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Registro Completo |
Biblioteca(s): |
Biblioteca Rui Tendinha. |
Data corrente: |
04/07/2018 |
Data da última atualização: |
12/04/2024 |
Tipo da produção científica: |
Artigo em Periódico Indexado |
Autoria: |
FERRÃO, L. F. V.; FERRÃO, R. G.; FERRÃO, M. A. G.; FONSECA, A. F. A. da.; CARBONETTO, P.; STEPHENS, M.; GARCIA, A. A. F. |
Afiliação: |
Luis Felipe Ventorim Ferrão, ESALQ; Romário Gava Ferrão, Incaper; Maria Amélia Gava Ferrão, Incaper/Embrapa Café; Aymbiré Francisco Almeida da Fonseca, Incaper/Embrapa Café; Peter Carbonetto, Research Computing Center, University of Chicago; Matthew Stephens, Research Computing Center, University of Chicago; Antonio Augusto Franco Garcia, ESALQ. |
Título: |
Accurate genomic prediction of Coffea canephora in multiple environments using whole-genome statistical models. |
Ano de publicação: |
2018 |
Fonte/Imprenta: |
Heredity, june 2018. |
Idioma: |
Português |
Conteúdo: |
Genomic selection has been proposed as the standard method to predict breeding values in animal and plant breeding. Although some crops have benefited from this methodology, studies in Coffea are still emerging. To date, there have been no studies describing how well genomic prediction models work across populations and environments for different complex traits in coffee. Considering that predictive models are based on biological and statistical assumptions, it is expected that their performance vary depending on how well these assumptions align with the true genetic architecture of the phenotype. To investigate this, we used data from two recurrent selection populations of Coffea canephora, evaluated in two locations, and single nucleotide polymorphisms identified by Genotyping-by-Sequencing. In particular, we evaluated the performance of 13 statistical approaches to predict three important traits in the coffee?production of coffee beans, leaf rust incidence and yield of green beans. Analyses were performed for predictions within-environment, across locations and across populations to assess the reliability of genomic selection. Overall, differences in the prediction accuracy of the competing models were small, although the Bayesian methods showed a modest improvement over other methods, at the cost of more computation time. As expected, predictive accuracy for within-environment analysis, on average, were higher than predictions across locations and across populations. Our results support the potential of genomic selection to reshape traditional plant breeding schemes. In practice, we expect to increase the genetic gain per unit of time by reducing the length cycle of recurrent selection in coffee. MenosGenomic selection has been proposed as the standard method to predict breeding values in animal and plant breeding. Although some crops have benefited from this methodology, studies in Coffea are still emerging. To date, there have been no studies describing how well genomic prediction models work across populations and environments for different complex traits in coffee. Considering that predictive models are based on biological and statistical assumptions, it is expected that their performance vary depending on how well these assumptions align with the true genetic architecture of the phenotype. To investigate this, we used data from two recurrent selection populations of Coffea canephora, evaluated in two locations, and single nucleotide polymorphisms identified by Genotyping-by-Sequencing. In particular, we evaluated the performance of 13 statistical approaches to predict three important traits in the coffee?production of coffee beans, leaf rust incidence and yield of green beans. Analyses were performed for predictions within-environment, across locations and across populations to assess the reliability of genomic selection. Overall, differences in the prediction accuracy of the competing models were small, although the Bayesian methods showed a modest improvement over other methods, at the cost of more computation time. As expected, predictive accuracy for within-environment analysis, on average, were higher than predictions across locations and across populations. Our... Mostrar Tudo |
Palavras-Chave: |
Cafe conilon. |
Thesaurus NAL: |
Coffea canephora; Genomic. |
Categoria do assunto: |
G Melhoramento Genético |
URL: |
https://biblioteca.incaper.es.gov.br/digital/bitstream/item/4674/1/s41437-018-0105-y.pdf
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Marc: |
LEADER 02393naa a2200229 a 4500 001 1020469 005 2024-04-12 008 2018 bl uuuu u00u1 u #d 100 1 $aFERRÃO, L. F. V. 245 $aAccurate genomic prediction of Coffea canephora in multiple environments using whole-genome statistical models.$h[electronic resource] 260 $c2018 520 $aGenomic selection has been proposed as the standard method to predict breeding values in animal and plant breeding. Although some crops have benefited from this methodology, studies in Coffea are still emerging. To date, there have been no studies describing how well genomic prediction models work across populations and environments for different complex traits in coffee. Considering that predictive models are based on biological and statistical assumptions, it is expected that their performance vary depending on how well these assumptions align with the true genetic architecture of the phenotype. To investigate this, we used data from two recurrent selection populations of Coffea canephora, evaluated in two locations, and single nucleotide polymorphisms identified by Genotyping-by-Sequencing. In particular, we evaluated the performance of 13 statistical approaches to predict three important traits in the coffee?production of coffee beans, leaf rust incidence and yield of green beans. Analyses were performed for predictions within-environment, across locations and across populations to assess the reliability of genomic selection. Overall, differences in the prediction accuracy of the competing models were small, although the Bayesian methods showed a modest improvement over other methods, at the cost of more computation time. As expected, predictive accuracy for within-environment analysis, on average, were higher than predictions across locations and across populations. Our results support the potential of genomic selection to reshape traditional plant breeding schemes. In practice, we expect to increase the genetic gain per unit of time by reducing the length cycle of recurrent selection in coffee. 650 $aCoffea canephora 650 $aGenomic 653 $aCafe conilon 700 1 $aFERRÃO, R. G. 700 1 $aFERRÃO, M. A. G. 700 1 $aFONSECA, A. F. A. da. 700 1 $aCARBONETTO, P. 700 1 $aSTEPHENS, M. 700 1 $aGARCIA, A. A. F. 773 $tHeredity, june 2018.
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Registro original: |
Biblioteca Rui Tendinha (BRT) |
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Registro Completo |
Biblioteca(s): |
Biblioteca Rui Tendinha. |
Data corrente: |
21/01/2014 |
Data da última atualização: |
21/01/2014 |
Tipo da produção científica: |
Publicação em Anais de Congresso |
Autoria: |
FONSECA, A. F. A. da.; FERRÃO, R. G.; FERRÃO, M. A. G.; BRAGANÇA, S. M.; SILVEIRA, J.S.M. |
Afiliação: |
Aymbiré Francisco Almeida da Fonseca, Incaper/Embrapa Café; Romário Gava Ferrão, Incaper; Maria Amélia Gava Ferrão, Incaper/Embrapa Café; Scheilla Marina Bragança, Incaper; Incaper. |
Título: |
Variedades derivadas de café conilon (Coffea canephora) desenvolvidas pelo Incaper para o Espírito Santo. |
Ano de publicação: |
2001 |
Fonte/Imprenta: |
In: SIMPÓSIO DE PESQUISA DOS CAFÉS DO BRASIL, 2., 2001, Vitória, ES. Trabalhos apresentados... Brasília, DF : Embrapa Café, 2001. |
Páginas: |
7p. |
Idioma: |
Português |
Conteúdo: |
Em quinze anos de pesquisa na área de melhoramento genético em populações de café Conilon pertencentes à espécie Coffea canephora, foram desenvolvidas pelo INCAPER quatro variedades clonais e uma de propagação sexuada para o Espírito Santo, denominadas, respectivamente: EMCAPA 8111 ? maturação precoce, EMCAPA 8121 ? maturação intermediária, EMCAPA 8131 ? maturação tardia, EMCAPA 8141 Robustão Capixaba - tolerante à seca e EMCAPER 8151 Robusta Tropical ? de propagação sexuada. Essas novas variedades têm sido a base para a renovação do parque cafeeiro da espécie no Espírito Santo e contribuído de forma efetiva para o avanço tecnológico da cultura em todo o País. Este trabalho objetiva descrever, de forma concisa, as principais características de cada uma das variedades de café Conilon recomendadas para o Estado do Espírito Santo. |
Palavras-Chave: |
Café conilon; Coffea canephora; Incaper; Tolerância à seca; Variedades clonais. |
Categoria do assunto: |
G Melhoramento Genético |
URL: |
http://biblioteca.incaper.es.gov.br/digital/bitstream/item/285/1/VARIEDADES-DERIVADAS-DE-CAFE-CONILON-Coffea-canephora-genet27.pdf
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Marc: |
LEADER 01655nam a2200229 a 4500 001 1001677 005 2014-01-21 008 2001 bl uuuu u01u1 u #d 100 1 $aFONSECA, A. F. A. da. 245 $aVariedades derivadas de café conilon (Coffea canephora) desenvolvidas pelo Incaper para o Espírito Santo.$h[electronic resource] 260 $aIn: SIMPÓSIO DE PESQUISA DOS CAFÉS DO BRASIL, 2., 2001, Vitória, ES. Trabalhos apresentados... Brasília, DF : Embrapa Café$c2001 300 $a7p. 520 $aEm quinze anos de pesquisa na área de melhoramento genético em populações de café Conilon pertencentes à espécie Coffea canephora, foram desenvolvidas pelo INCAPER quatro variedades clonais e uma de propagação sexuada para o Espírito Santo, denominadas, respectivamente: EMCAPA 8111 ? maturação precoce, EMCAPA 8121 ? maturação intermediária, EMCAPA 8131 ? maturação tardia, EMCAPA 8141 Robustão Capixaba - tolerante à seca e EMCAPER 8151 Robusta Tropical ? de propagação sexuada. Essas novas variedades têm sido a base para a renovação do parque cafeeiro da espécie no Espírito Santo e contribuído de forma efetiva para o avanço tecnológico da cultura em todo o País. Este trabalho objetiva descrever, de forma concisa, as principais características de cada uma das variedades de café Conilon recomendadas para o Estado do Espírito Santo. 653 $aCafé conilon 653 $aCoffea canephora 653 $aIncaper 653 $aTolerância à seca 653 $aVariedades clonais 700 1 $aFERRÃO, R. G. 700 1 $aFERRÃO, M. A. G. 700 1 $aBRAGANÇA, S. M. 700 1 $aSILVEIRA, J.S.M.
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