Laser-Induced Breakdown Spectroscopy vs. Fluorescence Spectroscopy for Olive Oil Authentication

In the present work, laser-induced breakdown spectroscopy (LIBS) and fluorescence spectroscopy are used and assessed for the detection of EVOOs' adulteration with some non-EVOO edible oils (i.e., pomace, corn, sunflower, and soybean) and the discrimination of EVOOs based on geographical origin. For the direct comparison of the performance of the two techniques, the same set of EVOO samples was studied. The acquired spectroscopic data were analyzed by several machine learning algorithms, and the constructed predictive models are evaluated thoroughly for their reliability and robustness. In all cases, the high classification accuracies obtained support the potential and efficiency of both LIBS and fluorescence spectroscopy for the rapid, online, and in situ study of EVOOs' authentication issues, with LIBS being more advantageous as it operates much faster.

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Publication Details

Journal
Foods
Published
2025-03-19
DOI
https://doi.org/10.3390/foods14061045
Citations
3
Primary Topic
Laser-induced spectroscopy and plasma
Type
article
Field-Weighted Citation Impact
2.59
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article

Laser-Induced Breakdown Spectroscopy vs. Fluorescence Spectroscopy for Olive Oil Authentication

Eleni Nanou, Stelios Couris, Marios Bekogianni, Theodoros Stamatoukos
3 citations
Foods
Laser-induced spectroscopy and plasma
2.59
article

Laser-Induced Breakdown Spectroscopy vs. Fluorescence Spectroscopy for Olive Oil Authentication

Eleni Nanou, Stelios Couris, Marios Bekogianni, Theodoros Stamatoukos
article en
3 citations

Abstract

In the present work, laser-induced breakdown spectroscopy (LIBS) and fluorescence spectroscopy are used and assessed for the detection of EVOOs' adulteration with some non-EVOO edible oils (i.e., pomace, corn, sunflower, and soybean) and the discrimination of EVOOs based on geographical origin. For the direct comparison of the performance of the two techniques, the same set of EVOO samples was studied. The acquired spectroscopic data were analyzed by several machine learning algorithms, and the constructed predictive models are evaluated thoroughly for their reliability and robustness. In all cases, the high classification accuracies obtained support the potential and efficiency of both LIBS and fluorescence spectroscopy for the rapid, online, and in situ study of EVOOs' authentication issues, with LIBS being more advantageous as it operates much faster.

FoodsVol. 14(6)
University of Patras (GR), Foundation for Research and Technology Hellas (GR)
Peace, Justice and strong institutions
Openalex Percentile: Top 12%
Laser-induced spectroscopy and plasma
2.59
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