Author(s): SILVA, K. J. da; TEODORO, P. E.; SILVA, M. J. da; TEODORO, L. P. R.; CARDOSO, M. J.; GODINHO, V. de P. C.; MOTA, J. H.; SIMON, G. A.; TARDIN, F. D.; SILVA, A. R. da; GUEDES, F. L.; MENEZES, C. B. de

Summary: The performance of genotypes in a wide range of environments can be affected by extensive genotype × environment (G × E) interactions, making the subdivision of the testing environments into relatively more homogeneous groups of locations (mega-environments) a necessary strategy. The genotype main effects + genotype × environment interaction biplot method (GGE) allows identification of megaenvironments and selection of stable genotypes adapted to specific environments and mega-environments. The objectives of this study were to identify mega-environments regarding sorghum [Sorghum bicolor (L.) Moench] grain yield and demonstrate that the GGE biplot method can identify essential locations for conducting tests in different mega-environments. A total of 22 competition trials of grain sorghum genotypes were conducted over three crop seasons across several production locations in Brazil. A total of 25, 22, and 30 genotypes were evaluated during the first, second, and third crop seasons, respectively. After identifying the presence of G × E interactions, the data were subjected to adaptability and stability analyses using the GGE biplot method. A phenotypic correlation network was used to express functional relationships between environments. The GGE biplot was found to be an efficient approach for identifying three mega-environments in grain sorghum in Brazil, selecting representative and discriminative environments, and recommending more adaptive and stable grain sorghum genotypes

Publication year: 2021

Types of publication: Journal article

Unit: Embrapa Mid-North

Keywords: Genótipo, Grão, Método biplot, Rendimento, Sorgo