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Registro Completo |
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Biblioteca(s): |
Embrapa Agroindústria Tropical; Embrapa Soja. |
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Data corrente: |
18/01/2024 |
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Data da última atualização: |
22/01/2024 |
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Tipo da produção científica: |
Artigo em Periódico Indexado |
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Autoria: |
VELOSO, G. B. R.; ASSIS, R. P.; PEREIRA, J. A. S.; CARVALHO, F. A.; SOARES, C. P.; BRUNETTI, I. L.; ISAAC, V. L. B.; RIBEIRO, P. R. V.; ZOCOLO, G. J.; CORRÊA, M. A.; SANTOS, A. G. DOS. |
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Afiliação: |
GABRIELA BRASIL ROMÃO VELOSO, SÃO PAULO STATE UNIVERSITY; RENATA PIRES ASSIS, SÃO PAULO STATE UNIVERSITY; JUHAN AUGUSTO SCARDELATO PEREIRA, SÃO PAULO STATE UNIVERSITY; FLÁVIO ALEXANDRE CARVALHO, SÃO PAULO STATE UNIVERSITY; CHRISTIANE PIENNA SOARES, SÃO PAULO STATE UNIVERSITY; IGUATEMY LOURENÇO BRUNETTI, SÃO PAULO STATE UNIVERSITY; VERA LUCIA BORGES ISAAC, SÃO PAULO STATE UNIVERSITY; PAULO RICELI VASCONCELOS RIBEIRO, CNPAT; GUILHERME JULIAO ZOCOLO, CNPSO; MARCOS ANTÔNIO CORRÊA, SÃO PAULO STATE UNIVERSITY; ANDRÉ GONZAGA DOS SANTOS, SÃO PAULO STATE UNIVERSITY. |
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Título: |
Scavenging activity on reactive oxygen species with biological relevance by Varronia curassavica. |
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Ano de publicação: |
2023 |
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Fonte/Imprenta: |
Orbital: the Electronic Journal of Chemistry, v. 15, n. 2, p. 111-117, 2023. |
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DOI: |
https://doi.org/10.17807/orbital.v15i2.17939 |
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Idioma: |
Inglês |
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Palavras-Chave: |
Citotoxicidade; Espécies reativas de oxigênio; Estresse oxidativo; ROS. |
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Thesagro: |
Antioxidante; Cordia Verbenaceae. |
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Thesaurus Nal: |
Antioxidants; Cytotoxicity; Oxidative stress; Reactive oxygen species. |
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Categoria do assunto: |
--
X Pesquisa, Tecnologia e Engenharia |
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URL: |
https://ainfo.cnptia.embrapa.br/digital/bitstream/doc/1161053/1/ART-23039.pdf
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Marc: |
LEADER 01119naa a2200361 a 4500
001 2161053
005 2024-01-22
008 2023 bl uuuu u00u1 u #d
024 7 $ahttps://doi.org/10.17807/orbital.v15i2.17939$2DOI
100 1 $aVELOSO, G. B. R.
245 $aScavenging activity on reactive oxygen species with biological relevance by Varronia curassavica.$h[electronic resource]
260 $c2023
650 $aAntioxidants
650 $aCytotoxicity
650 $aOxidative stress
650 $aReactive oxygen species
650 $aAntioxidante
650 $aCordia Verbenaceae
653 $aCitotoxicidade
653 $aEspécies reativas de oxigênio
653 $aEstresse oxidativo
653 $aROS
700 1 $aASSIS, R. P.
700 1 $aPEREIRA, J. A. S.
700 1 $aCARVALHO, F. A.
700 1 $aSOARES, C. P.
700 1 $aBRUNETTI, I. L.
700 1 $aISAAC, V. L. B.
700 1 $aRIBEIRO, P. R. V.
700 1 $aZOCOLO, G. J.
700 1 $aCORRÊA, M. A.
700 1 $aSANTOS, A. G. DOS
773 $tOrbital: the Electronic Journal of Chemistry$gv. 15, n. 2, p. 111-117, 2023.
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Registro original: |
Embrapa Agroindústria Tropical (CNPAT) |
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Registro Completo
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Biblioteca(s): |
Embrapa Gado de Corte. |
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Data corrente: |
27/12/2022 |
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Data da última atualização: |
23/01/2023 |
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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: |
AONO, A. H.; FERREIRA, R. C. U.; MORAES, A. da C. L.; LARA, L. A. de C.; PIMENTA, R. J. G.; COSTA, E. A.; PINTO, L. R.; LANDELL, M. G. de A.; SANTOS, M. F.; JANK, L.; BARRIOS, S. C. L.; VALLE, C. B.; CHIARI, L.; GARCIA, A. A. F.; KUROSHU, R. M.; LORENA, A. C.; GORJANC, G.; SOUZA, A. P. de. |
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Afiliação: |
ALEXANDRE HILD AONO, UNIVERSIDADE DE CAMPINAS, UNIVERSITY OF EDINBURGH; REBECCA CAROLINE ULBRICHT FERREIRA, UNIVERSDIDADE DE CAMPINAS; ALINE DA COSTA LIMA MORAES, UNIVERSIDADE DE CAMPINAS; LETÍCIA APARECIDA DE CASTRO LARA, ESCOLA SUPERIOR DE AGRICULTURA "LUIZ DE QUEIROZ"; RICARDO JOSÉ GONZAGA PIMENTA, UNIVERSIDADE DE CAMPINAS; ESTELAARAUJO COSTA, UNIVEDRSIDADE FEDERAL DE SÃO PAULO; LUCIANA ROSSINI PINTO, INSTITUTO AGRONÔMICO DE CAMPINAS; MARCOS GUIMARÃES DE ANDRADE LANDELL, INSTITUTO AGRONÔMICO DE CAMPINAS; MATEUS FIGUEIREDO SANTOS, CNPGC; LIANA JANK, CNPGC; SANZIO CARVALHO LIMA BARRIOS, CNPGC; CACILDA BORGES DO VALLE, CNPGC; LUCIMARA CHIARI, CNPGC; ANTONIO AUGUSTO FRANCO GARCIA, ESCOLA SUPERIOR DE AGRICULTURA "LUIZ DE QUEIROZ"; REGINALDO MASSANOBU KUROSHU, UNIVERSIDADE FERDERAL DE SÃO PAULO; ANA CAROLINA LORENA, INSTITUTO TECNOLÓGICO DE AERONÁUTICA; GREGOR GORJANC, UNIVERSITY OF EDINBURGH; ANETE PEREIRA DE SOUZA, UNIVERSIDADE DE CAMPINAS. |
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Título: |
A joint learning approach for genomic prediction in polyploid grasses. |
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Ano de publicação: |
2022 |
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Fonte/Imprenta: |
Scientific Reports, 12, article 12499, 2022. |
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Páginas: |
17 p. |
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ISSN: |
2045-2322 |
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DOI: |
https://doi.org/10.1038/s41598-022-16417-7 |
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Idioma: |
Inglês |
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Conteúdo: |
Poaceae, among the most abundant plant families, includes many economically important polyploid species, such as forage grasses and sugarcane (Saccharum spp.). These species have elevated genomic complexities and limited genetic resources, hindering the application of marker-assisted selection strategies. Currently, the most promising approach for increasing genetic gains in plant breeding is genomic selection. However, due to the polyploidy nature of these polyploid species, more accurate models for incorporating genomic selection into breeding schemes are needed. This study aims to develop a machine learning method by using a joint learning approach to predict complex traits from genotypic data. Biparental populations of sugarcane and two species of forage grasses (Urochloa decumbens, Megathyrsus maximus) were genotyped, and several quantitative traits were measured. High-quality markers were used to predict several traits in diferent cross-validation scenarios. By combining classifcation and regression strategies, we developed a predictive system with promising results. Compared with traditional genomic prediction methods, the proposed strategy achieved accuracy improvements exceeding 50%. Our results suggest that the developed methodology could be implemented in breeding programs, helping reduce breeding cycles and increase genetic gains. |
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Thesagro: |
Cana de Açúcar; Gramínea Forrageira; Recurso Genético. |
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Thesaurus NAL: |
Forage grasses; Genetic resources; Plant breeding; Poaceae; Polyploidy; Saccharum; Sugarcane. |
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Categoria do assunto: |
-- |
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URL: |
https://ainfo.cnptia.embrapa.br/digital/bitstream/doc/1150365/1/Joint-learning-approach-genomic-2022.pdf
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Marc: |
LEADER 02671naa a2200481 a 4500
001 2150365
005 2023-01-23
008 2022 bl uuuu u00u1 u #d
022 $a2045-2322
024 7 $ahttps://doi.org/10.1038/s41598-022-16417-7$2DOI
100 1 $aAONO, A. H.
245 $aA joint learning approach for genomic prediction in polyploid grasses.$h[electronic resource]
260 $c2022
300 $a17 p.
520 $aPoaceae, among the most abundant plant families, includes many economically important polyploid species, such as forage grasses and sugarcane (Saccharum spp.). These species have elevated genomic complexities and limited genetic resources, hindering the application of marker-assisted selection strategies. Currently, the most promising approach for increasing genetic gains in plant breeding is genomic selection. However, due to the polyploidy nature of these polyploid species, more accurate models for incorporating genomic selection into breeding schemes are needed. This study aims to develop a machine learning method by using a joint learning approach to predict complex traits from genotypic data. Biparental populations of sugarcane and two species of forage grasses (Urochloa decumbens, Megathyrsus maximus) were genotyped, and several quantitative traits were measured. High-quality markers were used to predict several traits in diferent cross-validation scenarios. By combining classifcation and regression strategies, we developed a predictive system with promising results. Compared with traditional genomic prediction methods, the proposed strategy achieved accuracy improvements exceeding 50%. Our results suggest that the developed methodology could be implemented in breeding programs, helping reduce breeding cycles and increase genetic gains.
650 $aForage grasses
650 $aGenetic resources
650 $aPlant breeding
650 $aPoaceae
650 $aPolyploidy
650 $aSaccharum
650 $aSugarcane
650 $aCana de Açúcar
650 $aGramínea Forrageira
650 $aRecurso Genético
700 1 $aFERREIRA, R. C. U.
700 1 $aMORAES, A. da C. L.
700 1 $aLARA, L. A. de C.
700 1 $aPIMENTA, R. J. G.
700 1 $aCOSTA, E. A.
700 1 $aPINTO, L. R.
700 1 $aLANDELL, M. G. de A.
700 1 $aSANTOS, M. F.
700 1 $aJANK, L.
700 1 $aBARRIOS, S. C. L.
700 1 $aVALLE, C. B.
700 1 $aCHIARI, L.
700 1 $aGARCIA, A. A. F.
700 1 $aKUROSHU, R. M.
700 1 $aLORENA, A. C.
700 1 $aGORJANC, G.
700 1 $aSOUZA, A. P. de
773 $tScientific Reports, 12, article 12499, 2022.
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Embrapa Gado de Corte (CNPGC) |
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