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dc.contributor.authorSILVA, K. J. da
dc.contributor.authorTEODORO, P. E.
dc.contributor.authorSILVA, M. J. da
dc.contributor.authorTEODORO, L. P. R.
dc.contributor.authorCARDOSO, M. J.
dc.contributor.authorGODINHO, V. de P. C.
dc.contributor.authorMOTA, J. H.
dc.contributor.authorSIMON, G. A.
dc.contributor.authorTARDIN, F. D.
dc.contributor.authorSILVA, A. R. da
dc.contributor.authorGUEDES, F. L.
dc.contributor.authorMENEZES, C. B. de
dc.date.accessioned2021-12-15T12:06:58Z-
dc.date.available2021-12-15T12:06:58Z-
dc.date.created2021-12-15
dc.date.issued2021
dc.identifier.citationAgronomy Journal, v. 113, n. 4, p. 3019-3030, Jul./Aug. 2021.
dc.identifier.urihttp://www.alice.cnptia.embrapa.br/alice/handle/doc/1137820-
dc.descriptionThe 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
dc.language.isoeng
dc.rightsopenAccesseng
dc.subjectMétodo biplot
dc.titleIdentification of mega-environments for grain sorghum in Brazil using GGE biplot methodology.
dc.typeArtigo de periódico
dc.subject.thesagroSorgo
dc.subject.thesagroGenótipo
dc.subject.thesagroRendimento
dc.subject.thesagroGrão
riaa.ainfo.id1137820
riaa.ainfo.lastupdate2021-12-15
dc.identifier.doihttps://doi.org/10.1002/agj2.20707
dc.contributor.institutionKARLA 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.
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