ABSTRACT

The objective of the present work was to evaluate the influence of environmental variables on the interaction between genotypes and environments and to identify adapted and stable genotypes for grain seed yield. Twenty-one cultivars were evaluated in randomized blocks with four replications in the years 2016, 2017, and 2018 in the northeastern semi-arid region of Brazil, for seed yield and oil content. Factor regression methodologies and principal component analysis were used with predictions of the sum of the genotypic effects and the interaction to quantify the role of five environmental covariates in the genotype x environment interaction; the Harmonic Mean Method of Relative Performance of Genotypic Values was used for identifying adapted and stable genotypes. The covariance biplot model is useful for relating important environmental factors and indicating their relative effect on seed yield and oil content. Rainfall, relative humidity and maximum temperature contribute positively to increasing oil content while minimum temperature and solar radiation reduce it. Within the limits of the work, the maximum temperature positively influences grain production while the minimum reduces it. The most stable genotypes and those adapted for grain seed yield and oil content are BMX OPUS IPRO, P 98Y70 RR, BRS 333 RR, BRS 9280 RR, M 8644 IPRO, M 8372 IPRO, and ST 920 RR.

Keywords:
Glycine max L; Mixed models; Multivariate analysis; Oilseed; REML/BLUP