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| Registros recuperados : 116 | |
| 10. |  | BALDONI, A. B.; TONINI, H.; TARDIN, F. D.; BOTELHO, S. C. C.; TEODORO, P. E. Minimum number of measurements for evaluating Bertholletia excelsa. Genetics and Molecular Research, Ribeirão Preto, v. 16, n. 3, p. 1-10, 2017. Artigo - gmr16039783.| Biblioteca(s): Embrapa Agrossilvipastoril; Embrapa Milho e Sorgo. |
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| 18. | | TEODORO, P. E.; COSTA, R. D.; ROCHA, R. B.; LAVIOLA, B. G. Número mínimo de medições para a avaliação acurada de características agronômicas de pinhão-manso. Pesquisa Agropecuária Brasileira, Brasília, DF, v. 51, n. 2, p. 112-119, fev. 2016| Biblioteca(s): Embrapa Rondônia; Embrapa Unidades Centrais. |
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| 19. | | TORRES, F. E.; SAGRILO, E.; TEODORO, P. E.; RIBEIRO, L. P.; CARGNELUTTI FILHO, A. Número de repetições para avaliação de caracteres em genótipos de feijão-caupi. Bragantia, Campinas, v. 74, n. 2, p. 161-168, 2015.| Biblioteca(s): Embrapa Meio-Norte. |
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| 20. | | TEODORO, P. E.; NASCIMENTO, M.; TORRES, F. E.; BARROSO, L. M. A.; SAGRILO, E. Perspectiva bayesiana na seleção de genótipos de feijão-caupi em ensaios de valor de cultivo e uso. Pesquisa Agropecuária Brasileira, Brasília, DF, v. 50, n. 10, p. 878-885, out. 2015.| Biblioteca(s): Embrapa Meio-Norte; Embrapa Unidades Centrais. |
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| Registros recuperados : 116 | |
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Registro Completo
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Biblioteca(s): |
Embrapa Caprinos e Ovinos; Embrapa Meio-Norte; Embrapa Milho e Sorgo; Embrapa Rondônia. |
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Data corrente: |
07/06/2021 |
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Data da última atualização: |
15/12/2021 |
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Tipo da produção científica: |
Artigo em Periódico Indexado |
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Circulação/Nível: |
A - 1 |
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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. |
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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. |
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Título: |
Identification of mega-environments for grain sorghum in Brazil using GGE biplot methodology. |
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Ano de publicação: |
2021 |
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Fonte/Imprenta: |
Agronomy Journal, v. 113, n. 4, p. 3019-3030, Jul./Aug. 2021. |
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DOI: |
https://doi.org/10.1002/agj2.20707 |
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Idioma: |
Inglês |
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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 |
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Palavras-Chave: |
Método biplot. |
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Thesagro: |
Genótipo; Grão; Rendimento; Sorgo. |
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Categoria do assunto: |
F Plantas e Produtos de Origem Vegetal |
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URL: |
https://ainfo.cnptia.embrapa.br/digital/bitstream/item/229158/1/Identification-of-megau2010environments-for-grain-sorghum-in-Brazil-using-GGE-biplot.pdf
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Marc: |
LEADER 02439naa a2200325 a 4500
001 2137820
005 2021-12-15
008 2021 bl uuuu u00u1 u #d
024 7 $ahttps://doi.org/10.1002/agj2.20707$2DOI
100 1 $aSILVA, K. J. da
245 $aIdentification of mega-environments for grain sorghum in Brazil using GGE biplot methodology.$h[electronic resource]
260 $c2021
520 $aThe 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
650 $aGenótipo
650 $aGrão
650 $aRendimento
650 $aSorgo
653 $aMétodo biplot
700 1 $aTEODORO, P. E.
700 1 $aSILVA, M. J. da
700 1 $aTEODORO, L. P. R.
700 1 $aCARDOSO, M. J.
700 1 $aGODINHO, V. de P. C.
700 1 $aMOTA, J. H.
700 1 $aSIMON, G. A.
700 1 $aTARDIN, F. D.
700 1 $aSILVA, A. R. da
700 1 $aGUEDES, F. L.
700 1 $aMENEZES, C. B. de
773 $tAgronomy Journal$gv. 113, n. 4, p. 3019-3030, Jul./Aug. 2021.
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Embrapa Meio-Norte (CPAMN) |
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