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 | Acesso ao texto completo restrito à biblioteca da Embrapa Agroindústria de Alimentos. Para informações adicionais entre em contato com ctaa.biblioteca@embrapa.br. |
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Registro Completo |
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Biblioteca(s): |
Embrapa Agroindústria de Alimentos. |
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Data corrente: |
12/07/2023 |
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Data da última atualização: |
13/07/2023 |
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Tipo da produção científica: |
Artigo em Periódico Indexado |
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Autoria: |
STILO, F.; ALLADIO, E.; SQUARA, S.; BICCHI, C.; VICENTI, M.; REICHENBACH, S. E.; CORDERO, C.; BIZZO, H. R. |
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Afiliação: |
FEDERICO STILO, Università degli Studi di Torino; EUGENIO ALLADIO, Università degli Studi di Torino; Centro Regionale Antidoping e di Tossicologia A. Bertinaria; SIMONE SQUARA, Università degli Studi di Torino; CARLO BICCHI, Università degli Studi di Torino; MARCO VINCENTI, Università degli Studi di Torino; STEPHEN E. REICHENBACH, University of Nebraska; e GC Image LLC; CHIARA CORDERO, Università degli Studi di Torino; HUMBERTO RIBEIRO BIZZO, CTAA. |
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Título: |
Delineating unique and discriminant chemical traits in Brazilian and Italian extra-virgin olive oils by quantitative 2D-fingerprinting and pattern recognition algorithms. |
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Ano de publicação: |
2023 |
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Fonte/Imprenta: |
Journal of Food Composition and Analysis, v. 115, 104899, 2023. |
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DOI: |
https://doi.org/10.1016/j.jfca.2022.104899 |
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Idioma: |
Inglês |
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Conteúdo: |
Brazil is the second-largest importer, after the United States, of extra-virgin olive oils with an internal production that just reaches 0.25 % of the volume imported and consumed. Information about diagnostic chemical signatures characterizing Brazilian oils is lacking, especially as related to geographical markers and key-aroma compounds distribution. This study fills this gap; by comprehensive two-dimensional gas chromatography (GC×GC) combined with headspace solid-phase microextraction (HS-SPME) and parallel detection (MS/FID), diagnostic quali-quantitative signatures of volatiles from Brazilian oils are obtained. Comprehensively mapping of untargeted and targeted (UT) features through fingerprinting algorithms provides effective classification models, benchmarking Brazilian oils (n = 28) vs. a large selection of Italian high-quality extra-virgin olive oils (n = 111). Identitation of Brazilian oils is achieved by combining six different feature selection strategies, the resulting pattern of predictors includes: 1-methoxy-2-propanol, ethyl acetate, (E)-4,8-dimethyl-1,3,7-nonatriene, propanoic acid, limonene, (E)-2-hexenal, hexanoic acid, pentanal, butanoic acid, hexanal, ?-pinene, (E)-?-ocimene, and propanal. Compositional differences also are evidenced in composite-class images resembling 2D patterns characteristic of the two production areas. Quantitative fingerprinting, resembling an artificial intelligence smelling machine, characterizes the unique aroma with 1-penten-3-one and (Z)? 3-hexenal, dominating with pungent and green notes, followed by (E)? 2-hexenal (bitter-almond), (E,E)? 2,4-heptadienal (fatty), eucalyptol (herbal), benzaldehyde (almond), hexanal (green), and (E)? 2-hexen-1-ol (green grass). MenosBrazil is the second-largest importer, after the United States, of extra-virgin olive oils with an internal production that just reaches 0.25 % of the volume imported and consumed. Information about diagnostic chemical signatures characterizing Brazilian oils is lacking, especially as related to geographical markers and key-aroma compounds distribution. This study fills this gap; by comprehensive two-dimensional gas chromatography (GC×GC) combined with headspace solid-phase microextraction (HS-SPME) and parallel detection (MS/FID), diagnostic quali-quantitative signatures of volatiles from Brazilian oils are obtained. Comprehensively mapping of untargeted and targeted (UT) features through fingerprinting algorithms provides effective classification models, benchmarking Brazilian oils (n = 28) vs. a large selection of Italian high-quality extra-virgin olive oils (n = 111). Identitation of Brazilian oils is achieved by combining six different feature selection strategies, the resulting pattern of predictors includes: 1-methoxy-2-propanol, ethyl acetate, (E)-4,8-dimethyl-1,3,7-nonatriene, propanoic acid, limonene, (E)-2-hexenal, hexanoic acid, pentanal, butanoic acid, hexanal, ?-pinene, (E)-?-ocimene, and propanal. Compositional differences also are evidenced in composite-class images resembling 2D patterns characteristic of the two production areas. Quantitative fingerprinting, resembling an artificial intelligence smelling machine, characterizes the unique aroma with 1-penten... Mostrar Tudo |
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Palavras-Chave: |
Aroma blueprint; Brazilian extra-virgin olive oil; Food volatiles analysis; Origin traceability; Quantitative fingerprinting. |
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Thesagro: |
Composição de Alimento. |
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Thesaurus Nal: |
Comprehensive two-dimensional gas chromatography; Food composition. |
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Categoria do assunto: |
-- |
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Marc: |
LEADER 02823naa a2200313 a 4500
001 2154900
005 2023-07-13
008 2023 bl uuuu u00u1 u #d
024 7 $ahttps://doi.org/10.1016/j.jfca.2022.104899$2DOI
100 1 $aSTILO, F.
245 $aDelineating unique and discriminant chemical traits in Brazilian and Italian extra-virgin olive oils by quantitative 2D-fingerprinting and pattern recognition algorithms.$h[electronic resource]
260 $c2023
520 $aBrazil is the second-largest importer, after the United States, of extra-virgin olive oils with an internal production that just reaches 0.25 % of the volume imported and consumed. Information about diagnostic chemical signatures characterizing Brazilian oils is lacking, especially as related to geographical markers and key-aroma compounds distribution. This study fills this gap; by comprehensive two-dimensional gas chromatography (GC×GC) combined with headspace solid-phase microextraction (HS-SPME) and parallel detection (MS/FID), diagnostic quali-quantitative signatures of volatiles from Brazilian oils are obtained. Comprehensively mapping of untargeted and targeted (UT) features through fingerprinting algorithms provides effective classification models, benchmarking Brazilian oils (n = 28) vs. a large selection of Italian high-quality extra-virgin olive oils (n = 111). Identitation of Brazilian oils is achieved by combining six different feature selection strategies, the resulting pattern of predictors includes: 1-methoxy-2-propanol, ethyl acetate, (E)-4,8-dimethyl-1,3,7-nonatriene, propanoic acid, limonene, (E)-2-hexenal, hexanoic acid, pentanal, butanoic acid, hexanal, ?-pinene, (E)-?-ocimene, and propanal. Compositional differences also are evidenced in composite-class images resembling 2D patterns characteristic of the two production areas. Quantitative fingerprinting, resembling an artificial intelligence smelling machine, characterizes the unique aroma with 1-penten-3-one and (Z)? 3-hexenal, dominating with pungent and green notes, followed by (E)? 2-hexenal (bitter-almond), (E,E)? 2,4-heptadienal (fatty), eucalyptol (herbal), benzaldehyde (almond), hexanal (green), and (E)? 2-hexen-1-ol (green grass).
650 $aComprehensive two-dimensional gas chromatography
650 $aFood composition
650 $aComposição de Alimento
653 $aAroma blueprint
653 $aBrazilian extra-virgin olive oil
653 $aFood volatiles analysis
653 $aOrigin traceability
653 $aQuantitative fingerprinting
700 1 $aALLADIO, E.
700 1 $aSQUARA, S.
700 1 $aBICCHI, C.
700 1 $aVICENTI, M.
700 1 $aREICHENBACH, S. E.
700 1 $aCORDERO, C.
700 1 $aBIZZO, H. R.
773 $tJournal of Food Composition and Analysis$gv. 115, 104899, 2023.
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