肉类的基因参数随机回归模型
Daniel Dantas Pereira1, João Vitor Santana Prates1, Yara Cardoso Braga1
1Instituto de Ciências Agrárias, Universidade Federal de Minas Gerais, Belo Horizonte, Brazil.
概括
同质模型对五种素水平的肉类 (ICA1和ICA2) 的遗传参数进行了最佳估计. 这一发现有助于优化养殖计划以提高肉类生产.
科学领域:
- 动物遗传学
- 定量遗传学
- 禽类科学
背景情况:
- 精确估计遗传参数对于有效的动物育种计划至关重要.
- 随机回归模型被广泛用于分析牲畜的纵向数据.
- 了解食因素对生长特征的影响对于家禽生产至关重要.
研究的目的:
- 评估在随机回归模型中包含固定效应和残余方差类的影响.
- 估计不同年龄的肉类 (ICA1和ICA2) 体重的遗传参数.
- 评估五种氨酸水平对遗传参数估计的影响.
主要方法:
- 使用了5407只肉类的920个体重记录.
- 采用随机回归模型,其余差异类各不相同 (均到五类).
- 使用多变量分析测试性别,化和出生体重的影响.
主要成果:
- 性别,潜伏期和线性出生体重是影响体重的重要因素.
- 概率测试显示模型之间没有显著的Log (L) 差异.
- 根据贝叶斯信息标准 (BIC),同质模型具有单一的残余方差等级.
结论:
- 一个均的残余方差模型足以估计这种肉类群的遗传参数.
- 饮食中的氨酸水平不需要异质变异模型进行基因分析.
- 这些发现支持在家禽中使用更简单的基因评估模型,从而提高效率.
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