Data/hora: 04/06/2024 04:47:41

Biblioteca(s): | Embrapa Agroindústria de Alimentos.
Data corrente: | 12/07/2023
Data da última atualização: | 13/07/2023
Autoria: | STILO, F.; ALLADIO, E.; SQUARA, S.; BICCHI, C.; VICENTI, M.; REICHENBACH, S. E.; CORDERO, C.; BIZZO, H. R.
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.
Título: | Delineating unique and discriminant chemical traits in Brazilian and Italian extra-virgin olive oils by quantitative 2D-fingerprinting and pattern recognition algorithms.
Ano de publicação: | 2023
Fonte/Imprenta: | Journal of Food Composition and Analysis, v. 115, 104899, 2023.
DOI: | https://doi.org/10.1016/j.jfca.2022.104899
Idioma: | Inglês
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).
Palavras-Chave: | Aroma blueprint; Brazilian extra-virgin olive oil; Food volatiles analysis; Origin traceability; Quantitative fingerprinting.
Thesagro: | Composição de Alimento.
Thesaurus Nal: | Comprehensive two-dimensional gas chromatography; Food composition.
Categoria do assunto: | --
Registro original: | Embrapa Agroindústria de Alimentos (CTAA)
Exemplares: | CTAA - (15525-1) - UPC - AP - DD -  -  -  - DIS