There is increasing interest in controlling EVOO quality on the market in order to maintain its high economic value and to protect the consumer from fraud. Here we developed a new pipeline to assess the quality of olive oil. Over five olive oil crop-years 792 oil samples were simultaneously evaluated by a Proton Transfer Reaction Time of Flight Mass Spectrometer (PTR-ToF-MS) and sensory analysis. To explore the greatest possible variability determined by cultivars and growing environments, we analyzed 364 EVOO blend, 397 EVOO from 64 different cultivars and 31 aged (3-5 years) samples. Surprisingly, of the 761 samples labelled EVOO, 53% did not conform to the declared category. Through multivariate analysis of spectral data, organized according to the assessors' judgments, we build a PLS-DA model that distinguished EVOO from non-EVOO. The proposed pipeline method allowed a rapid and consistent control of the EVOO quality market.

The olive oil dilemma: To be or not to be EVOO? chemometric analysis to grade virgin olive oils using 792 fingerprints from PTR-ToF-MS / Taiti, C.; Marone, E.; Fiorino, P.; Mancuso, S.. - In: FOOD CONTROL. - ISSN 0956-7135. - STAMPA. - 135:(2022), pp. 108817.0-108817.10. [10.1016/j.foodcont.2022.108817]

The olive oil dilemma: To be or not to be EVOO? chemometric analysis to grade virgin olive oils using 792 fingerprints from PTR-ToF-MS

Fiorino, P.;
2022

Abstract

There is increasing interest in controlling EVOO quality on the market in order to maintain its high economic value and to protect the consumer from fraud. Here we developed a new pipeline to assess the quality of olive oil. Over five olive oil crop-years 792 oil samples were simultaneously evaluated by a Proton Transfer Reaction Time of Flight Mass Spectrometer (PTR-ToF-MS) and sensory analysis. To explore the greatest possible variability determined by cultivars and growing environments, we analyzed 364 EVOO blend, 397 EVOO from 64 different cultivars and 31 aged (3-5 years) samples. Surprisingly, of the 761 samples labelled EVOO, 53% did not conform to the declared category. Through multivariate analysis of spectral data, organized according to the assessors' judgments, we build a PLS-DA model that distinguished EVOO from non-EVOO. The proposed pipeline method allowed a rapid and consistent control of the EVOO quality market.
2022
135
0
10
Goal 3: Good health and well-being
Taiti, C.; Marone, E.; Fiorino, P.; Mancuso, S.
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Utilizza questo identificatore per citare o creare un link a questa risorsa: https://hdl.handle.net/2158/1361674
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