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| 2. |  | CORRÊA, C. L. O.; LUNA, A. S.; PENHA, E. das M.; GOTTSCHALK, L. M. F. Determinação de acrilamida por espectrofluorêscencia em amostras de café. In: CONGRESSO BRASILEIRO DE PESQUISA S CAFEEIRAS, 44., 2018, Franca, SP. O Nosso café, melhorados desde o pé: Trabalhos apresentados. Varginha: Fundação Procafé, 2018. p. 182-183 23 a 26 out. 2018. Seção 4.5. Colheita, preparo, qualidade do café, consumo e saúde.| Biblioteca(s): Embrapa Agroindústria de Alimentos. |
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| 5. | | CORRÊA, C. L. O.; PENHA, E. das M.; ANJOS, M. R. dos; PACHECO, S.; FREITAS-SILVA, O.; LUNA, A. S.; GOTTSCHALK, L. M. F. Use of asparaginase for acrylamide mitigation in coffee and its influence on the content of caffeine, chlorogenic acid, and caffeic acid. Food Chemistry, v. 338, 128045, 6 p., fev. 2021.| Biblioteca(s): Embrapa Agroindústria de Alimentos. |
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 | Acesso ao texto completo restrito à biblioteca da Embrapa Rondônia. Para informações adicionais entre em contato com cpafro.biblioteca@embrapa.br. |
Registro Completo
|
Biblioteca(s): |
Embrapa Rondônia. |
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Data corrente: |
16/12/2021 |
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Data da última atualização: |
15/03/2023 |
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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: |
ROBERT, J. V.; GOIS, J. S. de; ROCHA, R. B.; LUNA, A. S. |
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Afiliação: |
JARBAS VERISSIMO ROBERT, Rio de Janeiro State University; JEFFERSON S. DE GOIS, Rio de Janeiro State University; RODRIGO BARROS ROCHA, CPAF-RO; ADERVAL S. LUNA, Rio de Janeiro State University. |
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Título: |
Direct solid sample analysis using synchronous fluorescence spectroscopy coupled with chemometric tools for the geographical discrimination of coffee samples. |
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Ano de publicação: |
2022 |
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Fonte/Imprenta: |
Food Chemistry, v. 371, 131063, 2022. |
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ISSN: |
0308-8146 |
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DOI: |
https://doi.org/10.1016/j.foodchem.2021.131063 |
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Idioma: |
Inglês |
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Conteúdo: |
This work aims the study chemometric methods for the classification of the origin of coffee samples. Samples of finely pulverized coffee grains were analyzed by synchronous molecular fluorescence spectroscopy to carry out the classification. The spectral data of the samples were obtained in triplicate in two offsets: 10 nm (with emission wavelengths from 240 nm to 600 nm) and 40 nm (from 240 nm to 560 nm), all with 1 nm resolution. Different strategies were performed using the spectra obtained with the offsets of 10 nm and 40 nm and fused data at mid-level (10 nm + 40 nm). The performances of linear and nonlinear methods were compared, the best results were obtained from the raw data from the fusion at low-level of the 10 nm and 40 nm offset spectra with the Pareto optimization criterion. |
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Palavras-Chave: |
Amazônia Ocidental; Rondônia; Western Amazon. |
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Thesagro: |
Café; Coffea Canephora; Composição Química; Distribuição Geográfica; Método de Análise. |
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Thesaurus NAL: |
Chemical analysis; Chemical composition; Geographical distribution; X-ray fluorescence spectroscopy. |
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Categoria do assunto: |
F Plantas e Produtos de Origem Vegetal |
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Marc: |
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001 2137961
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022 $a0308-8146
024 7 $ahttps://doi.org/10.1016/j.foodchem.2021.131063$2DOI
100 1 $aROBERT, J. V.
245 $aDirect solid sample analysis using synchronous fluorescence spectroscopy coupled with chemometric tools for the geographical discrimination of coffee samples.$h[electronic resource]
260 $c2022
520 $aThis work aims the study chemometric methods for the classification of the origin of coffee samples. Samples of finely pulverized coffee grains were analyzed by synchronous molecular fluorescence spectroscopy to carry out the classification. The spectral data of the samples were obtained in triplicate in two offsets: 10 nm (with emission wavelengths from 240 nm to 600 nm) and 40 nm (from 240 nm to 560 nm), all with 1 nm resolution. Different strategies were performed using the spectra obtained with the offsets of 10 nm and 40 nm and fused data at mid-level (10 nm + 40 nm). The performances of linear and nonlinear methods were compared, the best results were obtained from the raw data from the fusion at low-level of the 10 nm and 40 nm offset spectra with the Pareto optimization criterion.
650 $aChemical analysis
650 $aChemical composition
650 $aGeographical distribution
650 $aX-ray fluorescence spectroscopy
650 $aCafé
650 $aCoffea Canephora
650 $aComposição Química
650 $aDistribuição Geográfica
650 $aMétodo de Análise
653 $aAmazônia Ocidental
653 $aRondônia
653 $aWestern Amazon
700 1 $aGOIS, J. S. de
700 1 $aROCHA, R. B.
700 1 $aLUNA, A. S.
773 $tFood Chemistry$gv. 371, 131063, 2022.
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