Abstract

The potential of the combination of near infrared (NIR) spectroscopy and Raman spectroscopy to differentiate Italian and Greek extra virgin olive oil (EVOO) by geographical origin was evaluated. Near infrared spectroscopy and Raman fingerprints of both study groups (extra virgin olive oil from the two countries) were pre-processed, merged by low-level and mid-level data fusion strategies and submitted to partial least-squares discriminant analysis. The classification models were cross-validated. After low-level data fusion, the partial least-squares discriminant analysis correctly predicted the geographical origins of extra virgin olive oils in cross-validation with 93.9% accuracy, while sensitivity and specificity were 77.8% and 100%, respectively. After mid-level data fusion, the partial least-squares discriminant analysis correctly predicted the geographical origins of extra virgin olive oils in cross-validation with 97.0% accuracy, while sensitivity and specificity were 88.9% and 100%, respectively. In this preliminary study, improved discrimination of Italian extra virgin olive oils was achieved by the synergism of near infrared spectroscopy and Raman spectroscopy as compared to the discrimination obtained by the separate laboratory techniques. This pilot study shows encouraging results that could open a new avenue for the authentication of Italian extra virgin olive oil.

© 2021 The Author(s)

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