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 | Acesso ao texto completo restrito à biblioteca da Embrapa Arroz e Feijão. Para informações adicionais entre em contato com cnpaf.biblioteca@embrapa.br. |
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Registro Completo |
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Biblioteca(s): |
Embrapa Arroz e Feijão. |
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Data corrente: |
26/07/2023 |
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Data da última atualização: |
02/08/2023 |
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Tipo da produção científica: |
Artigo em Periódico Indexado |
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Autoria: |
MORAIS JUNIOR, O. P.; MÜLLER, B. S. F.; VALDISSER, P. A. M. R.; BRONDANI, C.; VIANELLO, R. P. |
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Afiliação: |
ODILON PEIXOTO MORAIS JUNIOR, UNIVERSIDADE FEDERAL DE GOIÁS; BÁRBARA S. F. MÜLLER, UNIVERSITY OF FLORIDA, Gainesville, FL; PAULA ARIELLE M RIBEIRO VALDISSER, CNPAF; CLAUDIO BRONDANI, CNPAF; ROSANA PEREIRA VIANELLO, CNPAF. |
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Título: |
Genomic prediction for drought tolerance using multienvironment data in a common bean (Phaseolus vulgaris) breeding program. |
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Ano de publicação: |
2023 |
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Fonte/Imprenta: |
Crop Science, v. 63, n. 4, p. 2145-2161, July/Aug. 2023. |
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ISSN: |
0011-183X |
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DOI: |
https://doi.org/10.1002/csc2.21000 |
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Idioma: |
Inglês |
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Conteúdo: |
This work evaluated the efficiency of different genomic prediction (GP) methods in a diverse Mesoamerican panel of 339 common bean accessions, genotyped with 3398 SNP markers. Field experiments were carried out for three consecutive years, with adequate water supply (non-stress?NS) and water restriction imposition (water-stress?WS), analyzing seed weight (SW) and grain yield (GY). Two methods to predict the accuracies (r?g) were adopted (GBLUP and Bayes) and also considered the environmental variation (GBLUP-based reaction norm model). Similar accuracies were observed for both methods. For GY, the highest r?g were detected under NS (rgg = 0.49) in 2016 (r?g = 0.49) and in the joint analysis for the WS condition (rgg = 0.33), both for models using local landraces. For SW under NS, the rgg was higher for the elite lines (rgg = 0.72), whereas for WS, the rgg dropped considerably, ranging from 0.45 to 0.61 for the joint analysis, considering the landraces and all samples, respectively. For GY and SW, under NS, the rgg using both models increased with increasing number of SNPs, until reaching a plateau of 800 and 300 SNPs, respectively. Increasing the training population (TP) size resulted in greater accuracy. Taking in account the Genotype × Environment, the multienvironment model performed better especially for more complex traits (GY/NS: rgg = 0.32). The GP approach has great potential to help commercial bean breeding programs improving the performance of target quantitative traits. MenosThis work evaluated the efficiency of different genomic prediction (GP) methods in a diverse Mesoamerican panel of 339 common bean accessions, genotyped with 3398 SNP markers. Field experiments were carried out for three consecutive years, with adequate water supply (non-stress?NS) and water restriction imposition (water-stress?WS), analyzing seed weight (SW) and grain yield (GY). Two methods to predict the accuracies (r?g) were adopted (GBLUP and Bayes) and also considered the environmental variation (GBLUP-based reaction norm model). Similar accuracies were observed for both methods. For GY, the highest r?g were detected under NS (rgg = 0.49) in 2016 (r?g = 0.49) and in the joint analysis for the WS condition (rgg = 0.33), both for models using local landraces. For SW under NS, the rgg was higher for the elite lines (rgg = 0.72), whereas for WS, the rgg dropped considerably, ranging from 0.45 to 0.61 for the joint analysis, considering the landraces and all samples, respectively. For GY and SW, under NS, the rgg using both models increased with increasing number of SNPs, until reaching a plateau of 800 and 300 SNPs, respectively. Increasing the training population (TP) size resulted in greater accuracy. Taking in account the Genotype × Environment, the multienvironment model performed better especially for more complex traits (GY/NS: rgg = 0.32). The GP approach has great potential to help commercial bean breeding programs improving the performance of target quantitative t... Mostrar Tudo |
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Thesagro: |
Feijão; Melhoramento Genético Vegetal; Phaseolus Vulgaris; Resistência a Seca. |
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Thesaurus Nal: |
Beans; Breeding and Genetic Improvement; Drought tolerance; Genomics. |
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Categoria do assunto: |
G Melhoramento Genético |
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Marc: |
LEADER 02428naa a2200289 a 4500
001 2155303
005 2023-08-02
008 2023 bl uuuu u00u1 u #d
022 $a0011-183X
024 7 $ahttps://doi.org/10.1002/csc2.21000$2DOI
100 1 $aMORAIS JUNIOR, O. P.
245 $aGenomic prediction for drought tolerance using multienvironment data in a common bean (Phaseolus vulgaris) breeding program.$h[electronic resource]
260 $c2023
520 $aThis work evaluated the efficiency of different genomic prediction (GP) methods in a diverse Mesoamerican panel of 339 common bean accessions, genotyped with 3398 SNP markers. Field experiments were carried out for three consecutive years, with adequate water supply (non-stress?NS) and water restriction imposition (water-stress?WS), analyzing seed weight (SW) and grain yield (GY). Two methods to predict the accuracies (r?g) were adopted (GBLUP and Bayes) and also considered the environmental variation (GBLUP-based reaction norm model). Similar accuracies were observed for both methods. For GY, the highest r?g were detected under NS (rgg = 0.49) in 2016 (r?g = 0.49) and in the joint analysis for the WS condition (rgg = 0.33), both for models using local landraces. For SW under NS, the rgg was higher for the elite lines (rgg = 0.72), whereas for WS, the rgg dropped considerably, ranging from 0.45 to 0.61 for the joint analysis, considering the landraces and all samples, respectively. For GY and SW, under NS, the rgg using both models increased with increasing number of SNPs, until reaching a plateau of 800 and 300 SNPs, respectively. Increasing the training population (TP) size resulted in greater accuracy. Taking in account the Genotype × Environment, the multienvironment model performed better especially for more complex traits (GY/NS: rgg = 0.32). The GP approach has great potential to help commercial bean breeding programs improving the performance of target quantitative traits.
650 $aBeans
650 $aBreeding and Genetic Improvement
650 $aDrought tolerance
650 $aGenomics
650 $aFeijão
650 $aMelhoramento Genético Vegetal
650 $aPhaseolus Vulgaris
650 $aResistência a Seca
700 1 $aMÜLLER, B. S. F.
700 1 $aVALDISSER, P. A. M. R.
700 1 $aBRONDANI, C.
700 1 $aVIANELLO, R. P.
773 $tCrop Science$gv. 63, n. 4, p. 2145-2161, July/Aug. 2023.
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Registro original: |
Embrapa Arroz e Feijão (CNPAF) |
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| Registros recuperados : 3 | |
| 1. |  | FERREIRA, T.; OLIVEIRA, T. C.; LIMA, I. S.; MORAIS, A. C. F.; FARAH, A.; OLIVEIRA, E. M. M. Desenvolvimento de método biomolecular para detecção e quantificação de arroz em amostras de café através do Sistema TaqMan. In: CONGRESSO BRASILEIRO DE CIÊNCIA E TECNOLOGIA DE ALIMENTOS, 25.; CIGR SESSION 6 INTERNATIONAL TECHNICAL SYMPOSIUM, 10., 2016, Gramado. Alimentação: árvore que sustenta a vida. Anais. Gramado: SBCTA Regional, 2016. 6 p.| Tipo: Artigo em Anais de Congresso |
| Biblioteca(s): Embrapa Agroindústria de Alimentos. |
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| 2. | | FRANCA, T. C. de O.; SOUZA, A. M. de; SANTOS, T. F. dos; LIMA, I. S. de; MORAIS, A. C. F. de; PEREIRA, A. F. de M.; OLIVEIRA, E. M. M. Desenvolvimento de método biomolecular para detecção e quantificação de arroz em amostras de café através dos sistema TAQMAN. In: CORDEIRO, A. M.; EVANGELISTA-BARRETO, N. S. (org.). Ciência e Tecnologia de Alimentos: o avanço da ciência no Brasil. Guarujá, SP: Científica Digital, 2023. v. 3, cap. 12, p. 157-170.| Tipo: Capítulo em Livro Técnico-Científico |
| Biblioteca(s): Embrapa Agroindústria de Alimentos. |
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| 3. | | MAMEDE, A. M. G. N.; PEREIRA, M. da S. G.; SANTOS, T. F. dos; OLIVEIRA, T. C. de; LIMA, I. S. de; MORAIS, A. C. F. de; SOUZA, A. M. de; FREITAS-SILVA, O.; OLIVEIRA, E. M. M. Efeito dos níveis de torra na cor e no rendimento da extração de DNA em cafés. In: SIMPÓSIO DE PESQUISA DOS CAFÉS DO BRASIL, 9., 2015, Curitiba. Consórcio pesquisa café: oportunidades e novos desafios: anais. Brasília, DF: Embrapa Café, 2015. 5 p. 1 CD-ROM.| Tipo: Artigo em Anais de Congresso |
| Biblioteca(s): Embrapa Agroindústria de Alimentos. |
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| Registros recuperados : 3 | |
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| Nenhum registro encontrado para a expressão de busca informada. |
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