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 | Acesso ao texto completo restrito à biblioteca da Embrapa Mandioca e Fruticultura. Para informações adicionais entre em contato com cnpmf.biblioteca@embrapa.br. |
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Registro Completo |
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Biblioteca(s): |
Embrapa Mandioca e Fruticultura. |
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Data corrente: |
15/10/2019 |
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Data da última atualização: |
15/10/2019 |
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Tipo da produção científica: |
Artigo em Periódico Indexado |
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Autoria: |
SILVA, P. P. dos S.; SOUSA, M. B. e; OLIVEIRA, E. J. de. |
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Afiliação: |
PRISCILA PATRÍCIA DOS SANTOS SILVA, UFRB; MASSAINE BANDEIRA E SOUSA, UFRB; EDER JORGE DE OLIVEIRA, CNPMF. |
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Título: |
Prediction models and selection of agronomic and physiological traits for tolerance to water deficit in cassava. |
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Ano de publicação: |
2019 |
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Fonte/Imprenta: |
Euphytica, v.215, n.73, 2019. |
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ISSN: |
1573-5060 |
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DOI: |
https://doi.org/10.1007/s10681-019-2399-0(0123456789().,-volV()0123456789().,-volV) |
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Idioma: |
Inglês |
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Conteúdo: |
The development of efficient and accurate strategies for evaluating and predicting the root yield of cassava (Manihot esculenta Crantz) can reduce the effort and time spent on phenotyping complex traits associated with productivity and abiotic stress. The objective of this study was to select phenotypic traits that are highly associated with fresh root yield (FRY) as well as to establish a prediction model of the performance of genotypes under water deficit conditions. A total of 49 cassava genotypes were evaluated in a complete randomized block design, with three replications and two water conditions: well-watered (control-WW) and water deficit. The physiological and agronomic traits were divided into three groups: Phys (all physiological traits); Phys?+?ShY (all physiological traits, with addition of shoot yield) and Phys?+?Agro (all physiological and agronomic traits). They were evaluated using six different predictive models: classification and regression trees, artificial neural network, support vector machines, extreme learning machine (ELM), generalized linear model with stepwise feature selection (GLMSS) and partial least squares (PLS). These same groups, but reduced to only the most important predictive traits, were also analyzed. The most important traits for predicting FRY were number of roots per plant, leaf area index, number of leaves measured in the eighth month, and shoot yield. The selection of the most important traits resulted in the best adjustment of the models, with GLMSS, ELM, and PLS being the models that presented the highest reliability of prediction according to the values of r2?>?0.75 with RMSE ranging from 0.49 to 0.51. MenosThe development of efficient and accurate strategies for evaluating and predicting the root yield of cassava (Manihot esculenta Crantz) can reduce the effort and time spent on phenotyping complex traits associated with productivity and abiotic stress. The objective of this study was to select phenotypic traits that are highly associated with fresh root yield (FRY) as well as to establish a prediction model of the performance of genotypes under water deficit conditions. A total of 49 cassava genotypes were evaluated in a complete randomized block design, with three replications and two water conditions: well-watered (control-WW) and water deficit. The physiological and agronomic traits were divided into three groups: Phys (all physiological traits); Phys?+?ShY (all physiological traits, with addition of shoot yield) and Phys?+?Agro (all physiological and agronomic traits). They were evaluated using six different predictive models: classification and regression trees, artificial neural network, support vector machines, extreme learning machine (ELM), generalized linear model with stepwise feature selection (GLMSS) and partial least squares (PLS). These same groups, but reduced to only the most important predictive traits, were also analyzed. The most important traits for predicting FRY were number of roots per plant, leaf area index, number of leaves measured in the eighth month, and shoot yield. The selection of the most important traits resulted in the best adjustment of the... Mostrar Tudo |
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Thesagro: |
Mandioca. |
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Thesaurus Nal: |
Cassava. |
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Categoria do assunto: |
-- |
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Marc: |
LEADER 02318naa a2200193 a 4500
001 2113130
005 2019-10-15
008 2019 bl uuuu u00u1 u #d
022 $a1573-5060
024 7 $ahttps://doi.org/10.1007/s10681-019-2399-0(0123456789().,-volV()0123456789().,-volV)$2DOI
100 1 $aSILVA, P. P. dos S.
245 $aPrediction models and selection of agronomic and physiological traits for tolerance to water deficit in cassava.$h[electronic resource]
260 $c2019
520 $aThe development of efficient and accurate strategies for evaluating and predicting the root yield of cassava (Manihot esculenta Crantz) can reduce the effort and time spent on phenotyping complex traits associated with productivity and abiotic stress. The objective of this study was to select phenotypic traits that are highly associated with fresh root yield (FRY) as well as to establish a prediction model of the performance of genotypes under water deficit conditions. A total of 49 cassava genotypes were evaluated in a complete randomized block design, with three replications and two water conditions: well-watered (control-WW) and water deficit. The physiological and agronomic traits were divided into three groups: Phys (all physiological traits); Phys?+?ShY (all physiological traits, with addition of shoot yield) and Phys?+?Agro (all physiological and agronomic traits). They were evaluated using six different predictive models: classification and regression trees, artificial neural network, support vector machines, extreme learning machine (ELM), generalized linear model with stepwise feature selection (GLMSS) and partial least squares (PLS). These same groups, but reduced to only the most important predictive traits, were also analyzed. The most important traits for predicting FRY were number of roots per plant, leaf area index, number of leaves measured in the eighth month, and shoot yield. The selection of the most important traits resulted in the best adjustment of the models, with GLMSS, ELM, and PLS being the models that presented the highest reliability of prediction according to the values of r2?>?0.75 with RMSE ranging from 0.49 to 0.51.
650 $aCassava
650 $aMandioca
700 1 $aSOUSA, M. B. e
700 1 $aOLIVEIRA, E. J. de
773 $tEuphytica$gv.215, n.73, 2019.
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Registro original: |
Embrapa Mandioca e Fruticultura (CNPMF) |
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| Registros recuperados : 38 | |
| 6. |  | SOUSA, M. B. e; SILVA, K. J. D. e; ROCHA, M. de M.; NEVES, A. C. das. Estimativas de parâmetros genéticos em linhagens de feijão-caupi nos municípios de Balsas, MA e Primavera do Leste, MT. In: CONGRESSO NACIONAL DE FEIJÃO-CAUPI, 3., 2013, Recife. Feijão-Caupi como alternativa sustentável para os sistemas produtivos familiares e empresariais. Recife: IPA, 2013. CONAC 2012. Disponível em: http://www.conac2012.org/resumos/pdf/132a.pdf. Acesso em: 22 jul. 2013.| Tipo: Artigo em Anais de Congresso |
| Biblioteca(s): Embrapa Meio-Norte. |
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| 7. | | SILVA, E. M. da; DINIZ, R. P.; SOUSA, M. B. e; BRAATZ, L. R.; OLIVEIRA, E. J. de. Geração de clones superiores de mandioca em progênies F1, S1 e S2 In: JORNADA CIENTÍFICA EMBRAPA MANDIOCA E FRUTICULTURA, 13., 2019. Foco e valor : resumos. Cruz das Almas, BA: Embrapa Mandioca e Fruticultura,2019. 119 p. il.| Tipo: Resumo em Anais de Congresso |
| Biblioteca(s): Embrapa Mandioca e Fruticultura. |
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| 13. | | SOUSA, M. B. e; SILVA, K. J. D. e; ROCHA, M. de M.; MENEZES JUNIOR, J. A. de; LIMA, L. R. L. Adaptabilidade e estabilidade produtiva em linhagens elite de feijão-caupi de porte semiprostrado no Cerrado do Brasil. In: CONGRESSO NACIONAL DE FEIJÃO-CAUPI, 4., 2016, Sorriso. Feijão-caupi: avanços e desafios tecnológicos e de mercado: resumos. Brasília, DF: Embrapa, 2016. p. 133. Na publicação: Kaesel Jackson Damasceno-Silva.| Tipo: Resumo em Anais de Congresso |
| Biblioteca(s): Embrapa Meio-Norte. |
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| 14. | | SOUSA, M. B. e; SILVA, K. J. D. e; ROCHA, M. de M.; MENEZES JUNIOR, J. A. de; LIMA, L. R. L. Adaptability and yield stability of cowpea elite lines of semi-prostrate growth habit in the cerrado biome. Revista Ciência Agronômica, v. 48, n. 5, Esp., p. 832-839, 2017.| Tipo: Artigo em Periódico Indexado | Circulação/Nível: A - 2 |
| Biblioteca(s): Embrapa Meio-Norte. |
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| 16. | | BISPO, V. R. de S.; SOUSA, M. B. e; SOUZA, G. D. de; CARVALHO, R. R. B. de; OLIVEIRA, L. A. de; OLIVEIRA, E. J. de. Classificação de genótipos de mandioca quanto à presença de compostos cianogênicos nas raízes via espectroscopia na região do visível (VIS) e infravermelho próximo (NIR). In: JORNADA CIENTÍFICA EMBRAPA MANDIOCA E FRUTICULTURA, 13., 2019. Foco e valor : resumos. Cruz das Almas, BA: Embrapa Mandioca e Fruticultura,2019. 119 p. il.| Tipo: Resumo em Anais de Congresso |
| Biblioteca(s): Embrapa Mandioca e Fruticultura. |
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| 17. | | SILVA, P. P. dos S.; SOUSA, M. B. e; OLIVEIRA, E. J. de; MORGANTE, C. V.; OLIVEIRA, C. R. S. de; VIEIRA, S. L.; BOREL, J. C. Genome-wide association study of drought tolerance in cassava. Euphytica, v.217, n.60, 2021.| Tipo: Artigo em Periódico Indexado | Circulação/Nível: A - 2 |
| Biblioteca(s): Embrapa Mandioca e Fruticultura; Embrapa Semiárido. |
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| 18. | | SOUSA, M. B. e; SILVA, K. J. D. e; ROCHA, M. de M.; MENEZES JUNIOR, J. A. de; LIMA, L. R. L. Genotype by environment interaction in cowpea lines using GGE Biplot method. Revista Caatinga, Mossoró, v. 31, n. 1, p. 64-71, jan./mar. 2018.| Tipo: Artigo em Periódico Indexado | Circulação/Nível: A - 2 |
| Biblioteca(s): Embrapa Meio-Norte. |
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| 20. | | SOUSA, M. B. e; SILVA, K. J. D. e; ROCHA, M. de M.; MENEZES JUNIOR, J. A. de; LIMA, L. R. L. Interação genótipos x ambientes em linhagens-elite de feijão-caupi via método GGE Biplot. In: CONGRESSO NACIONAL DE FEIJÃO-CAUPI, 4., 2016, Sorriso. Feijão-caupi: avanços e desafios tecnológicos e de mercado: resumos. Brasília, DF: Embrapa, 2016. p. 179. Na publicação: KAESEL JACKSON DAMASCENO-SILVA.| Tipo: Resumo em Anais de Congresso |
| Biblioteca(s): Embrapa Meio-Norte. |
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| Registros recuperados : 38 | |
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| Nenhum registro encontrado para a expressão de busca informada. |
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