Shedding Light on the Ageing of Extra Virgin Olive Oil: Probing the Impact of Temperature with Fluorescence Spectroscopy and Machine Learning Techniques

TL;DR

This study demonstrates that fluorescence spectroscopy combined with machine learning can effectively monitor the oxidation and quality degradation of extra virgin olive oil under accelerated aging conditions, enabling simple, cost-effective field assessments.

Contribution

It introduces a novel method using fluorescence spectroscopy and machine learning to assess EVOO oxidation, suitable for non-laboratory, in-field applications.

Findings

Fluorescence spectroscopy can monitor EVOO oxidation effectively.

Machine learning models accurately predict oil quality from aggregated data.

Cost-effective, portable solutions for EVOO quality assessment are feasible.

Abstract

This work systematically investigates the oxidation of extra virgin olive oil (EVOO) under accelerated storage conditions with UV absorption and total fluorescence spectroscopy. With the large amount of data collected, it proposes a method to monitor the oil's quality based on machine learning applied to highly-aggregated data. EVOO is a high-quality vegetable oil that has earned worldwide reputation for its numerous health benefits and excellent taste. Despite its outstanding quality, EVOO degrades over time owing to oxidation, which can affect both its health qualities and flavour. Therefore, it is highly relevant to quantify the effects of oxidation on EVOO and develop methods to assess it that can be easily implemented under field conditions, rather than in specialized laboratories. The following study demonstrates that fluorescence spectroscopy has the capability to monitor the effect of oxidation and assess the quality of EVOO, even when the data are highly aggregated. It shows that complex laboratory equipment is not necessary to exploit fluorescence spectroscopy using the proposed method and that cost-effective solutions, which can be used in-field by non-scientists, could provide an easily-accessible assessment of the quality of EVOO.