Data/hora: 26/09/2024 22:26:49

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