论文部分内容阅读
在农作物品种区域试验中,品种在各地点的表现通常是不一致的,也就是说品种的基因型和环境(G×E)存在着交互作用。常用的G×E交互作用分析方法是相对于环境指数的线性回归方程,但这一方法约束性较强,解释G×E交互作用较少。加性主效应和乘积交互作用模型(简称AMMI模型)在常规的基因型和环境的加性模型中加入了乘积形式的交互作用,能更多地解释G×E交互作用。实例分析表明AMMI模型是品种区域试验结果分析更为有效的方法。
In the regional trials of crop varieties, the performance of breeds at each locality is usually inconsistent, that is to say there is an interaction between the genotype of the breeds and the environment (G × E). The commonly used G × E interaction analysis method is a linear regression equation relative to the environmental index, but this method is more restrictive and explains that G × E interaction is less. The additive main effect and product interaction model (AMMI model for short) adds the product form interaction to the conventional additive model of genotype and environment, which can explain G × E interaction more. The case study shows that the AMMI model is a more effective method for analyzing regional test results.