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| Registros recuperados : 20 | |
| 1. |  | ALKIMIM, E. R.; SOUSA, T. V.; SILVA, F. L. da; SAKIYAMA, N. S.; ZAMBOLIM, L.; CAIXETA, E. T. Identificação e validação de marcadores SNP em Coffea canephora usando sequenciamento de nova geração. In: CONGRESSO BRASILEIRO DE MELHORAMENTO DE PLANTAS, 9., 2017, Foz de Iguaçu. Melhoramento de plantas: projetando o futuro. Maringá, PR: SBMP, 2017. p. 552| Biblioteca(s): Embrapa Café. |
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| 3. | | SOUSA, T. V. de; FRANCO, L. J. D.; SILVA, K. J. D. e; ROCHA, M. de M.; HASHIMOTO, J. M. Composição bromatológica e de elementos minerais em grãos de linhagens elites de feijão-mungo. In: JORNADA DE INICIAÇÃO CIENTÍFICA DA EMBRAPA MEIO-NORTE, 8., 2022, Teresina. Anais... Teresina: Embrapa Meio-Norte, 2023. p. 36. (Embrapa Meio-Norte. Documentos, 291).| Biblioteca(s): Embrapa Meio-Norte. |
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| 4. | | CORDEIRO, M. H. M.; BRUCKNER, C. H.; ROSADO, R. D. S.; SANTOS, C. E. M. dos; CAIXETA, E. T.; SOUSA, T. V.; CRUZ, C. D. Contribution of male genitors in open-pollination progenies of sour passion fruit. Euphytica, v. 216, n. 9, 2020.| Biblioteca(s): Embrapa Café. |
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| 5. | | SOUSA, T. V.; ALKIMIM, E. R.; OLIVEIRA, A. C. B. de; PEREIRA, A. A.; SAKIYAMA, N. S.; ZAMBOLIM, L.; CAIXETA, E. T. Estrutura de populações e diversidade genética de Coffea arabica analisadas por marcadores moleculares SNP. In: CONGRESSO BRASILEIRO DE MELHORAMENTO DE PLANTAS, 9., 2017, Foz de Iguaçu. Melhoramento de plantas: projetando o futuro. Maringá, PR: SBMP, 2017. p. 533| Biblioteca(s): Embrapa Café. |
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| 6. | | CAIXETA, E. T.; RESENDE, M. D. V. de; ALKIMIM, E. R.; SOUSA, T. V.; OLIVEIRA, A. C. B. de; PEREIRA, A. A.; ALVES, R. S. Aceleração do melhoramento do cafeeiro via seleção genômica: agilidade e eficácia no lançamento de novas cultivares. Brasília, DF: Embrapa Café, 2022. 54 p. PDF. (Embrapa Café. Documentos, 17). Projeto SI04 - Genotipagem e seleção genômica em populações de melhoramento de Coffea arabica.| Biblioteca(s): Embrapa Café. |
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| 7. | | SETOTAW, T. A.; CAIXETA, E. T.; ZAMBOLIM, E. M.; SOUSA, T. V.; PEREIRA, A. A.; OLIVEIRA, A. C. B. de; CRUZ, C. D.; ZAMBOLIM, L.; SAKYAMA, N. S. Genome introgression of Híbrido de Timor and its potential to develop high cup quality C. arabica cultivars. Journal of Agricultural Science, v. 12, n. 4, p. 64-76, 2020.| Biblioteca(s): Embrapa Café. |
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| 8. | | ALKIMIM, E. R.; CAIXETA, E. T.; SOUSA, T. V.; PEREIRA, A. A.; OLIVEIRA, A. C. B. de; ZAMBOLIM, L.; SAKIYAMA, N. S. Marker-assisted selection provides arabica coffee with genes from other Coffea species targeting on multiple resistance to rust and coffee berry disease. Molecular Breeding, v. 37, n. 6, p. 1-10, jan. 2017.| Biblioteca(s): Embrapa Café. |
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| 9. | | SOUSA, T. V.; CAIXETA, E. T.; ALKIMIM, E. R.; OLIVEIRA, A. C. B. de; PEREIRA, A. A.; ZAMBOLIM, E. M.; ZAMBOLIM, L.; SAKIYAMA, N. S. Caracterização molecular de cultivares de café resistentes à ferrugem. In: SIMPÓSIO DE PESQUISA DOS CAFÉS DO BRASIL, 8., 2013, Salvador. Sustentabilidade e inclusão Social. Brasília, DF: Embrapa Café, 2013.| Biblioteca(s): Embrapa Café. |
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| 10. | | MEDEIROS, A. C.; CAIXETA, E. T.; OLIVEIRA, A. C. B. de; SOUSA, T. V.; STOCK, V. de M.; CRUZ, C. D.; ZAMBOLIM, L.; PEREIRA, A. P. Combining ability and molecular marker approach identified genetic resources to improve agronomic performance in coffea arabica breeding. Frontiers in Sustainable Food Systems, v. 5, 705278, 2021.| Biblioteca(s): Embrapa Café. |
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| 11. | | RESENDE, M. D. V. de; OLIVEIRA, A. C. B. de; CAIXETA, E. T.; ALKIMIM, E. R.; SOUSA, T. V.; PEREIRA, A. A.; ALVES, R. S.; AZEVEDO, C. F. Tamanho amostral e detecção de genes via GWAS em características quantitativas do cafeeiro. Brasília, DF: Embrapa Café, 2022. 23 p. (Embrapa Café. Circular técnica, 7).| Biblioteca(s): Embrapa Café. |
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| 12. | | SOUSA, T. V.; CAIXETA, E. T.; ALKIMIM, E. R.; OLIVEIRA, A. C. B. de; PEREIRA, A. A.; SAKIYAMA, N. S.; ZAMBOLIM, L.; RESENDE, M. D. V. de. Early Selection Enabled by the Implementation of Genomic Selection in Coffea arabica Breeding. Frontiers in Plant Science, v. 9, January 2019.| Biblioteca(s): Embrapa Café; Embrapa Florestas. |
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| 13. | | CRUZ, A. F.; SIVA, L. F.; SOUSA, T. V.; NICOLI, A.; PAULA JUNIOR, T. J. de; CAIXETA, E. T.; ZAMBOLIM, L. Molecular diversity in Fusarium oxysporum isolates from common bean fields in Brazil. European Journal of Plant Pathology, v. 152, n. 2, p. 343-354, 2018.| Biblioteca(s): Embrapa Café. |
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| 14. | | SOUSA, T. V.; CAIXETA, E. T.; ALKIMIM, E. R.; OLIVEIRA, A. C. B. de; PEREIRA, A. A.; ZAMBOLIM, L.; SAKIYAMA, N. S. Molecular markers useful to discriminate Coffea arabica cultivars with high genetic similarity. Euphytica, v. 213, n. 3, March, 2017.| Biblioteca(s): Embrapa Café. |
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| 15. | | SOUSA, T. V.; CAIXETA, E. T.; ALKIMIM, E. R.; OLIVEIRA, A. C. B. de; PEREIRA, A. A.; SAKIYAMA, N. S.; RESENDE JÚNIOR, M. F. R. de; ZAMBOLIM, L. Population structure and genetic diversity of coffee progenies derived from Catuaí and Híbrido de Timor revealed by genome-wide SNP marker. Tree Genetics & Genomes, v. 13, n. 6, Dec. 2017.| Biblioteca(s): Embrapa Café. |
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| 16. | | ALKIMIM, E. R.; CAIXETA, E. T.; SOUSA, T. V.; RESENDE, M. D. V. de; SILVA, F. L. da; SAKIYAMA, N. S.; ZAMBOLIM, L. Selective efficiency of genome-wide selection in Coffea canephora breeding. Tree Genetics & Genomes, v. 16, n. 3, p. 1-11, 2020.| Biblioteca(s): Embrapa Café. |
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| 17. | | ALKIMIM, E. R.; CAIXETA, E. T.; SOUSA, T. V.; OLIVEIRA, A. C. B. de; PEREIRA, A. A.; ZAMBOLIM, E. M.; ZAMBOLIM, L.; SAKIYAMA, N. S. Seleção assistida por marcadores moleculares para resistência à ferrugem do cafeeiro. In: CONGRESSO BRASILEIRO DE MELHORAMENTO DE PLANTAS, 8., 2015, Goiânia. O melhoramento de plantas, o futuro da agricultura e a soberania nacional: anais. Goiânia: UFG: SBMP, 2015.| Biblioteca(s): Embrapa Café. |
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| 18. | | GUEDES, M. C.; RODRIGUES, E. G.; AUCA, E. C.; TORRES, D. del C.; WADT, L. H. de O.; GOMES, J. K. da S.; NEVES, E. de S.; SOUSA, T. V. A. de. Alternativas de baixo custo para produção de mudas. In: WADT, L. H. de O.; MAROCCOLO, J. F.; GUEDES, M. C.; SILVA, K. E. da (ed.). Castanha-da-amazônia: estudos sobre a espécie e sua cadeia de valor. Brasília, DF: Embrapa, 2023. v. 4, cap. 3, p. 65-87. ODS 2, ODS 3, ODS 8, ODS 11, ODS 12, ODS 13, ODS 17.| Biblioteca(s): Embrapa Amapá; Embrapa Rondônia. |
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| 19. | | SILVA, L. de F.; ALKIMIM, E. R.; BARREIRO, P. R. R. M.; LEICHTWEIS, B. G.; SILVA, A. C. A.; SILVA, R. A. da; SOUSA, T. V.; NASCIMENTO, M.; CAIXETA, E. T. Genome-wide association study of plant architecture and diseases resistance in Coffea canephora. Euphytica, v. 218, jun. 2022. 13 p.| Biblioteca(s): Embrapa Café. |
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| 20. | | ALKIMIM, E. R.; CAIXETA, E. T.; SOUSA, T. V.; GOIS, I. B.; SILVA, F. L. da; SAKIYAMA, N. S.; ZAMBOLIM, L.; ALVES, R. S.; RESENDE, M. D. V. de. Designing the best breeding strategy for Coffea canephora: Genetic evaluation of pure and hybrid individuals aiming to select for productivity and disease resistance traits. Plos One, v. 16, n. 12, e0260997, 2021.| Biblioteca(s): Embrapa Café. |
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| Registros recuperados : 20 | |
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Registro Completo
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Biblioteca(s): |
Embrapa Café; Embrapa Florestas. |
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Data corrente: |
19/02/2019 |
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Data da última atualização: |
17/10/2019 |
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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: |
SOUSA, T. V.; CAIXETA, E. T.; ALKIMIM, E. R.; OLIVEIRA, A. C. B. de; PEREIRA, A. A.; SAKIYAMA, N. S.; ZAMBOLIM, L.; RESENDE, M. D. V. de. |
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Afiliação: |
TIAGO VIEIRA SOUSA, BIOAGRO/BioCafé/Universidade Federal de Viçosa - UFV; EVELINE TEIXEIRA CAIXETA, CNPCa; EMILLY RUAS ALKIMIM, Universidade Federal do Triângulo Mineiro - UFTM; ANTONIO CARLOS BAIAO DE OLIVEIRA, CNPCa; ANTONIO ALVES PEREIRA, Empresa de Pesquisa Agropecuária de Minas Gerais – Epamig; NEY SUSSUMU SAKIYAMA, Universidade Federal de Viçosa - UFV/Departamento de Fitotecnia; LAÉRCIO ZAMBOLIM, Universidade Federal de Viçosa - UFV/Departamento de Fitopatologia; MARCOS DEON VILELA DE RESENDE, CNPF. |
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Título: |
Early Selection Enabled by the Implementation of Genomic Selection in Coffea arabica Breeding. |
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Ano de publicação: |
2019 |
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Fonte/Imprenta: |
Frontiers in Plant Science, v. 9, January 2019. |
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Idioma: |
Inglês |
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Conteúdo: |
Genomic Selection (GS) has allowed the maximization of genetic gains per unit time in several annual and perennial plant species. However, no GS studies have addressed Coffea arabica, the most economically important species of the genus Coffea. Therefore, this study aimed (i) to evaluate the applicability and accuracy of GS in the prediction of the genomic estimated breeding value (GEBV); (ii) to estimate the genetic parameters; and (iii) to evaluate the time reduction of the selection cycle by GS in Arabica coffee breeding. A total of 195 Arabica coffee individuals, belonging to 13 families in generation of F2, susceptible backcross and resistant backcross, were phenotyped for 18 agronomic traits, and genotyped with 21,211 SNP molecular markers. Phenotypic data, measured in 2014, 2015, and 2016, were analyzed by mixed models. GS analyses were performed by the G-BLUPmethod, using the RKHS (Reproducing Kernel Hilbert Spaces) procedure, with a Bayesian algorithm. Heritabilities and selective accuracies were estimated, revealing moderate to high magnitude for most of the traits evaluated. Results of GS analyses showed the possibility of reducing the cycle time by 50%, maximizing selection gains per unit time. The effect of marker density on GS analyses was evaluated. Genomic selection proved to be promising for C. arabica breeding. The agronomic traits presented high complexity for they are controlled by several QTL and showed low genomic heritabilities, evidencing the need to incorporate genomic selection methodologies to the breeding programs of this species. MenosGenomic Selection (GS) has allowed the maximization of genetic gains per unit time in several annual and perennial plant species. However, no GS studies have addressed Coffea arabica, the most economically important species of the genus Coffea. Therefore, this study aimed (i) to evaluate the applicability and accuracy of GS in the prediction of the genomic estimated breeding value (GEBV); (ii) to estimate the genetic parameters; and (iii) to evaluate the time reduction of the selection cycle by GS in Arabica coffee breeding. A total of 195 Arabica coffee individuals, belonging to 13 families in generation of F2, susceptible backcross and resistant backcross, were phenotyped for 18 agronomic traits, and genotyped with 21,211 SNP molecular markers. Phenotypic data, measured in 2014, 2015, and 2016, were analyzed by mixed models. GS analyses were performed by the G-BLUPmethod, using the RKHS (Reproducing Kernel Hilbert Spaces) procedure, with a Bayesian algorithm. Heritabilities and selective accuracies were estimated, revealing moderate to high magnitude for most of the traits evaluated. Results of GS analyses showed the possibility of reducing the cycle time by 50%, maximizing selection gains per unit time. The effect of marker density on GS analyses was evaluated. Genomic selection proved to be promising for C. arabica breeding. The agronomic traits presented high complexity for they are controlled by several QTL and showed low genomic heritabilities, evidencing the need to ... Mostrar Tudo |
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Palavras-Chave: |
Accelerating improvement; Complex traits; Ganho genético; Genetic gains; Genomic-enabled prediction accuracy; Selective efficiency; SNP molecular marker. |
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Thesagro: |
Café; Coffea Arábica. |
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Thesaurus NAL: |
Plant breeding. |
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Categoria do assunto: |
--
G Melhoramento Genético |
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URL: |
https://ainfo.cnptia.embrapa.br/digital/bitstream/item/193820/1/Early-selection-enabled-by-the-implementation.pdf
https://ainfo.cnptia.embrapa.br/digital/bitstream/item/197479/1/2019-M.Deon-FPS-Early.pdf
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Marc: |
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100 1 $aSOUSA, T. V.
245 $aEarly Selection Enabled by the Implementation of Genomic Selection in Coffea arabica Breeding.$h[electronic resource]
260 $c2019
520 $aGenomic Selection (GS) has allowed the maximization of genetic gains per unit time in several annual and perennial plant species. However, no GS studies have addressed Coffea arabica, the most economically important species of the genus Coffea. Therefore, this study aimed (i) to evaluate the applicability and accuracy of GS in the prediction of the genomic estimated breeding value (GEBV); (ii) to estimate the genetic parameters; and (iii) to evaluate the time reduction of the selection cycle by GS in Arabica coffee breeding. A total of 195 Arabica coffee individuals, belonging to 13 families in generation of F2, susceptible backcross and resistant backcross, were phenotyped for 18 agronomic traits, and genotyped with 21,211 SNP molecular markers. Phenotypic data, measured in 2014, 2015, and 2016, were analyzed by mixed models. GS analyses were performed by the G-BLUPmethod, using the RKHS (Reproducing Kernel Hilbert Spaces) procedure, with a Bayesian algorithm. Heritabilities and selective accuracies were estimated, revealing moderate to high magnitude for most of the traits evaluated. Results of GS analyses showed the possibility of reducing the cycle time by 50%, maximizing selection gains per unit time. The effect of marker density on GS analyses was evaluated. Genomic selection proved to be promising for C. arabica breeding. The agronomic traits presented high complexity for they are controlled by several QTL and showed low genomic heritabilities, evidencing the need to incorporate genomic selection methodologies to the breeding programs of this species.
650 $aPlant breeding
650 $aCafé
650 $aCoffea Arábica
653 $aAccelerating improvement
653 $aComplex traits
653 $aGanho genético
653 $aGenetic gains
653 $aGenomic-enabled prediction accuracy
653 $aSelective efficiency
653 $aSNP molecular marker
700 1 $aCAIXETA, E. T.
700 1 $aALKIMIM, E. R.
700 1 $aOLIVEIRA, A. C. B. de
700 1 $aPEREIRA, A. A.
700 1 $aSAKIYAMA, N. S.
700 1 $aZAMBOLIM, L.
700 1 $aRESENDE, M. D. V. de
773 $tFrontiers in Plant Science$gv. 9, January 2019.
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Registro original: |
Embrapa Café (CNPCa) |
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