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| Registros recuperados : 116 | |
| 81. |  | SANCHÉZ, C. F. B.; ALVES, R. S.; GARCIA, A. d. P.; TEODORO, P. E.; PEIXOTO, L. A.; SILVA, L. A.; BHERING, L. L.; RESENDE, M. D. V. de. Estimates of repeatability coefficients and the number of the optimum measure to select superior genotypes in Annona muricata L. Genetics and Molecular Research, v. 16, n. 3, gmr16039753, 2017. 8 p.| Biblioteca(s): Embrapa Florestas. |
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| 82. | | CARVALHO, L. P. de; FARIAS, F. J. C.; RODRIGUES, J. I. S.; CASTRO, K. S.; ZUFFO, A. M.; TEODORO, P. E. Correlations and selection of parents to technological traits of upland cotton. Ciência Rural, v. 49, n. 6, e20180701, 2019. Título em português: Correlações e seleção de genitores para caracteres tecnológicos em algodoeiro herbáceo.| Biblioteca(s): Embrapa Algodão. |
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| 83. | | SILVA, K. J. da; TEODORO, P. E.; MENEZES, C. B. de; JÚLIO, M. P. M.; SOUZA, V. F. de; SILVA, M. J. da; PIMENTEL, L. D.; BORÉM, A. Contribution of morphoagronomic traits to grain yield and earliness in grain sorghum. Genetics and Molecular Research, Ribeirão Preto, v. 16, n. 2, p. 1-10, 2017.| Biblioteca(s): Embrapa Milho e Sorgo. |
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| 84. | | COSTA, A. F. da; TEODORO, P. E.; BHERING, L. L.; TARDIN, F. D.; DAHER, R. F.; CAMPOS, W. F.; VIANA, A. P.; PEREIRA, M. G. Molecular analysis of genetic diversity among vine accessions using DNA markers. Genetics and Molecular Research, Ribeirão Preto, v. 16, n. 2, p. 1-9, 2017.| Biblioteca(s): Embrapa Milho e Sorgo. |
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| 85. | | PEIXOTO, M. A.; EVANGELISTA, J. S. P. C.; ALVES, R. S.; FARIAS, F. J. C.; CARVALHO, L. P.; TEODORO, L. P. R.; TEODORO, P. E.; BHERING, L. L. Models for optimizing selection based on adaptability and stability of cotton genotypes. Ciência Rural, v. 51, n. 5, e20200530, p. 1-8, 2021. 8 p.| Biblioteca(s): Embrapa Algodão. |
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| 86. | | VOLPATO, L.; ALVES, R. S.; TEODORO, P. E.; RESENDE, M. D. V. de; NASCIMENTO, M.; NASCIMENTO, A. C. C.; LUDKE, W. H.; SILVA, F. L. da; BORÉM, A. Multi-trait multi-environment models in the genetic selection of segregating soybean progeny. PLoS ONE, v. 14, n. 4, e0215315, Apr. 2019. 22 p.| Biblioteca(s): Embrapa Florestas. |
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| 87. | | OLIVEIRA, T. B. de; PEIXOTO, L. de A.; TEODORO, P. E.; ALVARENGA, A. A. de; BHERING, L. L.; HOFFMANN-CAMPO, C. B. The number of measurements needed to obtain high reliability for traits related to enzymatic activities and photosynthetic compounds in soybean plants infected with Phakopsora pachyrhizi. Plos One, v. 13, n. 2, e0192189, 2018. 16 p.| Biblioteca(s): Embrapa Soja. |
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| 88. | | TEODORO, P. E.; JUNQUEIRA, V.; PEIXOTO, L. de A.; SPONCHIADO, S.; MENEZES, C. B. de; TARDIN, F. D.; BHERING, L. L. Predição de ganho genético em híbridos de sorgo utilizando modelo aditivo-materno multicaracterístico. In: CONGRESSO BRASILEIRO DE MELHORAMENTO DE PLANTAS, 9., 2017, Foz do Iguaçu. Melhoramento de plantas: projetando o futuro. Foz do Iguaçu: SBMP, 2017. p. 393.| Biblioteca(s): Embrapa Milho e Sorgo. |
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| 90. | | TARDIN, F. D.; RAMOS JUNIOR, E. U.; BROGIN, R. L.; GODINHO, V. de P. C.; BOTELHO, F. J. E.; TEODORO, P. E. Recomendação de genótipos de soja com alta estabilidade para o cerrado utilizando modelo AMMI. In: CONGRESSO BRASILEIRO DE MELHORAMENTO DE PLANTAS, 9., 2017, Foz do Iguaçu. Melhoramento de plantas: projetando o futuro. Foz do Iguaçu: SBMP, 2017. p. 420.| Biblioteca(s): Embrapa Milho e Sorgo; Embrapa Rondônia; Embrapa Soja. |
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| 91. | | RIBEIRO, L. P.; TEODORO, P. E.; LOPES, M. C.; SANTOS, A. dos; CORRÊA, C. C. G.; SILVA, F. A. da; TORRES, F. E. Quantifying the genetic divergence among maize hybrids using Ward-MLM strategy. Revista Brasileira de Milho e Sorgo, Sete Lagoas, v. 14, n. 3, p. 400-408, 2015.| Biblioteca(s): Embrapa Milho e Sorgo. |
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| 92. | | RODRIGUES, E. V.; LAVIOLA, B. G.; TEODORO, P. E.; COSTA, R. D.; LOPES, H. G. R.; COSTA, L. T. da; ALVES, A. A. Relações entre caracteres avaliados na fase juvenil e produtividade de grãos em pinhão-manso. In: CONGRESSO DA REDE BRASILEIRA DE TECNOLOGIA DE BIODIESEL, 6.; CONGRESSO BRASILEIRO DE PLANTAS OLEAGINOSAS, ÓLEOS, GORDURAS E BIODIESEL, 9., 2016, Natal, RN. Biodiesel: 10 anos de pesquisa, desenvolvimento e inovação no Brasil: anais. Lavras: UFLA, 2016. Não paginado.| Biblioteca(s): Embrapa Agroenergia. |
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| 93. | | OLIVEIRA, T. B. de; PEIXOTO, L. A.; TEODORO, P. E.; ALVARENGA, A. A. de; BHERING, L. L.; HOFFMANN-CAMPO, C. B. Relationship between biochemical and photosynthetic traits with Asian soybean rust. Anais da Academia Brasileira de Ciências, v. 90, n. 4, p. 3925-3940, 2018.| Biblioteca(s): Embrapa Soja. |
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| 94. | | SIMOES, W. L.; OLIVEIRA, A. R. de; TARDIN, F. D.; OLIVEIRA, C. P. M. de; MORAIS, L. K. de; TEODORO, L. P. R.; TEODORO, P. E. Saline stress affects the growth of Saccharum complex genotypes. Journal of Agronomy and Crop Science, v. 209, n. 5, p. 613-618, 2023.| Biblioteca(s): Embrapa Milho e Sorgo; Embrapa Semiárido; Embrapa Tabuleiros Costeiros. |
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| 95. | | TARDIN, F. D.; SPONCHIADO, S.; FERREIRA, L. U.; MENEZES, C. B. de; BALDONI, A. B.; BARELLI, M. A. A.; TEODORO, P. E. Seleção de genitores para a obtenção de híbridos de sorgo granífero com alto desempenho produtivo. In: CONGRESSO BRASILEIRO DE MELHORAMENTO DE PLANTAS, 9., 2017, Foz do Iguaçu. Melhoramento de plantas: projetando o futuro. Foz do Iguaçu: SBMP, 2017. p. 429.| Biblioteca(s): Embrapa Agrossilvipastoril. |
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| 96. | | TARDIN, F. D.; SPONCHIADO, S.; FERREIRA, L. U.; MENEZES, C. B. de; BALDONI, A. B.; BARELLI, M. A. A.; TEODORO, P. E. Seleção de genitores para a obtenção de híbridos de sorgo granífero com alto desempenho produtivo. In: CONGRESSO BRASILEIRO DE MELHORAMENTO DE PLANTAS, 9., 2017, Foz do Iguaçu. Melhoramento de plantas: projetando o futuro. Foz do Iguaçu: SBMP, 2017. p. 429.| Biblioteca(s): Embrapa Milho e Sorgo. |
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| 97. | | CORREA, A. M.; BRAGA, D. C.; CECCON, G.; OLIVEIRA, L. V. A. de; LIMA, A. R. de S.; TEODORO, P. E. Variabilidade genética e correlações entre caracteres de feijão-caupi. Agro@mbiente, v. 9, n. 1, p. 42-47, jan./mar, 2015.| Biblioteca(s): Embrapa Agropecuária Oeste. |
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| 98. | | BARROSO, L. M. A.; TEODORO, P. E.; NASCIMENTO, M.; TORRES, F. E.; SANTOS, A. dos; CORRÊA, A. M.; SAGRILO, E.; CORRÊA, C. C. G.; SILVA, F. A.; CECCON, G. Bayesian approach increases accuracy when selecting cowpea genotypes with high adaptability and phenotypic stability. Genetics and Molecular Research, v. 15, n. 1, p. 1-11, 2016.| Biblioteca(s): Embrapa Agropecuária Oeste; Embrapa Meio-Norte. |
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| 99. | | RODRIGUES, E. V.; ROCHA, J. R. do A. S. de C.; ALVES, R. S.; TEODORO, P. E.; LAVIOLA, B. G.; RESENDE, M. D. V. de; CARNEIRO, P. C. S.; BHERING, L. L. Selection of Jatropha genotypes for bioenergy purpose: an approach with multitrait, multiharvest and effective population size. Bragantia, Campinas, v. 79, n.3, Jul./Sept. 2020.| Biblioteca(s): Embrapa Agroenergia. |
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| 100. | | LAVIOLA, B. G.; SANTOS, A. dos; RODRIGUES, E. V.; TEODORO, L. P. R.; TEODORO, P. E.; ROSADO, T. B.; GUIMARÃES, C. G.; CONCEIÇÃO, L. D. H. C. S. DA. Structure and genetic diversity of macauba [Acrocomia aculeata (Jacq.) Lodd. ex Mart.] approached by SNP markers to assist breeding strategies. Genetic Resources and Crop Evolution, v. 69, p. 1179-1191, Nov. 2021. 13 p. PDF: il. color.| Biblioteca(s): Embrapa Agroenergia; Embrapa Uva e Vinho. |
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| Registros recuperados : 116 | |
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Registro Completo
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Biblioteca(s): |
Embrapa Algodão. |
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Data corrente: |
26/01/2023 |
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Data da última atualização: |
30/01/2023 |
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Tipo da produção científica: |
Artigo em Periódico Indexado |
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Circulação/Nível: |
A - 2 |
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Autoria: |
PEIXOTO, M. A.; EVANGELISTA, J. S. P. C.; COELHO, I. F.; CARVALHO, L. P. de; FARIAS, F. J. C.; TEODORO, P. E.; BHERING, L. L. |
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Afiliação: |
MARCO ANTÔNIO PEIXOTO, UNIVERSIDADE FEDERAL DE VIÇOSA; JENIFFER SANTANA PINTO COELHO EVANGELISTA, UNIVERSIDADE FEDERAL DE VIÇOSA; IGOR FERREIRA COELHO, UNIVERSIDADE FEDERAL DE VIÇOSA; LUIZ PAULO DE CARVALHO, CNPA; FRANCISCO JOSE CORREIA FARIAS, CNPA; PAULO EDUARDO TEODORO, UNIVERSIDADE FEDERAL DE MATO GROSSO DO SUL; LEONARDO LOPES BHERING, UNIVERSIDADE FEDERAL DE VIÇOSA. |
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Título: |
Genotype selection based on multiple traits in cotton crops: the application of genotype by yield trait biplot. |
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Ano de publicação: |
2022 |
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Fonte/Imprenta: |
Acta Scientiarum. Agronomy, v. 44, e54136, 2022. |
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ISSN: |
1807-8621 |
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DOI: |
10.4025/actasciagron.v44i1.54136 |
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Idioma: |
Inglês |
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Conteúdo: |
ABSTRACT - In cotton crops, the cotton seed yield significantly contributes with the success of any cultivar. However, other traits are considered when an ideotype is pointed out in the selection, such as the fiber quality traits. The aim of this study was to applied genotype by yield*trait (GYT) biplot to a multi-environment trial data of cotton genotypes and selected the best genotypes. For this end, thirteen genotypes from nineteen trials were assessed. Seven traits were evaluated [cotton seed yield (SY), fiber percentage (FP), fiber length (FL), fiber uniformity (FU), short fiber index (SFI), fiber strength (FS), and elongation (EL)] and residual error variances structures [identity variance (IDV) and diagonal (Diag)] were tested by bayesian information criterion. After, the REML/BLUP approach was applied to predict the genetic values of each trait and the selective accuracy were measured from the prediction. Then, the GYT-biplot were applied to the data. For SP and SFI traits, the model with Diag residual variance was indicated, whereas for SY FL, FU, FS, and EL traits the model with IDV residual variance demonstrated the best fit to the data. Values of accuracy were higher than 0.9 for all traits analyzed. In the GYT-biplot acute angles were find for all traits relations, which means high correlation between the yield*traits combination. Besides that, the correlation still can be seen in the GYT-biplot, as shown by the magnitudes of the angles between the pairs Yield*FU-Yield*FS and Yield*FS-Yield*EL. Also, the GYT-biplot indicates the genotype G4 with the best performance for Yield*FS, Yield*SFI, Yield*FU, Yield*FL, and Yield*FP combined. The genotypes G4, G1, G13, G8, and G9 represent those genotypes with yield advantage over the other cultivars. Then, the genotype G4 combines all desirable characteristics and demonstrate have large potential in the cotton breeding. The GYT approach were valuable and were highly recommended in cotton breeding programs for selection purpose in a multivariate scenario. MenosABSTRACT - In cotton crops, the cotton seed yield significantly contributes with the success of any cultivar. However, other traits are considered when an ideotype is pointed out in the selection, such as the fiber quality traits. The aim of this study was to applied genotype by yield*trait (GYT) biplot to a multi-environment trial data of cotton genotypes and selected the best genotypes. For this end, thirteen genotypes from nineteen trials were assessed. Seven traits were evaluated [cotton seed yield (SY), fiber percentage (FP), fiber length (FL), fiber uniformity (FU), short fiber index (SFI), fiber strength (FS), and elongation (EL)] and residual error variances structures [identity variance (IDV) and diagonal (Diag)] were tested by bayesian information criterion. After, the REML/BLUP approach was applied to predict the genetic values of each trait and the selective accuracy were measured from the prediction. Then, the GYT-biplot were applied to the data. For SP and SFI traits, the model with Diag residual variance was indicated, whereas for SY FL, FU, FS, and EL traits the model with IDV residual variance demonstrated the best fit to the data. Values of accuracy were higher than 0.9 for all traits analyzed. In the GYT-biplot acute angles were find for all traits relations, which means high correlation between the yield*traits combination. Besides that, the correlation still can be seen in the GYT-biplot, as shown by the magnitudes of the angles between the pairs Yield*F... Mostrar Tudo |
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Thesagro: |
Algodão; Análise Estatística; Genótipo; Gossypium Hirsutum. |
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Thesaurus NAL: |
Cotton; Cultivars; Genotype; Seed cotton. |
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Categoria do assunto: |
-- |
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URL: |
https://ainfo.cnptia.embrapa.br/digital/bitstream/doc/1151251/1/Genotype-selection-based-multiple-2022.pdf
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Marc: |
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245 $aGenotype selection based on multiple traits in cotton crops$bthe application of genotype by yield trait biplot.$h[electronic resource]
260 $c2022
520 $aABSTRACT - In cotton crops, the cotton seed yield significantly contributes with the success of any cultivar. However, other traits are considered when an ideotype is pointed out in the selection, such as the fiber quality traits. The aim of this study was to applied genotype by yield*trait (GYT) biplot to a multi-environment trial data of cotton genotypes and selected the best genotypes. For this end, thirteen genotypes from nineteen trials were assessed. Seven traits were evaluated [cotton seed yield (SY), fiber percentage (FP), fiber length (FL), fiber uniformity (FU), short fiber index (SFI), fiber strength (FS), and elongation (EL)] and residual error variances structures [identity variance (IDV) and diagonal (Diag)] were tested by bayesian information criterion. After, the REML/BLUP approach was applied to predict the genetic values of each trait and the selective accuracy were measured from the prediction. Then, the GYT-biplot were applied to the data. For SP and SFI traits, the model with Diag residual variance was indicated, whereas for SY FL, FU, FS, and EL traits the model with IDV residual variance demonstrated the best fit to the data. Values of accuracy were higher than 0.9 for all traits analyzed. In the GYT-biplot acute angles were find for all traits relations, which means high correlation between the yield*traits combination. Besides that, the correlation still can be seen in the GYT-biplot, as shown by the magnitudes of the angles between the pairs Yield*FU-Yield*FS and Yield*FS-Yield*EL. Also, the GYT-biplot indicates the genotype G4 with the best performance for Yield*FS, Yield*SFI, Yield*FU, Yield*FL, and Yield*FP combined. The genotypes G4, G1, G13, G8, and G9 represent those genotypes with yield advantage over the other cultivars. Then, the genotype G4 combines all desirable characteristics and demonstrate have large potential in the cotton breeding. The GYT approach were valuable and were highly recommended in cotton breeding programs for selection purpose in a multivariate scenario.
650 $aCotton
650 $aCultivars
650 $aGenotype
650 $aSeed cotton
650 $aAlgodão
650 $aAnálise Estatística
650 $aGenótipo
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700 1 $aFARIAS, F. J. C.
700 1 $aTEODORO, P. E.
700 1 $aBHERING, L. L.
773 $tActa Scientiarum. Agronomy$gv. 44, e54136, 2022.
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Embrapa Algodão (CNPA) |
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