Estratificação ambiental baseada em envirotyping para análise e predição da interaçao genótipo x ambiente em soja

Abstract

Recent climate change has intensified the challenges associated with agricultural production, increasing environmental variability and the complexity of cultivar responses across different growing environments. Understanding how soybean cultivars (Glycine max (L.) Merrill) respond to climatic variability is essential to sustaining food production and achieving productivity gains under increasingly adverse and challenging scenarios. Therefore, the aim of this study was to identify the formation of mega-environments (MEs) within the soybean-producing macro-region M1 using environmental information derived from envirotyping techniques, as well as to identify cultivars that are adapted and stable within the resulting MEs. This investigation used grain yield data from 25 soybean genotypes (10 cultivars and 15 breeding lines) evaluated during the 2023/24 growing season across 14 locations within Brazil’s soybean macro-region 1 (MRS1), together with 11 environmental parameters recorded for each site. Eleven environmental covariates were collected for each location and grouped into five developmental stages: 1-VE (Emergence); 2-VE/R2 (Full flowering); 3-R2/R5 (Beginning of pod filling); 4-R5/R7 (Onset of maturation); and 5-R7/R8 (Physiological maturity), based on environmental data obtained from NASA POWER. Environmental stratification identified four mega-environments with contrasting climatic profiles, varying mainly in TMAX, T2M, PRECTOT, PETP, and VPD. ME1 was characterised by high reproductive temperatures and elevated evaporative demand; ME2 showed the highest productivity, with favourable T2M and irregular precipitation; ME3 stood out for its thermal and hydric stability; and ME4 represented the most restrictive environment, with high TMAX, severe PETP, and elevated VPD. Regarding genotypic performance, G2, G15, G9, and G8 showed superiority in ME1; G3, G11, and G25 were more productive in ME2; G11, G19, and G22 performed best in ME3; and G5, G11, G8, G17, and G20 demonstrated superior performance under the adverse conditions of ME4. Environmental stratification proves essential for guiding plant breeding by identifying adaptation and stability patterns across environments. In the face of climate change, advancing studies that improve environmental characterisation and accelerate the selection of more resilient and broadly adapted genotypes becomes increasingly crucial.