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| Registros recuperados : 271 | |
| 61. |  | PEREIRA, L. L.; GUARÇONI, R. C.; FERRAO, M. A. G.; FONSECA, A. F. A. da; CATEN, C. S. ten. Los caminhos de la calidad, un estudio sobre la visión de expertos y productores rurales a respeto de procesos y tecnologías. In: CONGRESSO INTERNACIONAL DE CONHECIMENTO E INOVAÇÃO, 6., 2016. Bogotá, Colômbia. Acelerar a Inovação: fator decisivo para o Desenvolvimento Social. anais... Florianópolis: EGC – Engenharia do Conhecimento – UFSC, 2016| Biblioteca(s): Embrapa Café. |
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| 62. | | PEREIRA, L. L.; GUARÇONI, R. C.; FERRAO, M. A. G.; FONSECA, A. F. A. da; CATEN, C. S. T. Los caminos de la calidad: un estudio sobre la visión de expertos y productiores rurales a respeito de procesos y tecnologias. International Journal of Knowledge Engineering and Management, Florianópolis, v. 6, n. 15, p. 72-89, jul./out. 2017.| Biblioteca(s): Embrapa Café. |
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| 69. | | FONSECA, A. F. A. da; SEDIYAMA, T.; FERRÃO, R. G.; FERRAO, M. A. G.; CRUZ, C. D.; SAKIYAMA, N. S. Correlações entre caracteres em café Conilon. In: SIMPÓSIO DE PESQUISA DOS CAFÉS DO BRASIL, 3., 2003, Porto Seguro. Resumos... Brasília, DF: Embrapa Café, 2003.| Biblioteca(s): Embrapa Café. |
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| 70. | | FERRAO, M. A. G.; FERRÃO, R. G.; FONSECA, A. F. A. da; PEREIRA, A. A.; FAZUOLI, L. C. Desempenho de genótipos de Coffea arabica em baixa altitude. In: SIMPÓSIO DE PESQUISA DOS CAFÉS DO BRASIL, 3., 2003, Porto Seguro. Resumos... Brasília, DF: Embrapa Café, 2003.| Biblioteca(s): Embrapa Café. |
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| 71. | | FONSECA, A. F. A. da; FERRAO, M. A. G.; CASTRO, L. L. F. de; FERRÃO, R. G. O sistema de inovação como fator indutor de competitividade na cafeicultura. In: TOMAZ, M. A.; AMARAL, J. F. T. do; JESUS JUNIOR, W. C. de; FONSECA, A. F. A. da; FERRÃO, R. G.; FERRAO, M. A. G.; MARTINS, L. D.; RODRIGUES, W. N. (Coord.). Inovação, difusão e integração: bases para a sustentabilidade da cafeicultura. Alegre, ES: CAUFES, 2012 270 p. p.57-70| Biblioteca(s): Embrapa Café. |
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| 72. | | RODRIGUES, W. N.; TOMAZ, M. A.; FERRAO, M. A. G.; FERRÃO, R. G.; FONSECA, A. F. A. da. Diversity among genotypes of conilon coffee selected in Espírito Santo State. Bioscience Journal, Uberlânida, v. 31, n. 6,p. 1643-1650, nov./dez. 2015.| Biblioteca(s): Embrapa Café. |
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| 73. | | FONSECA, A. F. A. da; SEDIYAMA, T.; CRUZ, C. D.; SAKAIYAMA, N. S.; FERRÃO, R. G.; BRAGANÇA, S. M. Divergência genética em café conilon. Pesquisa Agropecuária Brasileira, Brasília, DF, v. 41, n. 4, p. 599-605, abr. 2006 Título em inglês: Genetic divergence in conilon coffee.| Biblioteca(s): Embrapa Unidades Centrais. |
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| 74. | | FIALHO, G. S.; SILVA, D. P. da; REIS, E. F. dos; FONSECA, A. F. A. da; FERRAO, M. A. G. Avaliação de plantas de Coffea arabica L. submetidas a déficit hídrico em diferentes fases de seu desenvolvimento inicial. In: SIMPÓSIO DE PESQUISA DOS CAFÉS DO BRASIL, 5., 2007, Águas de Lindóia, SP. Anais... Brasília, DF: Embrapa Café, 2007.| Biblioteca(s): Embrapa Café. |
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| 80. | | ANGELETTI, M. da P.; FONSECA, A. F. A. da; LIMA, M. I. P. M.; COLTRI, M. L. Avaliação do comportamento de cultivares de tomateiro no período chuvoso, em Rondônia. Horticultura Brasileira, v. 4, n. 1, p. 45, maio 1986. Resumo do XXVI Congresso Brasileiro de Olericultura, 1986. Resumo 002.| Biblioteca(s): Embrapa Amazônia Ocidental. |
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| Registros recuperados : 271 | |
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Registro Completo
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Biblioteca(s): |
Embrapa Café. |
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Data corrente: |
07/12/2017 |
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Data da última atualização: |
07/12/2017 |
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Tipo da produção científica: |
Artigo em Periódico Indexado |
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Circulação/Nível: |
A - 1 |
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Autoria: |
FERRÃO, L. F. V.; FERRÃO, R. G.; FERRAO, M. A. G.; FONSECA, A. F. A. da; GARCIA, A. A. F. |
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Afiliação: |
LUIS FELIPE VENTORIM FERRÃO, DG/ESALQ; ROMÁRIO GAVA FERRÃO, INCAPER; MARIA AMELIA GAVA FERRAO, SAPC; AYMBIRE FRANCISCO A DA FONSECA, SAPC; ANTONIO AUGUSTO FRANCO GARCIA, DG/ESALQ. |
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Título: |
A mixed model to multiple harvest-location trials applied to genomic prediction in Coffea canephora. |
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Ano de publicação: |
2017 |
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Fonte/Imprenta: |
Tree Genetics & Genomes, v. 13, n. 95, 2017. |
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Idioma: |
Inglês |
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Conteúdo: |
Genomic selection (GS) has been studied in several crops to increase the rates of genetic gain and reduce the length of breeding cycles. Despite its relevance, there are only a modest number of reports applied to the genus Coffea. Effective implementation depends on the ability to consider genomic models, which correctly represent breeding scenario in which the species are inserted. Coffee experimentation, in general, is represented by evaluations in multiple locations and harvests to understand the interaction and predict the performance of untested genotypes. Therefore, the main objective of this study was to investigate GS models suitable for use in Coffea canephora. An expansion of traditional GBLUP was considered and genomic analysis was performed using a genotyping-by-sequencing (GBS) approach, showed good potential to be used in coffee breeding programs. Interactions were modeled using the multiplicative mixed model theory, which is commonly used in multi-environment trials (MET) analysis in perennial crops. The effectiveness of the method used was compared with other genetic models in terms of goodness-of-fit statistics and prediction accuracy. Different scenarios that mimic coffee breeding were used in the cross-validation process. The method used had the lowest AIC and BIC values and, consequently, the best fit. In terms of predictive ability, the incorporation of the MET modeling showed higher accuracy (on average 10–17% higher) and lower prediction errors than traditional GBLUP. The results may be used as basis for additional studies into the genus Coffea and can be expanded for similar perennial crops. MenosGenomic selection (GS) has been studied in several crops to increase the rates of genetic gain and reduce the length of breeding cycles. Despite its relevance, there are only a modest number of reports applied to the genus Coffea. Effective implementation depends on the ability to consider genomic models, which correctly represent breeding scenario in which the species are inserted. Coffee experimentation, in general, is represented by evaluations in multiple locations and harvests to understand the interaction and predict the performance of untested genotypes. Therefore, the main objective of this study was to investigate GS models suitable for use in Coffea canephora. An expansion of traditional GBLUP was considered and genomic analysis was performed using a genotyping-by-sequencing (GBS) approach, showed good potential to be used in coffee breeding programs. Interactions were modeled using the multiplicative mixed model theory, which is commonly used in multi-environment trials (MET) analysis in perennial crops. The effectiveness of the method used was compared with other genetic models in terms of goodness-of-fit statistics and prediction accuracy. Different scenarios that mimic coffee breeding were used in the cross-validation process. The method used had the lowest AIC and BIC values and, consequently, the best fit. In terms of predictive ability, the incorporation of the MET modeling showed higher accuracy (on average 10–17% higher) and lower prediction errors than tr... Mostrar Tudo |
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Palavras-Chave: |
GBLUP; Genotyping-by-sequencing; Multi-environment trials; Perennial crops. |
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Thesaurus NAL: |
Marker-assisted selection. |
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Categoria do assunto: |
-- |
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URL: |
https://ainfo.cnptia.embrapa.br/digital/bitstream/item/168435/1/A-mixed-model-to-multiple-harvest-location.pdf
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Marc: |
LEADER 02351naa a2200229 a 4500
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100 1 $aFERRÃO, L. F. V.
245 $aA mixed model to multiple harvest-location trials applied to genomic prediction in Coffea canephora.$h[electronic resource]
260 $c2017
520 $aGenomic selection (GS) has been studied in several crops to increase the rates of genetic gain and reduce the length of breeding cycles. Despite its relevance, there are only a modest number of reports applied to the genus Coffea. Effective implementation depends on the ability to consider genomic models, which correctly represent breeding scenario in which the species are inserted. Coffee experimentation, in general, is represented by evaluations in multiple locations and harvests to understand the interaction and predict the performance of untested genotypes. Therefore, the main objective of this study was to investigate GS models suitable for use in Coffea canephora. An expansion of traditional GBLUP was considered and genomic analysis was performed using a genotyping-by-sequencing (GBS) approach, showed good potential to be used in coffee breeding programs. Interactions were modeled using the multiplicative mixed model theory, which is commonly used in multi-environment trials (MET) analysis in perennial crops. The effectiveness of the method used was compared with other genetic models in terms of goodness-of-fit statistics and prediction accuracy. Different scenarios that mimic coffee breeding were used in the cross-validation process. The method used had the lowest AIC and BIC values and, consequently, the best fit. In terms of predictive ability, the incorporation of the MET modeling showed higher accuracy (on average 10–17% higher) and lower prediction errors than traditional GBLUP. The results may be used as basis for additional studies into the genus Coffea and can be expanded for similar perennial crops.
650 $aMarker-assisted selection
653 $aGBLUP
653 $aGenotyping-by-sequencing
653 $aMulti-environment trials
653 $aPerennial crops
700 1 $aFERRÃO, R. G.
700 1 $aFERRAO, M. A. G.
700 1 $aFONSECA, A. F. A. da
700 1 $aGARCIA, A. A. F.
773 $tTree Genetics & Genomes$gv. 13, n. 95, 2017.
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