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| Registros recuperados : 70 | |
| 61. |  | PEREIRA, G. S.; PADILHA, L.; VON PINHO, E. V. R.; TEIXEIRA, R. de K. S.; CARVALHO, C. H. S. de; MALUF, M. P.; CARVALHO, B. L. de. Microsatellite markers in analysis of resistance to coffee leaf miner in Arabica coffee. Pesquisa agropecuária Brasileira, Brasília, v.46, n.12, p.1650-1656, dez. 2011| Biblioteca(s): Embrapa Café. |
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| 62. | | SILVA, M. S.; PATRICIO, F. R. A.; BRAGHINI, M. T.; SALOMÃO, D.; MALUF, M. P.; MARTINATI, J.; FAZUOLI, L. C.; GUERREIRO FILHO, O. Selection of coffee plants resistant to brown eye spot: genetic variability and influence of the nutritional condition on the expression of resistance to the pathogen. In: INTERNATIONAL CONFERENCE ON COFFEE SCIENCE, 24., 2012, Costa Rica. Programme & abstracts. [S.l.]: Association for Science and Information on Coffee, 2012. p. 201| Biblioteca(s): Embrapa Café. |
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| 63. | | CARVALHO, H. F.; FERRÃO, L. F. V.; GALLI, G.; NONATO, J. V. A.; PADILHA, L.; MALUF, M. P.; RESENDE JR., M. F. R. de; FRITSCHE-NETO, R.; GUERREIRO-FILHO, O. On the accuracy of threshold genomic prediction models for leaf miner and leaf rust resistance in arabica coffee. Tree Genetics & Genomes, v. 19, n. 1, 2023. 10 p.| Biblioteca(s): Embrapa Café. |
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| 64. | | CARVALHO, H. F.; GALLI, G.; FERRÃO, L. F. V.; NONATO, J. V. A.; PADILHA, L.; MALUF, M. P.; RESENDE JR, M. F. R. de; GUERREIRO FILHO, O.; FRITSCHE-NETO, R. The effect of bienniality on genomic prediction of yield in arabica coffee. Euphytica, v. 216, n. 101, p. 100-111, 2020.| Biblioteca(s): Embrapa Café. |
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| 65. | | QUINTERO, F. O. C.; PINTO, L. G.; BARSALOBRES-CAVALLARI, C. F.; ARCURI, M. de L. C.; PINO, L. E.; PERES, L. E. P.; MALUF, M. P.; MAIA, I. G. Identification of a seed maturation protein gene from Coffea arabica (CaSMP) and analysis of its promoter activity in tomato. Plant Cell Reports, v. 37, n.9, p.1257–1268, September 2018.| Biblioteca(s): Embrapa Café. |
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| 66. | | SILVESTRINI, M.; MALUF, M. P.; SILVAROLLA, M. B.; GUERREIRO-FILHO, O.; MEDINA-FILHO, H. P.; VANINI, M. M. T.; OLIVEIRA, A. S.; GAPARI-PEZZOPANE, C. de; FAZUOLI, L. C. Genetic diversity of a Coffea germplasm collection assessed by RAPD markers. GENETIC RESOURCE CROP EVOLUTION, v.55, n.6, p.901-910, 2008. 901-910| Biblioteca(s): Embrapa Café; Embrapa Unidades Centrais. |
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| 67. | | PEREIRA, L. F. P.; SCHENK, J. C. M.; MALUF, M. P.; SANT'ANA, G. C.; NOGUEIRA, L.; PEREIRA, L. A.; SILVA, B. S. R. da; GUIMARÃES, P. de S.; GUERREIRO FILHO, O.; PADILHA, L. Marcadores SNP avaliados em cultivares de Café Arábica. In: SIMPÓSIO DE PESQUISA DOS CAFÉS DO BRASIL, 10., 2019, Vitória. Pesquisa, Inovação e Sustentabilidade dos Cafés do Brasil. Anais... Brasília, DF: Embrapa Café, 2019. Título em inglês: SNP markers assessed in Arabica coffee cultivars.| Biblioteca(s): Embrapa Café. |
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| 68. | | BABA, V. Y.; BRAGHINI, M. T.; SANTOS, T. B. dos; CARVALHO, K. de; SOARES, J. D. M.; IVAMOTO-SUZUKI, S. T.; MALUF, M. P.; PADILHA, L.; PACCOLA-MEIRELLES, L. D.; PEREIRA, L. F. P.; DOMINGUES, D. S. Transcriptional patterns of Coffea arabica L. nitrate reductase, glutamine and asparagine synthetase genes are modulated under nitrogen suppression and coffee leaf rust. PeerJ, v. 8, e8320, 2020. eCollection 2020.| Biblioteca(s): Embrapa Café. |
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| 69. | | PRADO, G. S.; ROCHA, D. C.; SANTOS, L. N. dos; CONTILIANI, D. F.; NOBILE, P. M.; MARTINATI-SCHENK, J. C.; PADILHA, L.; MALUF, M. P.; LUBINI, G.; PEREIRA, T. C.; MONTEIRO-VITORELLO, C. B.; CRESTE, S.; BOSCARIOL-CAMARGO, R. L.; TAKITA, M. A.; CRISTOFANI-YALY, M.; SOUZA, A. A. de. CRISPR technology towards genome editing of the perennial and semi-perennial crops citrus, coffee and sugarcane. Frontiers in Plant Science, v. 14, article 1331258, 2023.| Biblioteca(s): Embrapa Café. |
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| 70. | | VIEIRA, L. G. E.; ANDRADE, A. C.; COLOMBO, C. A.; MORAES, A. H. de A.; METHA, A.; OLIVEIRA, A. C. de; LABATE, C. A.; MARINO, C. L.; MONTEIRO-VITORELLO, C. de B.; MONTE, D. C.; GIGLIOTI, E.; KIMURA, E. T.; ROMANO, E.; KURAMAE, E. E.; LEMOS, E. G. M.; ALMEIDA, E. R. P. de; JORGE, E. C.; ALBUQUERQUE, E. V. S.; SILVA, F. R. da; VINECKY, F.; SAWAZAKI, H. E.; DORRY, H. F. A.; CARRER, H.; ABREU, I. N.; BATISTA, J. A. N.; TEIXEIRA, J. B.; KITAJIMA, J. P.; XAVIER, K. G.; LIMA, L. M. de; CAMARGO, L. E. A. de; PEREIRA, L. F. P.; COUTINHO, L. L.; LEMOS, M. V. F.; ROMANO, M. R.; MACHADO, M. A.; COSTA, M. M. do C.; SÁ, M. F. G. de; GOLDMAN, M. H. S.; FERRO, M. I. T.; TINOCO, M. L. P.; OLIVEIRA, M. C.; VAN SLUYS, M-A.; SHIMIZU, M. M.; MALUF, M. P.; EIRA, M. T. S. da; GUERREIRO FILHO, O.; ARRUDA, P.; MAZZAFERA, P.; MARIANI, P. D. S. C.; OLIVEIRA, R. L. B. C. de; HARAKAVA, R.; BALBAO, S. F.; TSAI, S. M.; MAURO, S. M. Z. di; SANTOS, S. N.; SIQUEIRA, W. J.; COSTA, G. G. L.; FORMIGHIERI, E. F.; CARAZZOLLE, M. F.; PEREIRA, G. A. G. Brazilian coffee genome project: an EST-based genomic resource. Brazilian Journal of Plant Physiology, v. 18, n. 1, p. 95-108, 2006.| Biblioteca(s): Embrapa Recursos Genéticos e Biotecnologia. |
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| Registros recuperados : 70 | |
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Registro Completo
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Biblioteca(s): |
Embrapa Café. |
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Data corrente: |
21/08/2023 |
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Data da última atualização: |
21/08/2023 |
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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: |
CARVALHO, H. F.; FERRÃO, L. F. V.; GALLI, G.; NONATO, J. V. A.; PADILHA, L.; MALUF, M. P.; RESENDE JR., M. F. R. de; FRITSCHE-NETO, R.; GUERREIRO-FILHO, O. |
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Afiliação: |
HUMBERTO FANELLI CARVALHO, INSTITUTO AGRONÔMICO DE CAMPINAS; LUÍS FELIPE VENTORIM FERRÃO, UNIVERSITY OF FLORIDA; GIOVANNI GALLI, LOUISIANA STATE UNIVERSITY; JULIANA VIEIRA ALMEIDA NONATO, INSTITUTO AGRONÔMICO DE CAMPINAS; LILIAN PADILHA, CNPCa; MIRIAN PEREZ MALUF, CNPCa; MÁRCIO FERNANDO RIBEIRO DE RESENDE JR., UNIVERSITY OF FLORIDA; ROBERTO FRITSCHE-NETO, LOUISIANA STATE UNIVERSITY; OLIVEIRO GUERREIRO-FILHO, INSTITUTO AGRONÔMICO DE CAMPINAS. |
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Título: |
On the accuracy of threshold genomic prediction models for leaf miner and leaf rust resistance in arabica coffee. |
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Ano de publicação: |
2023 |
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Fonte/Imprenta: |
Tree Genetics & Genomes, v. 19, n. 1, 2023. |
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Páginas: |
10 p. |
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DOI: |
https://doi.org/10.1007/s11295-022-01581-8 |
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Idioma: |
Inglês |
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Conteúdo: |
Obtaining resistance cultivars for leaf miner and leaf rust are the main important strategy of Brazil?s national coffee breeding program. The narrow genetic basis, and founder effect consequences, lead to challenges in quantifying and detecting genetic diversity for these traits. Biotechnology tools allied with classical breeding strategies are powerful in detecting variability and deploying a precision selection. The selection based on the genetic merit of an individual obtained from thousands of single nucleotide polymorphism effects is known as genomic selection. The ordinal scale principally makes the resistance evaluation of the leaf rust and leaf miner of the score, categorizing the phenotypes following the discrete (ordinal) distribution. Hence, this distribution can be better analyzed by threshold models. Our goals were to optimize genomic prediction models for coffee resistance to leaf rust and leaf miner via threshold models and compare pedigree and genomic relationship matrices to underlying prediction models. We have observed that the genomic model with the genomic relationship matrix performed better for all scenarios. For the traits with at least five degrees of scores, the threshold models performed better, whereas for a trait with ten degrees of scores, we see no advantage to using a threshold model for genomic prediction. |
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Thesaurus NAL: |
Coffea arabica var. arabica; Genomics; Hemileia; Leaf rust; Leucoptera. |
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Categoria do assunto: |
-- |
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URL: |
https://ainfo.cnptia.embrapa.br/digital/bitstream/doc/1156023/1/On-the-accuracy-of-threshold-genomic-prediction.pdf
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Marc: |
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024 7 $ahttps://doi.org/10.1007/s11295-022-01581-8$2DOI
100 1 $aCARVALHO, H. F.
245 $aOn the accuracy of threshold genomic prediction models for leaf miner and leaf rust resistance in arabica coffee.$h[electronic resource]
260 $c2023
300 $a10 p.
520 $aObtaining resistance cultivars for leaf miner and leaf rust are the main important strategy of Brazil?s national coffee breeding program. The narrow genetic basis, and founder effect consequences, lead to challenges in quantifying and detecting genetic diversity for these traits. Biotechnology tools allied with classical breeding strategies are powerful in detecting variability and deploying a precision selection. The selection based on the genetic merit of an individual obtained from thousands of single nucleotide polymorphism effects is known as genomic selection. The ordinal scale principally makes the resistance evaluation of the leaf rust and leaf miner of the score, categorizing the phenotypes following the discrete (ordinal) distribution. Hence, this distribution can be better analyzed by threshold models. Our goals were to optimize genomic prediction models for coffee resistance to leaf rust and leaf miner via threshold models and compare pedigree and genomic relationship matrices to underlying prediction models. We have observed that the genomic model with the genomic relationship matrix performed better for all scenarios. For the traits with at least five degrees of scores, the threshold models performed better, whereas for a trait with ten degrees of scores, we see no advantage to using a threshold model for genomic prediction.
650 $aCoffea arabica var. arabica
650 $aGenomics
650 $aHemileia
650 $aLeaf rust
650 $aLeucoptera
700 1 $aFERRÃO, L. F. V.
700 1 $aGALLI, G.
700 1 $aNONATO, J. V. A.
700 1 $aPADILHA, L.
700 1 $aMALUF, M. P.
700 1 $aRESENDE JR., M. F. R. de
700 1 $aFRITSCHE-NETO, R.
700 1 $aGUERREIRO-FILHO, O.
773 $tTree Genetics & Genomes$gv. 19, n. 1, 2023.
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Embrapa Café (CNPCa) |
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