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Bedhane M, Haile A, Dadi H, et al. Estimates of genetic and phenotypic parameters for growth traits in Arsi-Bale goat in Ethiopia[J]. Journal of Animal Sciences Advances, 2013, 3: 439-448.
1，摘要
数据类型
A total of 978 birth weights (Brwt), 642 weaning weights (Wnwt), 438 six month weights (Sixmwt) and 348 yearling weights (Ywt) traits were used.
固定效应影响较大
The least squares mean analyses were performed using the general linear model procedure of SAS to determine effects of fixed factors on the traits studied. Fixed effects were found to be important source of variation in this study. The overall least square means of Brwt, Wnwt, Sixmwt and Ywt, were 1.91, 6.65, 9.03 and 14.32kg, respectively.
不同性状的遗传力和母体效应遗传力
The heritability estimates for Brwt, Wnwt, Sixmwt and Ywt under varied from 0.04 - 0.39, 0.02 - 0.08, 0.02 - 0.08 and 0.13 - 0.23, respectively and maternal genetic effect were 0.20 and 0.09, 0.07 and 0.03, 0.06 and 0.04, and 0.02 and 0.01, respectively.
性状相关的利用价值
Genetic and phenotypic correlations between growth performance traits vary from medium to high. Therefore, it can be concluded that, the traits can be improved if selection could be based on the traits which has relatively high heritability value. Fixed effects are important and they should be included in the intended genetic improvement program of Arsi-Bale goat.
2，统计方法
1，用SAS的GLM模型评价固定效应的显著性，并计算预测均值
2，用DFREML估算四种模型的方差组分、遗传力和遗传相关
- 第一种模型：加性效应
- 第二种模型：加性效应+母体效应
- 第三种模型：加性效应+永久环境效应
- 第四种模型：加性效应+母体效应+ 永久环境效应
3，分析结果
1，方差分析结果以及对预测均值的多重比较
方差分析结果：
多重比较结果：
2，四种模型的方差组分估计和遗传力的计算
3，多性状分析中遗传相关和表型相关
4，如果用asreml-r分析
- 里面的所有分析都可以更容易的实现。
- SAS中的GLM模型，可以用R语言中的aov来代替。
- 多重比较，也可以由R语言完成。
- 文中的4中模型，asreml-r包可以轻松的完成。
