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Registros recuperados : 82 | |
1. | | MOLLINARI, M.; MARGARIDO, G. R. A.; GARCIA, A. A. F. Comparação dos algoritmos delineação rápida em cadeia e seriação, para a construção de mapas genéticos. Pesquisa Agropecuária Brasileira, Brasília, DF, v. 43, n. 4, p. 505-512, abr. 2008 Título em inglês: Comparison of algorithms rapid chain delineation and seriation, for the construction of genetic linkage maps. Biblioteca(s): Embrapa Unidades Centrais. |
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4. | | LARA, L. A. DE C.; SANTOS, M. F.; JANK, L.; CHIARI, L.; GARCIA, A. A. F. Modeling the variance-covariance matrix of genetic and residual effects in a Panicum maximum genome wide selection experiment. In: INTERNATIONAL CONFERENCE ON QUANTITATIVE GENETICS, 5., Madison, Wisconsin, USA, 2016. Proceedings... Madison, Wisconsin, USA: ICQG, 2016. Biblioteca(s): Embrapa Gado de Corte. |
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5. | | SANTOS, M. A.; GERALDI, I. O.; GARCIA, A. A. F.; BORTOLATTO, N.; SCHIAVON, A.; HUNGRIA, M. Mapping of QTLs associated with biological nitrogen fixation traits in soybean. Hereditas, Lund, v. 150, n. 2-3, p. 17-25, 2013. Biblioteca(s): Embrapa Soja. |
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6. | | ALVES, R. M.; GARCIA, A. A. F.; CRUZ, E. D.; FIGUEIRA, A. Seleção de descritores botânico-agronômicos para caracterização de germoplasma de cupuaçuzeiro. Pesquisa Agropecuária Brasileira, Brasília, DF, v. 38, n. 7, p. 807-818, jul. 2003. il. Biblioteca(s): Embrapa Amazônia Oriental; Embrapa Unidades Centrais. |
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9. | | FERRÃO, L. F. V.; FERRÃO, R. G.; FERRAO, M. A. G.; FONSECA, A. F. A. da; GARCIA, A. A. F. Mixed model to multiple havest-location trial applied to genomic prediction in Coffea canephora. In: PLANT & ANIMAL GENOME CONFERENCE, 24., 2016, San Diego, CA. [Abstracts...]. San Diego, CA: [s.n.], 2016. Biblioteca(s): Embrapa Café. |
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10. | | BRAGA, M. F.; VIEIRA, M. L. C.; GAZAFFI, R.; GARCIA, A. A. F.; GIRALDI, I. O.; JUNQUEIRA, N. T. V. Mapeamento de QTL (quantitative trait loci) associados à resistência do maracujá-doce à bacteriose. In: CONGRESSO BRASILEIRO DE FRUTICULTURA, 22., 2012, Bento Gonçalves. Anais... Bento Gonçalves: SBF, 2012. Biblioteca(s): Embrapa Cerrados. |
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13. | | FAVERO, A. P.; MORAES, S. A. de; GARCIA, A. A. F.; VALLS, J. F. M.; VELLO, N. A. Characterization of rust, early and late leaf spot resistance in wild and cultivated peanut germplasm. Scientia Agricola, v.66, n. 1, p.110-117, 2009. Biblioteca(s): Embrapa Recursos Genéticos e Biotecnologia. |
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14. | | CASTRO, C. M.; FERRÃO, L. F. V.; ROHR, A.; PINHEIRO, N. L.; PEREIRA, A. da S.; GARCIA, A. A. F. Population structure of potato breeding germplasm from Embrapa-Brazil assessed with single nucleotide polymorphism (SNP) markers. In: CONGRESO DE LA ASOCIACION LATINOAMERICANA DE LA PAPA - ALAP, 28., 2018, Cusco, Peru. Abstract Book 10th: Congress: Biodiversity, Food Security and Business. Instituto Nacional de Innovación: Agraria-INIA. Cusco, Perú, 2018. p. 123 Biblioteca(s): Embrapa Clima Temperado. |
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15. | | FÁVERO, A. P.; MORAES, S. A. de; GARCIA, A. A. F.; VALLS, J. F. M.; VELLO, N. A. Caracterização da resistÊncia à ferrugem, mancha preta e mancha castanha em germoplasma silvestre e cultivado de amendoim. Scientia Agricola, v. 66, n.1, p. 110-117, jan./fev., 2009. Biblioteca(s): Embrapa Algodão. |
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16. | | ROSÁRIO, M. F. do; GAZAFFI, R.; MOURA, A. S. A. M. T.; LEDUR, M. C.; GARCIA, A. A. F.; COUTINHO, L. L. Base genética da correlação entre características de desempenho e de rendimento de carcaça no cromossomo 1 da galinha. In: CONFERÊNCIA FACTA DE CIÊNCIA E TECNOLOGIA AVÍCOLAS, 2011, Santos, SP. Anais... Santos: FACTA, 2011. Trabalhos de Pesquisa José Maria Lamas da Silva. 1 CD-ROM. Projeto: 02.09.07.006. Biblioteca(s): Embrapa Suínos e Aves. |
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17. | | DIAS, K. O. G.; SANTOS, J. P. R. dos; KRAUSE, M. D.; PIEPHO, H.-P.; GUIMARAES, L. J. M.; PASTINA, M. M.; GARCIA, A. A. F. Leveraging probability concepts for cultivar recommendation in multi?environment trials. Theoretical and Applied Genetics, v. 135, n. 4, p. 1385-1399, 2022. Biblioteca(s): Embrapa Milho e Sorgo. |
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18. | | VIGNA, B. B. Z.; JUNGMANN, L.; ALLEONI, G. C.; VALLE, C. B. do; FEIJO, G. L. D.; GARCIA, A. A. F.; SOUZA, A. P. Análise da segregação de locos microssatélites em uma população F1 segregante de Brachiaria humidicola hexaplóide. In: CONGRESSO BRASILEIRO DE GENÉTICA, 56., 2010, Guarujá. Resumos... Ribeirão Preto: Sociedade Brasileira de Genética, 2010. p. 176 Biblioteca(s): Embrapa Gado de Corte. |
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19. | | FREITAS, E. G. de; PASTINA, M. M.; GAZAFFI, R.; PINTO, L. R.; XAVIER, M. A.; LANDELL, M. G. de A.; GARCIA, A. A. F. Modelos mistos para seleção de genótipos superiores e de futuros genitores de cana-de-açúcar. In: REUNIÃO ANUAL DA REGIÃO BRASILEIRA DA SOCIEDADE INTERNACIONAL DE BIOMETRIA, 58.; SIMPÓSIO DE ESTATÍSTICA APLICADA À EXPERIMENTAÇÃO AGRONÔMICA, 15., 2013, Campina Grande. Modelagem estatística em áreas multidisciplinares: impactos causados pelas mudanças climáticas na Região Nordeste: anais. Campina Grande: Sociedade Internacional de Biometria, 2013. Biblioteca(s): Embrapa Milho e Sorgo. |
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20. | | PÉREZ-JARAMILLO, J. E.; CARRIÓN, V. J.; BOSSE, M.; FERRÃO, L. F. V.; HOLLANDER, M. de; GARCIA, A. A. F.; RAMIREZ, C. A.; MENDES, R.; RAAIJMAKER, J. M. Linking rhizosphere microbiome composition of wild and domesticated Phaseolus vulgaris to genotypic and root phenotypic traits. The ISME Journal, v. 11, p. 2244-2257, 2017. Biblioteca(s): Embrapa Meio Ambiente. |
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Registros recuperados : 82 | |
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Registro Completo
Biblioteca(s): |
Embrapa Café. |
Data corrente: |
07/12/2017 |
Data da última atualização: |
07/12/2017 |
Tipo da produção científica: |
Artigo em Periódico Indexado |
Circulação/Nível: |
A - 1 |
Autoria: |
FERRÃO, L. F. V.; FERRÃO, R. G.; FERRAO, M. A. G.; FONSECA, A. F. A. da; GARCIA, A. A. F. |
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. |
Título: |
A mixed model to multiple harvest-location trials applied to genomic prediction in Coffea canephora. |
Ano de publicação: |
2017 |
Fonte/Imprenta: |
Tree Genetics & Genomes, v. 13, n. 95, 2017. |
Idioma: |
Inglês |
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 |
Palavras-Chave: |
GBLUP; Genotyping-by-sequencing; Multi-environment trials; Perennial crops. |
Thesaurus NAL: |
Marker-assisted selection. |
Categoria do assunto: |
-- |
URL: |
https://ainfo.cnptia.embrapa.br/digital/bitstream/item/168435/1/A-mixed-model-to-multiple-harvest-location.pdf
|
Marc: |
LEADER 02351naa a2200229 a 4500 001 2081803 005 2017-12-07 008 2017 bl uuuu u00u1 u #d 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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Embrapa Café (CNPCa) |
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