Mega-environment identification for soybean (Glycine max) breeding and production in Brazilian Midwest region

Abstract

Mega-environment (ME) identification is the first step for evaluating, selecting and recommending genotypes within a target region (TR). The present study aimed to (a) identify MEs, using GGE biplot methods, in Brazilian edaphoclimatic region (ECR) 402 of soybean cultivation, located in the Mato Grosso State (the TR) and (b) compare the performance of genotypes within the TR and in each ME using fixed and mixed models. Data from three years of soybean yield trials, 19 genotypes and 22 environments were used. The biplots GGE, GGL + GGE and GGS + GGE were implemented to identify the MEs. Two MEs were identified in the TR. ME1 presents a higher altitude, farms which use a higher level of fertilizer inputs and a higher occurrence of the soybean cyst nematode (SCN) than ME2. When selection and recommendation are made based on MEs, genotypes with both broadly and specific adaptation can be selected. This action can improve grain yield in the entire target region.