Classification of Greek Olive Oils from Different Regions by Machine Learning-Aided Laser-Induced Breakdown Spectroscopy and Absorption Spectroscopy

Abstract

In the present work, the emission and the absorption spectra of numerous Greek olive oil samples and mixtures of them, obtained by two spectroscopic techniques, namely Laser-Induced Breakdown Spectroscopy (LIBS) and Absorption Spectroscopy, and aided by machine learning algorithms, were employed for the discrimination/classification of olive oils regarding their geographical origin. Both emission and absorption spectra were initially preprocessed by means of Principal Component Analysis (PCA) and were subsequently used for the construction of predictive models, employing Linear Discriminant Analysis (LDA) and Support Vector Machines (SVM). All data analysis methodologies were validated by both “k-fold” cross-validation and external validation methods. In all cases, very high classification accuracies were found, up to 100%. The present results demonstrate the advantages of machine learning implementation for improving the capabilities of these spectroscopic techniques as tools for efficient olive oil quality monitoring and control.

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 very recent study by Gyftokostas et al (2021) [ 59 ], the classification of olive oil samples based on their geographical origin was studied employing two spectroscopic techniques, namely LIBS and absorption spectroscopy. The former technique provided the emission spectrum revealing the elemental composition of the olive oil samples, while the latter one provides spectroscopic information related to the chlorophylls and carotenoids content of the olive oil sample, corresponding to the absorption bands appearing within the 350–750 nm spectral region.…”

“…So, in the work by Stefas et al [ 60 ], as a natural continuation of the work of ref. [ 59 ], data fusion of LIBS and absorption spectroscopic data was performed for the discrimination of olive oils based on the olive cultivar origin. In that view, LIBS and absorption spectra were collected from two different olive oil cultivars that are quite wide spreading and popular in Greece, namely the Koroneiki and Kolovi cultivars.…”

Rapid classification of heavy metal soils from different mining areas by using a GSCV quadratic merit seeking network combined with MF-LIBS

“…Laser induced breakdown spectroscopy (LIBS) 9,10 is a plasma atomic emission spectroscopy technique based on high power pulses, which utilizes an intense pulsed laser focused on the surface of a target sample to generate a plasma, enabling quantitative and qualitative analyses of the sample's composition. As a common means of chemical analysis, LIBS not only has the advantages of rapid, multi-element detection, it also allows non-contact detection, which opens up new possibilities for high-precision and rapid detection, and has been widely used in many elds, such as food safety, 11,12 substance detection, 13 geological exploration, 14 and Mars exploration. 15 LIBS technology has developed rapidly and in a wide range of areas in the last few years, but there are still shortcomings present.…”

Modelling Polyphenol Extraction through Ultrasound-Assisted Extraction by Machine Learning in Olea europaea Leaves

“…The operation is based on building a hyperplane to separate the data into different classes [35], while minimizing the classification error, through geometric margin maximization between classes [33]. SVM can be applied in different research areas, such as in chemistry to predict the toxicity of different compounds [37,38], in hydrology to determine water quality for drinking purposes [39], and in food technology to study plasticizers in extra virgin olive oil [40] or to classify Greek olive oils [41], among others.…”