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| Registros recuperados : 2 | |
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Registro Completo |
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Biblioteca(s): |
Biblioteca Rui Tendinha. |
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Data corrente: |
05/02/2016 |
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Data da última atualização: |
02/07/2017 |
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Tipo da produção científica: |
Publicação em Anais de Congresso |
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Autoria: |
FERRÃO, L. F. V.; FERRÃO, R. G.; FERRÃO, M. A. G.; FONSECA, A. F. A. da.; GARCIA, A. F. |
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Afiliação: |
Luis Felipe V. Ferrão, ESALQ/USP; Romário Gava Ferrão, Incaper; Maria Amélia Gava Ferrão, Incaper/Embrapa Café; Aymbiré Francisco Almeida da Fonseca, Incaper/Embrapa Café; Antônio Augusto Franco Garcia, ESALQ/USP. |
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Título: |
Mixed model to multiple Harvest-Location trial applied to genomic prediction in Coffea canephora. |
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Ano de publicação: |
2016 |
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Fonte/Imprenta: |
In: PLANT & ANIMAL GENOME CONFERENCE, 24., 2016, San Diego, CA. [Abstracts...]. San Diego: [s.n.], 2016. não paginado. P1168. |
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Idioma: |
Português |
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Conteúdo: |
Genomic Selection (GS) has been studied in several crops with potential to increase the rates of genetic gain and reduce the length of breeding cycle. Despite the relevance, there is a modest number of reports applied to the genus Coffea. Nevertheless, the effective implementation depends on the ability to consider genomic models that represent with adequate reliability the breeding scenario in which the specie are inserted. Coffee experimentation, in general, is represented for evaluations in multiples sites and harvests (MET), in order to understand the interaction magnitude and predicting the performance of untested genotypes. Therefore, the main objective of this study was investigate GS models that accommodate MET modeling. A expansion of the traditional GBLUP was proposed in order to accommodate the interactions in the GS model. Different scenarios that mimic the coffee breeding and models commonly used in the analysis were compared. In terms of goodness of fit this approach showed the lowest AIC and BIC values and, consequently, the best goodness of fit. The predictive capacity was measured by cross-validation and, in contrast with the GBLUP, the incorporation of the MET modeling showed higher predictive accuracy (on average 10-17% higher) and lower prediction errors. All the genomic analysis were performed using the Genotyping-by-sequencing (GBS) approach, which showed a good potential to be used in coffee breeding programs. Thus, as conclusion, the results achieved may be used as basis for additional studies into the Genus Coffea and expanded for other perennial crops, that have a similar experimentation design. MenosGenomic Selection (GS) has been studied in several crops with potential to increase the rates of genetic gain and reduce the length of breeding cycle. Despite the relevance, there is a modest number of reports applied to the genus Coffea. Nevertheless, the effective implementation depends on the ability to consider genomic models that represent with adequate reliability the breeding scenario in which the specie are inserted. Coffee experimentation, in general, is represented for evaluations in multiples sites and harvests (MET), in order to understand the interaction magnitude and predicting the performance of untested genotypes. Therefore, the main objective of this study was investigate GS models that accommodate MET modeling. A expansion of the traditional GBLUP was proposed in order to accommodate the interactions in the GS model. Different scenarios that mimic the coffee breeding and models commonly used in the analysis were compared. In terms of goodness of fit this approach showed the lowest AIC and BIC values and, consequently, the best goodness of fit. The predictive capacity was measured by cross-validation and, in contrast with the GBLUP, the incorporation of the MET modeling showed higher predictive accuracy (on average 10-17% higher) and lower prediction errors. All the genomic analysis were performed using the Genotyping-by-sequencing (GBS) approach, which showed a good potential to be used in coffee breeding programs. Thus, as conclusion, the results achieved ... Mostrar Tudo |
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Palavras-Chave: |
Café Conilon; Coffea canephora; Genomic Selection. |
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Categoria do assunto: |
G Melhoramento Genético |
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URL: |
http://biblioteca.incaper.es.gov.br/digital/bitstream/item/2728/1/Mixed-Model-to-Multiple-Harvest-Location1.pdf
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Marc: |
LEADER 02337nam a2200193 a 4500
001 1009544
005 2017-07-02
008 2016 bl uuuu u01u1 u #d
100 1 $aFERRÃO, L. F. V.
245 $aMixed model to multiple Harvest-Location trial applied to genomic prediction in Coffea canephora.$h[electronic resource]
260 $aIn: PLANT & ANIMAL GENOME CONFERENCE, 24., 2016, San Diego, CA. [Abstracts...]. San Diego: [s.n.], 2016. não paginado. P1168.$c1168
520 $aGenomic Selection (GS) has been studied in several crops with potential to increase the rates of genetic gain and reduce the length of breeding cycle. Despite the relevance, there is a modest number of reports applied to the genus Coffea. Nevertheless, the effective implementation depends on the ability to consider genomic models that represent with adequate reliability the breeding scenario in which the specie are inserted. Coffee experimentation, in general, is represented for evaluations in multiples sites and harvests (MET), in order to understand the interaction magnitude and predicting the performance of untested genotypes. Therefore, the main objective of this study was investigate GS models that accommodate MET modeling. A expansion of the traditional GBLUP was proposed in order to accommodate the interactions in the GS model. Different scenarios that mimic the coffee breeding and models commonly used in the analysis were compared. In terms of goodness of fit this approach showed the lowest AIC and BIC values and, consequently, the best goodness of fit. The predictive capacity was measured by cross-validation and, in contrast with the GBLUP, the incorporation of the MET modeling showed higher predictive accuracy (on average 10-17% higher) and lower prediction errors. All the genomic analysis were performed using the Genotyping-by-sequencing (GBS) approach, which showed a good potential to be used in coffee breeding programs. Thus, as conclusion, the results achieved may be used as basis for additional studies into the Genus Coffea and expanded for other perennial crops, that have a similar experimentation design.
653 $aCafé Conilon
653 $aCoffea canephora
653 $aGenomic Selection
700 1 $aFERRÃO, R. G.
700 1 $aFERRÃO, M. A. G.
700 1 $aFONSECA, A. F. A. da.
700 1 $aGARCIA, A. F.
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Registro original: |
Biblioteca Rui Tendinha (BRT) |
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Biblioteca |
ID |
Origem |
Tipo/Formato |
Classificação |
Cutter |
Registro |
Volume |
Status |
Fechar
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Registro completo |
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Biblioteca(s): |
Biblioteca Rui Tendinha. |
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Identificador: |
6823 |
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Data corrente: |
22/05/2015 |
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Data da última atualização: |
26/04/2018 |
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Código do título: |
0000248 |
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Título e Subtítulo: |
REVISTA INOVES |
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Título posterior: |
INOVES |
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Entidade: |
Secretaria de Estado de Gestão e Recursos Humanos |
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Local de publicação: |
vitória, ES |
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Periodicidade: |
Anual |
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Inicio de publicação: |
2005 |
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URL: |
http://www.inoves.es.gov.br/Revistas/Revistas.aspx
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