weight could be used in the next step, 2 223 of which collected from blue shelled chickens, 696 of which collected from White Leghorn, 6 002 of which collected from F₁ generation and 16 562 of which collected from F₂ generation. The influence of the nongenetic factors on body weights was analyzed by GLM in SPSS. The fixed effects of animal model included batch and sex factors. Using the random regression model, variance components, genetic parameters and eigenvectors were obtained. The model included general fixed effect and fixed regression, random regression. In this study, batch-sex was the fixed effects, and a fixed regression was fitted for week age body weight effects; the direct additive genetic, permanent environment were the random effects. Comparing with AIC and BIC values, the best model should embed 2nd Legendre polynomials into fixed effects, 5th Legendre polynomials into additive genetic effects and permanent environmental effects. Heterogeneous residual variance was grouped into 5 levels. Each observation was set an initial estimate. The residual variance between the neighboring observations was treated as a linear regression. 【Result】 For the body weights on resource population, heritability was ranged from 0.46 to 0.63, repeatability varied from 0.88 to 0.92, the genetic correlation was ranged from 0.32 to 0.99, and permanent environmental correlation was varied from 0.34 to 0.99. The genetic correlations among the weeks reduced with the intervals increased, high correlations occurred between the neighboring weeks. The genetic variance, permanent environmental variance and residual variance increased with ages. The first three eigenvalues of additive genetic effects was 1 976.91, 161.95, and 42.22, respectively, and these eigenvalues could explain 99% of total variations. 【Conclusion】The genetic parameters on the early body weights in laying chickens were estimated with a random regression model. The individual growth curve could be altered by selection on the coefficients associated with the second eigenfunction. The right time seemed to select on 3 to 6 week. Estimates of heritability in the resource population were larger than the results in the literatures.

Key words: body weight, random regression model, heritability, eigenvalue, layer