In the last years, olive oil authentication issues have become topics of prominent importance, not only for consumers, but also for suppliers, retailers, and administrative authorities, and particularly for assurance of public health. In this work, the sterolic and phenolic profile of Tunisian and Italian extra-virgin olive oil (EVOO) samples was depicted using an untargeted UHPLC-ESI/QTOF mass spectrometry approach. Polyphenols and sterols were quantified according to their chemical sub-classes, with high sterols (around 1000 up to 2000 mg/kg) and tyrosols (on average 420.2 mg/kg) contents detected. The metabolomics data were elaborated by means of multivariate statistics, i.e. unsupervised hierarchical cluster analysis and orthogonal projections to latent structures discriminant analysis (OPLS-DA). This approach allowed identifying the best markers (i.e. hydroxybenzoic acids, cholesterol and stigmasterol derivatives) of the geographical origin able to discriminate Tunisian and Italian EVOO samples, showing the potential of sterolic and phenolic fingerprints for olive oil authenticity evaluations.

Discrimination of Tunisian and Italian extra-virgin olive oils according to their phenolic and sterolic fingerprints

Montesano, Domenico
Data Curation
;
2018

Abstract

In the last years, olive oil authentication issues have become topics of prominent importance, not only for consumers, but also for suppliers, retailers, and administrative authorities, and particularly for assurance of public health. In this work, the sterolic and phenolic profile of Tunisian and Italian extra-virgin olive oil (EVOO) samples was depicted using an untargeted UHPLC-ESI/QTOF mass spectrometry approach. Polyphenols and sterols were quantified according to their chemical sub-classes, with high sterols (around 1000 up to 2000 mg/kg) and tyrosols (on average 420.2 mg/kg) contents detected. The metabolomics data were elaborated by means of multivariate statistics, i.e. unsupervised hierarchical cluster analysis and orthogonal projections to latent structures discriminant analysis (OPLS-DA). This approach allowed identifying the best markers (i.e. hydroxybenzoic acids, cholesterol and stigmasterol derivatives) of the geographical origin able to discriminate Tunisian and Italian EVOO samples, showing the potential of sterolic and phenolic fingerprints for olive oil authenticity evaluations.
2018
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11391/1423409
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