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ProbBreed:一种用于计算多环境试验中品种推风险的新工具
Saulo F S Chaves1, Matheus D Krause2, Luiz A S Dias1
1Department of Agronomy, Federal University of Viçosa, Viçosa 36570-900, Brazil.
G3 (Bethesda, Md.)
|January 20, 2024
概括
育种者现在可以使用ProbBreed R包轻松评估跨环境的基因型表现. 该工具通过计算优异表现的概率来改善品种选择,减少有缺陷的建议.
科学领域:
- 农业科学 农业科学
- 生物技术是生物技术.
- 统计遗传学 统计遗传学
背景情况:
- 在多环境试验 (MET) 中,基因型与环境相互作用 (GxE) 对于准确的品种建议至关重要.
- 忽视GxE可能会导致种植者选择低于最佳的品种,影响农业生产率.
- 需要先进的统计方法和软件来简化在育种计划中的GxE分析.
研究的目的:
- 为育种者引入ProbBreed R包,以量化MET中的基因型性能概率.
- 提供一个用户友好的工具来计算一个基因型在贝叶斯框架内表现优于其他基因型的概率.
- 加强在品种选择中的决策,以改善农业成果.
主要方法:
- 在R中开发ProbBreed包,实现贝叶斯方法.
- 工作流包括MET模型的适配和性能和稳定性概率的估计.
- 使用选择强度作为概率计算的主要输入.
主要成果:
- ProbBreed可以计算单独和双对概率,以获得卓越的基因型性能和稳定性.
- 该软件包简化了复杂的概率学方法,用于实际的育种应用.
- 证明选择强度足以计算这些关键概率.
结论:
- 在ProbBreed包中,在MET中进行基因型评估的先进统计方法得到了民主化.
- 它为育种者和种植者提供了更准确,更可靠的品种建议.
- 旨在提高全球植物育种计划的效率和成功率.
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