## 1 Introduction
Principal Component analysis (PCA) and PLS analysis classified 33 of the 88 samples labeled as EVOO according to national authorities since adulteration with oils of minor quality was detected. Mixing EVOO with hazelnut oil is a common type of fraud. These two types of oil have similar chemical compositions; as a result, detection of low percentages of the adulterant is quite difficult. Raman spectroscopy was used by [PERSON] et al. (2003) [16], who distinguished EVOO of similar cultivars and quantified the degree of adulteration with refined hazelnut oil, using PCA analysis and PLS analysis in order to simplify data and to quantify adulteration. Results showed that quantification of adulteration was achieved to a range between 0 and 20%. Likewise, [PERSON] et al. (2000) [17] determined adulteration of greek EVOOs with sunflower oil. Fourier transformed (FT-NIR) Raman spectroscopy was used, and PCA analysis confirmed the addition of sunflower oil at a level of 2% due to clear spectrum differences at the 1300-1250 cm\({}^{-1}\) region. Following the good classification rates regarding PCA analysis, the authors examined whether the PLS method also provides satisfactory results. A full spectrum analysis was first performed without choosing a specific wavenumbers area. By restricting the samples used in one geographic area, the root means square error of prediction (RMSEP) significantly improved (1.69% instead of 2.86% in the first case). Additional tests included a selection of a specific wavelength and comparison of the root means square error of calibration (RMSEC) and RMSEP values between samples from different geographic regions and samples from the same region. According to their results, the less the geographic variability of the selected samples, the better the predictive capacity of the model. In another study, Vis-Raman was used to classify vegetable oils and to detect adulteration of EVOO. Discrimination between EVOO and vegetable oils, as well as detection of adulterated EVOO with sunflower oil, were performed with the PCA analysis in combination with multidimensional scaling (MDS). Adulteration was detectable at levels lower than 5%. Afterward, PLS analysis was used to design the calibration model and to quantify the adulterant. Spectral regions according to which the PLS model was designed were 800-1800 and 3020-2850 cm\({}^{-1}\)[18]. In a similar study, adulteration of Greek EVOO with sunflower oil was investigated by [PERSON] et al. (2016) [19], using Raman and visible spectroscopy. Regarding Raman spectroscopy, PLS method and a three latent variable algorithm were used to distinguish between EVOO and the adulterant. Characteristic peaks at 1265 and 1657 cm\({}^{-1}\), which belong to monomsaturated and polyunsaturated fatty acids, respectively, are more intense in the case of sunflower oil. In addition to the above-mentioned characteristic peaks, absorption bands at 1082 and 1657 cm\({}^{-1}\) were used for sufficient differentiation. Model robustness was evaluated by cross- and external validation, using the R\({}^{2}\) and root mean square error of cross-validation (RMSECV) parameters in the first case, while for the second one, the RMSEP was examined. In addition, the authors used a Raman spectrometer with a visible laser to examine the presence of carotenoids presented at 1004, 1156 and 1527 cm\({}^{-1}\), which appear only at the samples of EVOO. Furthermore, adulteration of EVOO with 5% soybean oil using Raman spectroscopy combined with Linear Discriminant Analysis (LDA) was also evaluated by [PERSON] et al., 2017 [20]. PCA analysis was selected to diminish data variability, and LDA analysis followed. However, their experiment differed from other studies in which authors supported that since compounds of an EVOO are not structurally similar; the selection of an optimal temperature that enhances authentication accuracy is of critical importance. Their assumption was evaluated based on spectral differences acquired at different temperatures, using as markers linoleic and oleic acids.