The causes of genotype interaction with the environment was investigated using AMMI (Additive Main Effects and Multiplicative Interaction)analysis. AMMI quantified environments by means of E_IPCA1 (first principal component analysis for environment) such that it was highly significantly correlated (r = -0.79) with accumulated growing degree units (GDUs) during the growing season. G_IPCA1 (first principal component analysis for genotype) scores were highly significantly correlated with growth rate related observations, such as days to 50 pollen shed (-0.77), days to physiological maturity (-0.81), and grain moisture at harvest (-0.87). Multiple linear regression analysis of data led to the conclusion that GJPCA1 scores can be explained with R2= 0.80 accuracy from a combination of grain moisture at harvest and either days to physiological maturity, or days to pollen shed. The AMMI required that E_IPCA1 and G_IPCA1 scores should, both be either positive or negative in order to increase AMMI1 yield estimates. This means that hybrids with a slower growth rate will be better adapted to environments with more GDUs during the growing season, and hybrids with a faster growth rate will be better adapted to environments with less GDUs during the growing season. This conclusion suggests that temperature, especially minimum night temperature, which determines the rate of development between physiological stages in the maize plant, may be a major contributor to genotype by environment interaction.
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