Laser-induced breakdown spectroscopy coupled with machine learning as a tool for olive oil authenticity and geographic discrimination

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.

Chemometric approach to characterization of the selected grape seed oils based on their fatty acids composition and FTIR spectroscopy

“…One of the first use of Fourier Transform Infrared Spectroscopy (FTIR) for analysis of grapes and wine started with near-infrared spectroscopy 13 , 14 . Due to higher accuracy and more constituents and properties which can be quantified, the analysis of grapes and wine is nowadays based mainly on FT-IR spectroscopy combined with advanced statistical methods (also known as chemometrics analysis) 15 and more frequently with the use of machine learning methods 11 , 16 . During the last decades the FTIR spectroscopy combined with the advanced statistics mentioned are increasingly used for extended studies on grapes and wines, and usually effects in excellent precision and accuracy of results obtained.…”

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)

“…In another work, Gyftokostas et al (2021) [ 58 ] performed classification of olive oil LIBS spectra based on their designation of origin and employed some machine learning algorithms to determine the importance of their spectral features. More specifically, 139 extra virgin and virgin olive oil samples were studied, originating from three different regions of Greece, i.e., Peloponnese, Crete, and Lesvos.…”

Human Angiotensin I-Converting Enzyme Produced by Different Cells: Classification of the SERS Spectra with Linear Discriminant Analysis

“…Classification methods are widely used for separation [ 46 ] and feature importance search [ 47 ] for further interpretation of these values. Specifically, LDA allows us to present data in an optimal low-dimensional space, where studied samples can be efficiently separated.…”