Título:	Identification of mega-environments for grain sorghum in Brazil using GGE biplot methodology.
Autoria:	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
Afiliação:	KARLA JORGE DA SILVA; PAULO EDUARDO TEODORO, Universidade Federal de Mato Grosso do Sul; MICHELE JORGE DA SILVA, Universidade Federal de Viçosa; LARISSA PEREIRA RIBEIRO TEODORO, Universidade Federal de Mato Grosso do Sul; MILTON JOSE CARDOSO, CPAMN; VICENTE DE PAULO CAMPOS GODINHO, CPAF-RO; JOSÉ HORTÊNCIO MOTA, Universidade Federal de Jataí; GUSTAVO ANDRÉ SIMON, Universidade de Rio Verde; FLAVIO DESSAUNE TARDIN, CNPMS; ADELMO RESENDE DA SILVA, CNPMS; FERNANDO LISBOA GUEDES, CNPC; CICERO BESERRA DE MENEZES, CNPMS.
Ano de publicação:	2021
Referência:	Agronomy Journal, v. 113, n. 4, p. 3019-3030, Jul./Aug. 2021.
Conteúdo:	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
Thesagro:	Sorgo Genótipo Rendimento Grão
Palavras-chave:	Método biplot
Digital Object Identifier:	https://doi.org/10.1002/agj2.20707
Tipo do material:	Artigo de periódico
Acesso:	openAccess
Aparece nas coleções:	Artigo em periódico indexado (CPAMN)