Exploring genotype × environment interaction in sweet sorghum under tropical environments

Abstract

AbstractUnderstanding the genotype‐by‐environment interactions (GEI) is crucial to release sweet sorghum [Sorghum bicolor (L.) Moench] cultivars with stable and high agronomic performance under tropical environments. Therefore, linear mixed models could be used to face this challenge by leveraging the biological process of GEI into cultivar recommendation. The goals of this study were: (a) to explore GEI patterns under tropical conditions to select stable and high‐yielding genotypes for energy‐use in the bioethanol industry; and (b) to evaluate the advantages of linear mixed models taking into account simultaneously the genetic and the residual correlations across environments and the genomic relationship between genotypes. The breeding dataset was comprised of 41 genotypes evaluated for Tonnes of brix per hectare (TBH) in late‐stage trials over 32 tropical environments. The models incorporating simultaneously the genomic relationship matrix of genotypes and the genetic and the residual correlations across environments showed the lowest values of Akaike Information Criterion (AIC) compared to the standard phenotypic models, and also increased the expected genetic gains of TBH across years. Based on the best models selected by AIC, the genotypes 38 (CMSXS5006), 6 (BRS511), 5 (CMSXS633), 9 (CMSXS637), and 12 (BRS506) exhibited the highest productivity in TBH. Particularly, the genotype 9 (CMSXS637) showed broad stability and high productivity under tropical environments, besides the desirable traits for bioethanol production. These results highlight the importance of modeling the genomic relationship between genotypes and the genetic and the residual correlations across environments to increase the breeding efficiency of sweet sorghum under tropical environments.