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Registro Completo |
Biblioteca(s): |
Embrapa Café. |
Data corrente: |
17/03/2017 |
Data da última atualização: |
20/03/2017 |
Tipo da produção científica: |
Resumo em Anais de Congresso |
Autoria: |
FERRÃO, L. F. V.; FERRÃO, R. G.; FERRAO, M. A. G.; FONSECA, A. F. A. da; GARCIA, A. A. F. |
Afiliação: |
LUIS FELIPE V. FERRÃO, ESALQ/USP; ROMÁRIO G. FERRÃO, INCAPER; MARIA AMELIA GAVA FERRAO, SAPC; AYMBIRE FRANCISCO A DA FONSECA, SAPC; ANTONIO AUGUSTO FRANCO GARCIA, ESALQ/USP. |
Título: |
Mixed model to multiple havest-location trial applied to genomic prediction in Coffea canephora. |
Ano de publicação: |
2016 |
Fonte/Imprenta: |
In: PLANT & ANIMAL GENOME CONFERENCE, 24., 2016, San Diego, CA. [Abstracts...]. San Diego, CA: [s.n.], 2016. |
Idioma: |
Inglês |
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 |
Thesagro: |
Coffea Canephora. |
Thesaurus Nal: |
Marker-assisted selection. |
Categoria do assunto: |
-- |
URL: |
https://ainfo.cnptia.embrapa.br/digital/bitstream/item/157826/1/Mixed-Model-to-Multiple-Harvest-Location1.pdf
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Marc: |
LEADER 02290nam a2200181 a 4500 001 2067269 005 2017-03-20 008 2016 bl uuuu u00u1 u #d 100 1 $aFERRÃO, L. F. V. 245 $aMixed model to multiple havest-location trial applied to genomic prediction in Coffea canephora.$h[electronic resource] 260 $aIn: PLANT & ANIMAL GENOME CONFERENCE, 24., 2016, San Diego, CA. [Abstracts...]. San Diego, CA: [s.n.]$c2016 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. 650 $aMarker-assisted selection 650 $aCoffea Canephora 700 1 $aFERRÃO, R. G. 700 1 $aFERRAO, M. A. G. 700 1 $aFONSECA, A. F. A. da 700 1 $aGARCIA, A. A. F.
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Registro original: |
Embrapa Café (CNPCa) |
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| Acesso ao texto completo restrito à biblioteca da Embrapa Hortaliças. Para informações adicionais entre em contato com cnph.biblioteca@embrapa.br. |
Registro Completo
Biblioteca(s): |
Embrapa Hortaliças. |
Data corrente: |
17/10/2000 |
Data da última atualização: |
17/10/2000 |
Autoria: |
REIFSCHNEIDER, F. J. B.; GUEDES, A. C. |
Afiliação: |
EMBRAPA-CNPH, Brasilia, DF. |
Título: |
Diagnostico da patologia de sementes de hortalicas no Brasil. |
Ano de publicação: |
1984 |
Fonte/Imprenta: |
In: SIMPOSIO BRASILEIRO DE PATOLOGIA DE SEMENTES, 1., 1984, Piracicaba, SP. Anais... Piracicaba: ABRATES / CENA-USP, 1984. |
Páginas: |
p.92. |
Idioma: |
Português |
Palavras-Chave: |
Brasil; Diseases. |
Thesagro: |
Doença; Hortaliça; Semente. |
Thesaurus NAL: |
Brazil; seeds; vegetables. |
Categoria do assunto: |
-- |
Marc: |
LEADER 00647naa a2200229 a 4500 001 1768817 005 2000-10-17 008 1984 bl --- 0-- u #d 100 1 $aREIFSCHNEIDER, F. J. B. 245 $aDiagnostico da patologia de sementes de hortalicas no Brasil. 260 $c1984 300 $ap.92. 650 $aBrazil 650 $aseeds 650 $avegetables 650 $aDoença 650 $aHortaliça 650 $aSemente 653 $aBrasil 653 $aDiseases 700 1 $aGUEDES, A. C. 773 $tIn: SIMPOSIO BRASILEIRO DE PATOLOGIA DE SEMENTES, 1., 1984, Piracicaba, SP. Anais... Piracicaba: ABRATES / CENA-USP, 1984.
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