Abstract
The objective of this work was to identify key locations for the establishment of soybean (Glycine max) genetic breeding programs, in the Central Region of Brazil. Grain yield data of three maturity groups of soybean genotypes, from regional trials conducted over three years, at 18 locations in Brazilian Cerrado were used. A key location for the early phases of the breeding program was defined as the site that best classifies the winning genotypes in the region. Key locations for the final phases were defined as those sites that best represent each environmental stratum, in relation to the adaptability of the respective winning genotype. This adaptability was estimated by additive main effects and multiplicative interaction (AMMI) model analysis, using the distance between the score of each location in a stratum and the score of the winning genotype, which characterizes such stratum in an AMMI biplot. The locations that best classified the winning genotypes over space and time were Mineiros, Placas and Rio Verde. For the final phases of genotype selection, with data from the three maturity group, the recommended locations were: Buritis, Chapadão do Céu, Iraí, Pamplona, Placas, Planaltina, Rio Verde, Sacramento, Senador Canedo, Uberaba, and Uberlândia.
Highlights
Intensive management techniques for soybean (Glycine max L.) crop, allied to genetic breeding, have resulted in expressive increases in grain productivity
The environmental stratification into homogeneous groups leads to the need for identification of key locations within these groups, where the genotype tests should be prioritized in the selection phases of the plant breeding programs
(early, medium and late maturity groups, respectively). These tables show the_means of these distances in the three growing years (d2vj ), for each test location. Examination of these results allows the identification of the key location, for the final phases of the genotypic assessment related to the target populations of the genotypes and environments
Summary
Intensive management techniques for soybean (Glycine max L.) crop, allied to genetic breeding, have resulted in expressive increases in grain productivity. With the genetic breeding progress, research activities have become more expensive, requiring greater care and technical refinement. Bras., Brasília, v.44, n.5, p.478-486, maio 2009 the phenotypic variance of a set of genotypes submitted to different environmental conditions, or by the lack of correlation among genotype responses in the series of environments The occurrence of this phenomenon can lead to overestimations of the heritability value, because the GE interaction inflates the genotypic variance estimates with constant overvalue of the predicted gain with selection. It can result in productivity reduction of a region for which a general recommendation of a given cultivar is made
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