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| Registros recuperados : 6 | |
| 5. |  | GARRETT, R.; SCHMIDT, E. M.; PEREIRA, L. F. P.; KITZBERGER, C. S. G.; SCHOLZ, M. B. S.; EBERLIN, M. N.; REZENDE, C. M. Discrimination of arabica coffee cultivars by electrospray ionization fourier transform ion cyclotron resonance mass spectrometry and chemometrics. LWT - Food Science and Technology, v. 50, n. 2, p. 496-502, 2013.| Biblioteca(s): Embrapa Café. |
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| 6. | | QUEIROZ, C. M.; SANTOS, G. J.; DESTRO, F. C.; TEIXEIRA, C. R.; PANTOJA, J. C.; SCHMIDT, E. M. S.; PALME, R.; FERREIRA, J. C. P. Resposta endócrina à contenção física e isolamento em papagaios-verdadeiros. Pesquisa Veterinária Brasileira, Brasília, DF, v. 36 (supl. 1), p. 41-45, jun. 2016.| Biblioteca(s): Embrapa Unidades Centrais. |
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 | Acesso ao texto completo restrito à biblioteca da Embrapa Café. Para informações adicionais entre em contato com biblioteca@embrapa.br. |
Registro Completo
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Biblioteca(s): |
Embrapa Café. |
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Data corrente: |
08/01/2024 |
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Data da última atualização: |
08/01/2024 |
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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: |
GARRETT, R.; SCHMIDT, E. M.; PEREIRA, L. F. P.; KITZBERGER, C. S. G.; SCHOLZ, M. B. S.; EBERLIN, M. N.; REZENDE, C. M. |
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Afiliação: |
RAFAEL GARRETT, UNIVERSIDADE FEDERAL DO RIO DE JANEIRO; EDUARDO M. SCHMIDT, UNIVERSIDADE ESTADUAL DE CAMPINAS; LUIZ FILIPE PROTASIO PEREIRA, CNPCa; CÍNTIA S. G. KITZBERGER, INSTITUTO AGRONÔMICO DO PARANÁ; MARIA BRÍGIDA S. SCHOLZ, INSTITUTO AGRONÔMICO DO PARANÁ; MARCOS N. EBERLIN, UNIVERSIDADE ESTADUAL DE CAMPINAS; CLAUDIA M. REZENDE, UNIVERSIDADE FEDERAL DO RIO DE JANEIRO. |
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Título: |
Discrimination of arabica coffee cultivars by electrospray ionization fourier transform ion cyclotron resonance mass spectrometry and chemometrics. |
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Ano de publicação: |
2013 |
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Fonte/Imprenta: |
LWT - Food Science and Technology, v. 50, n. 2, p. 496-502, 2013. |
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Idioma: |
Inglês |
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Conteúdo: |
Green beans of Coffee arabica (arabica coffee) cultivars with Sarchimor and Catuai genetic background were grown under the same edaphoclimatic conditions, in two different regions, and analysed by direct-infusion electrospray ionization Fourier transform ion cyclotron resonance mass spectrometry (ESI FT-ICR MS) followed by a metabolomic approach. A total of 20 coffee metabolites including phenolic compounds, fatty acids, sucrose, and diterpene glycosides were identified by negative ESI FT-ICR MS with a mass error <2 ppm. Furthermore, the multivariate data analysis techniques principal components analysis (PCA) and partial least squares-discriminant analysis (PLS-DA) successfully discriminated the arabica coffee cultivars with Sarchimor from those with Catuai genetic background, and also revealed the correlations between the coffee metabolites with the arabica cultivars and their growing region. This methodology could be used to identify coffee cultivars according to their genetic background as well as coffees from different growing regions, being a valuable tool for traceability and certification processes. |
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Thesagro: |
Coffea Arábica. |
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Thesaurus NAL: |
Chemometrics; Cultivars; Electrospray ionization mass spectrometry; Genetic background. |
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Categoria do assunto: |
-- |
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Marc: |
LEADER 01960naa a2200253 a 4500
001 2160510
005 2024-01-08
008 2013 bl uuuu u00u1 u #d
100 1 $aGARRETT, R.
245 $aDiscrimination of arabica coffee cultivars by electrospray ionization fourier transform ion cyclotron resonance mass spectrometry and chemometrics.$h[electronic resource]
260 $c2013
520 $aGreen beans of Coffee arabica (arabica coffee) cultivars with Sarchimor and Catuai genetic background were grown under the same edaphoclimatic conditions, in two different regions, and analysed by direct-infusion electrospray ionization Fourier transform ion cyclotron resonance mass spectrometry (ESI FT-ICR MS) followed by a metabolomic approach. A total of 20 coffee metabolites including phenolic compounds, fatty acids, sucrose, and diterpene glycosides were identified by negative ESI FT-ICR MS with a mass error <2 ppm. Furthermore, the multivariate data analysis techniques principal components analysis (PCA) and partial least squares-discriminant analysis (PLS-DA) successfully discriminated the arabica coffee cultivars with Sarchimor from those with Catuai genetic background, and also revealed the correlations between the coffee metabolites with the arabica cultivars and their growing region. This methodology could be used to identify coffee cultivars according to their genetic background as well as coffees from different growing regions, being a valuable tool for traceability and certification processes.
650 $aChemometrics
650 $aCultivars
650 $aElectrospray ionization mass spectrometry
650 $aGenetic background
650 $aCoffea Arábica
700 1 $aSCHMIDT, E. M.
700 1 $aPEREIRA, L. F. P.
700 1 $aKITZBERGER, C. S. G.
700 1 $aSCHOLZ, M. B. S.
700 1 $aEBERLIN, M. N.
700 1 $aREZENDE, C. M.
773 $tLWT - Food Science and Technology$gv. 50, n. 2, p. 496-502, 2013.
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