线性混合模型用于识别谷物产量与其他产量相关特征之间的关系,以及为小麦的基因型选择
Mulugeta Tesfa1,2, Temesgen Zewotir3, Solomon Assefa Derese4,5
1Department of Statistics, College of Science, Bahir Dar University, P. O. Box, 79, Bahir Dar, Ethiopia.
Heliyon
|July 17, 2023
概括
这项研究使用混合模型确定了干旱地区的顶级类基因型. 推使用40型,186型和196型基因型进行广泛种植,并选择适合灌或应激条件的特定品种.
科学领域:
- 农业科学 农业科学
- 遗传学 是一个遗传学.
- 植物育种 植物育种
背景情况:
- 在干旱和半干旱地区,特别是撒哈拉以南非洲地区,是一种重要的作物.
- 的表型特征受到基因型,环境及其相互作用的影响.
研究的目的:
- 分析谷物产量与其他产量相关特征之间的关系.
- 为了确定粮食产量的高性能基因型.
- 使用混合模型检查特征与谷物产量的关联.
主要方法:
- 用于数据生成的格子方形设计.
- 主要组件分析 (PCA) 创建无关联的变量.
- 混合模型分析,以评估对谷物产量的基因型和环境影响.
主要成果:
- 由于治疗和基因型与环境的相互作用,观察到谷物产量的显著变化.
- 前三个主要组成部分解释了77.12%的表型变异.
- 基因型影响占谷物产量变化的45.73%,而基因型与环境相互作用解释了39.06%.
结论:
- 推使用G40,G186和G196基因型进行大规模生产,而无需环境限制.
- 特定的基因型 (G40,G62,G192用于灌;G26,G55,G49用于压力) 已被确定为目标环境.
- 混合模型方法对分析谷谷物产量是有效的,未来的研究重点是多环境和多年评估.
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