AMMI and sequential path analyses of soybean [Glycine max (L.) Merrill] experimental lines in a breeding program in the Mexican tropics

The selection of soybean genetic material for crop production is complicated by genotype × environment interactions (G×E) during the development of breeding materials. The Additive Main Effects and Multiplicative Interactions (AMMI) model is the most com-monly used model for modeling G×E and analyzing field data in plant breeding experiments. The objective of this study was to evaluate the significance and magnitude of the effect of G×E on soybean grain yield using a biplot based on AMMI analysis. The study also aimed to determine the relationship between total yield and various yield components for soybean using a sequential path analysis. For this purpose, data on grain yields and agronomic traits for 12 soybean genotypes over seven growing seasons (2004-2010) were collected. The first two components of the AMMI model explained 61.5% of the G×E. According to the biplot analysis, no single plant material had the highest yield across all environmental growing conditions. The genotype H98-1521 had the highest yields overall, in addition to a high average yield and less variable yields across different environments. The sequential path analysis demonstrated that soybean yield is significantly related to the following yield components: Weight of 100 seeds (100SEW), plant height at first pod (FPOH), and plant height at R7 (PLHR7).