Adaptability and Genotype x Environment Interaction of Spring Wheat Cultivars in Chile using Regression Analysis, AMMI, and SRAG.

Abstract

Wheat (Triticum aestivum L.) genetic improvement objectives include obtaining cultivars capable of expressing their maximum potential yield and quality in diverse environments. This make necessary to know and define the environment in which a variety can express its maximum potential yield and quality. The objective of this study was to assess which method is the most efficient to study cultivars response in multiple environments. For this, we analyze the adaptability, stability, and genotype x environment (GxE) interaction effect, grain yield, sedimentation, and wet gluten content of 13 spring wheat cultivars sown in six environments in the central-south and southern zones of Chile during two seasons. The data were analyzed by regression analysis, additive main effects and multiplicative interaction (AMMI), and the sites regression (SREG) model. By this was thus established that SREG analysis is the most efficient for this type of study since, in addition to analyzing stability, adaptability, and effect (GxE), it allows identifying the best cultivar. In this case, `Pandora-INIA' stands out by exhibiting the best yield (7.38 t ha(-1)), high sedimentation (36.95 cm(3)), and wet gluten (41.54%) indices in all the environments, and this positions it as a variety having both high yield and quality.