Journal
JOURNAL OF THE SCIENCE OF FOOD AND AGRICULTURE
Volume 98, Issue 2, Pages 681-690Publisher
WILEY
DOI: 10.1002/jsfa.8515
Keywords
Voltammetric electronic tongue; layer-by-layer films; electrochemical sensors; HS-GC-MS analysis; physicochemical analysis; olive oils
Funding
- Centre National pour la Recherche Scientifique et Technique (CNRST - Maroc)
- Fundacao para a Ciencia e Tecnologia (FCT-Portugal) [Chimie/01 13/14]
- Moulay Ismail University
- FCT-Portugal [PEst-OE/FIS/UI0068/2011]
- [SFRH/BD/62229/2009]
- Fundação para a Ciência e a Tecnologia [SFRH/BD/62229/2009] Funding Source: FCT
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BACKGROUNDIn this paper, various extra-virgin and virgin olive oils samples from different Portuguese markets were studied. For this purpose, a voltammetric electronic tongue (VE-tongue), consisting of two kinds of working electrode within the array, together with physicochemical analysis and headspace gas chromatography coupled with mass spectrometry (HS-GC-MS), were applied. In addition, preliminary considerations of relationships between physicochemical parameters and multisensory system were reported. RESULTSThe physicochemical parameters exhibit significant differences among the analyzed olive oil samples that define its qualities. Regarding the aroma profile, 14 volatile compounds were characterized using HS-GC-MS; among these, hex-2-enal, hexanal, acetic acid, hex-3-ene-1-ol acetate and hex-3-en-1-ol were semi-quantitatively detected as the main aroma compounds in the analyzed samples. Moreover, pattern recognition methods demonstrate the discrimination power of the proposed VE-tongue system. The results reveal the VE-tongue's ability to classify olive oil samples and to identify unknown samples based of built models. In addition, the correlation between VE-tongue and physicochemical analysis exhibits a remarkable prediction model aimed at anticipating carotenoid content. CONCLUSIONThe preliminary results of this investigation indicate that physicochemical and HS-GC-MS analysis, together with multisensory system coupled with chemometric techniques, presented a satisfactory performance regarding olive oil sample discrimination and identification. (c) 2017 Society of Chemical Industry
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