Statistical models for studying and understanding genotype × environment interaction in an era of climate change and increased genetic information.

Annual crop production will be greatly affected by increases in mean temperature and climate change, which will be likely to reduce agricultural production and decrease food availability. Plant breeding will play an important role in developing more sustainable lines and varieties for less favourable environments that will be subjected to extreme changes in biotic and abiotic stresses. Breeding cultivars with enhanced tolerance to heat, moisture stress and salinity is essential for long-term adaptation response to climate change. Multi-environment trials (METs) play a paramount role in breeding cultivars for general and specific adaptation and yield stability, studying genotype × environment (GE) interaction, and predicting the performance of new cultivars in future years and new locations. METs produce a vast amount of useful data, including not only phenotypic measurements of cultivars evaluated in different environments but also climatic and soil data as well as molecular markers representing genetic data. Appropriate statistical models and analyses used to study response patterns of genotypes and their molecular marker attributes across different environments undergoing varying climatic changes will be of paramount importance for developing sustainable and stable cultivars that are resistant/tolerant to diverse biotic and abiotic stresses. In this chapter, we explain the theoretical basis of several statistical models and their application for explaining the climatic and genetic causes of GE interaction.