ArticleScientific reports2021
Laser-induced breakdown spectroscopy coupled with machine learning as a tool for olive oil authenticity and geographic discrimination.
Article in Scientific reports, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 11 papers.
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Who cites it
11 citing papers in PubMed, 36 citations in OpenAlex.
- Hydrogen isotopes retention studies using laser and microwave induced plasma coupling.Scientific reports · 2025Article
- Laser-Induced Breakdown Spectroscopy vs. Fluorescence Spectroscopy for Olive Oil Authentication.Foods (Basel, Switzerland) · 2025Article
- Adulteration Detection and Quantification in Olive Oil Using Excitation-Emission Matrix Fluorescence Spectroscopy and Chemometrics.Journal of fluorescence · 2025Article
- Rapid Authentication and Detection of Olive Oil Adulteration Using Laser-Induced Breakdown Spectroscopy.Molecules (Basel, Switzerland) · 2023Article
- Post-heating Fluorescence-based Alteration and Adulteration Detection of Extra Virgin Olive Oil.Journal of fluorescence · 2023Article
- Non-targeted detection of food adulteration using an ensemble machine-learning model.Scientific reports · 2022Article
- Human Angiotensin I-Converting Enzyme Produced by Different Cells: Classification of the SERS Spectra with Linear Discriminant Analysis.Biomedicines · 2022Article
- Integration of Innovative Technologies in the Agri-Food Sector: The Fundamentals and Practical Case of DNA-Based Traceability of Olives from Fruit to Oil.Plants (Basel, Switzerland) · 2022Review
- Qualitative Analysis of Glass Microfragments Using the Combination of Laser-Induced Breakdown Spectroscopy and Refractive Index Data.Sensors (Basel, Switzerland) · 2022Article
- Chemometric approach to characterization of the selected grape seed oils based on their fatty acids composition and FTIR spectroscopy.Scientific reports · 2021Article
- Laser-Induced Breakdown Spectroscopy: An Efficient Tool for Food Science and Technology (from the Analysis of Martian Rocks to the Analysis of Olive Oil, Honey, Milk, and Other Natural Earth Products).Molecules (Basel, Switzerland) · 2021Review
Corrections and comments
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Authors and funding
5 authors at 1 institution in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Olive oil is a basic element of the Mediterranean diet and a key product for the economies of the Mediterranean countries. Thus, there is an added incentive in the olive oil business for fraud through practices like adulteration and mislabeling. In the present work, Laser Induced Breakdown Spectroscopy (LIBS) assisted by machine learning is used for the classification of 139 virgin olive oils in terms of their geographical origin. The LIBS spectra of these olive oil samples were used to train different machine learning algorithms, namely LDA, ERTC, RFC, XGBoost, and to assess their classification performance. In addition, the variable importance of the spectral features was calculated, for the identification of the most important ones for the classification performance and to reduce their number for the algorithmic training. The algorithmic training was evaluated and tested by means of classification reports, confusion matrices and by external validation procedure as well. The present results demonstrate that machine learning aided LIBS can be a powerful and efficient tool for the rapid authentication of the geographic origin of virgin olive oil.
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Registered trials
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