摘要：Additive Main Effect and Multiplicative Model (AMMI Model) nowadays is used to asses in plant breeding, especially to asses the Genotype × Environment Interaction (GEI) on multi-environment trial. The presence of genotype × environment interaction (GEI) creates difficulties in modeling complex trait that involve sequence biological process. Coupling Structural equation modeling with AMMI was developed to analyzed genotype × environment interaction (GEI). Structural equation modeling allows us to account for underlying sequential process in plant development by incorporating intermediate variables associated with those processes in the model. With this method we can incorporating genotypic and environmental covariate in the model and explain how those covariates influence grain yield. SEM-AMMI useful when both environments and genotype are fixed and the purpose of the multi-environment trials (MET) is to assess the combined effect genotypic and environmental covariate on yield and yield components.
其他摘要：Additive Main Effect and Multiplicative Model (AMMI Model) nowadays is used to asses in plant breeding, especially to asses the Genotype × Environment Interaction (GEI) on multi-environment trial. The presence of genotype × environment interaction (GEI) creates difficulties in modeling complex trait that involve sequence biological process. Coupling Structural equation modeling with AMMI was developed to analyzed genotype × environment interaction (GEI). Structural equation modeling allows us to account for underlying sequential process in plant development by incorporating intermediate variables associated with those processes in the model. With this method we can incorporating genotypic and environmental covariate in the model and explain how those covariates influence grain yield. SEM-AMMI useful when both environments and genotype are fixed and the purpose of the multi-environment trials (MET) is to assess the combined effect genotypic and environmental covariate on yield and yield components
