TRANSFORMING TROPICAL WHEAT RECOMMENDATION: A FRESH PERSPECTIVE WITH GIS-FA 1.1

In breeding programs, it is essential to use analytical methods that fully exploit the patterns of genotype-by-environment interaction (GEI) in multi-environment trials (MET). A parsimonious extension of these methods is GIS-FA, which integrates factor-analytic multiplicative (FA) models, partial least squares (PLS) regression, geographic information system (GIS) techniques and enviromics to predict the performance of genotypes in untested environments. This work aimed to propose some modifications to the GIS-FA method and apply it to the recommendation of wheat (Triticum aestivum L.) genotypes throughout the state of Minas Gerais. We used thematic maps of genotypic adaptation to support decision-making and recommend genotypes for specific environments. Two genotypes stood out in terms of adaptation: a commercial variety (brs_264) and an inbred line from the UFV wheat breeding program (VI_19065). The VI_19065 performed well in the south and some central Minas Gerais areas, showing superiority over the commercial variety. In summary, the thematic maps allow us to target new breeding scenarios by identifying groups of environments where genotypes are expected to outperform better.