Key locations for soybean genotype assessment in South Brazil region

Abstract

Mitigating the high costs of soybean breeding programs requires constant improvement of all the involved processes. Identifying representative and discriminating test locations, as well as excluding redundant and/or non-representative locations, makes it possible to select genotypes with more accuracy while reducing the costs of the multi-environment trials (MET). Therefore, this study had three objectives: to evaluate the representativeness and discriminating power of test locations; to identify similar test locations for each Edaphoclimatic Region (ECR) and locations that did not contribute to genotype evaluation; and to recommend the best locations for evaluating MET in order to reduce breeding program costs in the soybean macro regions 1 (M1) and 2 (M2). Grain yield (GY) data from ‘Value-for-Cultivation-and-Use’ (VCU) trials obtained during the 2012-2016 crop seasons were used, totaling 132 environments (location x year) and 43 genotypes. The experiments were arranged in a randomized complete block design with three replications. Representative and discriminant locations were identified by GGL (genotype main effects plus genotype × location interaction) + GGE (genotype main effects plus genotype × environment interaction) analysis, using GGEbiplot software. Representative and discriminant locations were identified for each ECR and can be used as core locations for breeding programs. Similarly, locations that were not representative and discriminant, or that present redundancy in the results, should be excluded from or replaced in MET. The most recommended locations for conducting VCU trials in M1 are: Cachoeira do Sul (ECR 101); Ronda Alta, Passo Fundo, Santa Bárbara do Sul, and Ciríaco (ECR 102); and Castro (ECR 103). For M2, the most suitable locations are Rolândia, Marechal Cândido Rondon, Campo Mourão, Santa Terezinha de Itaipu, Palotina, Floresta, and Londrina (ECR 201); Naviraí (ECR 202); and Ponta Porã and Maracajú (ECR 204).

Keywords

• Glycine max (L.) Merrill
• GGL GGE Biplots
• Representativeness and Discriminating power.