Selection to high productivity and stink bugs resistance by multivariate data analyses in soybean

ABSTRACT Stink bugs that affect soybeans are responsible for significant losses in seed production, quality and germination potential, in addition to hindering the mechanized harvest. To develop insect resistant materials, the breeder can compile a selection index by factor analysis. Therefore, the objective of this work was to validate the use of factor analysis, by means of its estimated gains, for the selection of highly productive and stink bugs resistant genotypes in two soybean segregating populations. For this, the phenotypic evaluation was performed in the generation F2:3, in two distinct experiments, being the populations from the crosses between IAC-100 × PI 295952 and IAC-100 × PI 306712. The experiments were installed in an 18 × 9 alpha-lattice design, with three replicates for each population. Agronomic and resistance characters were evaluated. The factorial scores for each character were obtained for the creation of “supercharacters”. These were designed to check if the selection in the new characters could provide satisfactory simultaneous gains in the original characters. Subsequently, the analysis of variance was performed for all factors, in both populations. The F test showed the presence of variability among genotypes, allowing the selection of superior genotypes. None of the factors selected progenies with all the characters favorably, and their use was not interesting for both populations. With this, complementary studies should be performed with other selection indices in these populations.