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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: |
null
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Registro original: |
Embrapa Arroz e Feijão (CNPAF) |
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| 2. |  | PEREIRA, V. A.; FORTE, J. M.; ARRUDA-JÚNIOR, J. P. V.; DINIZ, F. M.; MAGGIONI, R.; SALMITO-VANDERLEY, C. S. B. Identification and characterization of microsatellite loci in West Atlantic sea cucumber Holothuria grisea (Selenka 1867). Journal of Genetics, v. 97, n. 5, p. 1363-1369, Dec. 2018.| Tipo: Artigo em Periódico Indexado | Circulação/Nível: B - 1 |
| Biblioteca(s): Embrapa Caprinos e Ovinos. |
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| 3. | | FREITAS, V. J. F.; LOPES-JUNIOR, E. S.; RONDINA, D.; SALMITO-VANDERLEY, C. S. B.; SALLES, H. O.; SIMPLÍCIO, A. A.; BARIL, G.; SAUMANDE, J. Puberty in Anglo-Nubian and Saanen female kids raised in the semi-arid of North-eastern Brazil. Small Ruminant Research, v. 53, n. 1/2, p. 167-172, 2004. Technical note.| Tipo: Nota Técnica/Nota Científica |
| Biblioteca(s): Embrapa Caprinos e Ovinos. |
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| 4. | | LEAL, T. M.; NUNES, J. F.; SALGUEIRO, C. C. de M.; SALMITO-VANDERLEY, C. S. B.; VIEIRA, R. J.; NASCIMENTO, M. do P. S. C. B.; MOURA, A. de A. A. Retorno ao estro pós-parto em ovelhas da raça Santa Inês: influência do manejo alimentar e da amamentação. In: XIMENES, L. J. F.; MARTINS, G. A.; MORAIS, O. R. de; COSTA, L. S. de A.; NASCIMENTO, J. L. S. do. Ciência e tecnologia na pecuária de caprinos e ovinos. Fortaleza: Banco do Nordeste do Brasil, 2010. Cap. 23. p. 559-574. (Série BNB. Ciência e Tecnologia, 5). Na publicação autoria: LELEAL [i.e. LEAL], T. M.; TÂNIA MARIA LELEAL[i.e. LEAL].| Tipo: Capítulo em Livro Técnico-Científico |
| Biblioteca(s): Embrapa Meio-Norte. |
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| Registros recuperados : 4 | |
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