## 3 Results and Discussion
### Chemometric Analysis  
Principal component analysis (PCA) was carried out for the confirmation and strengthening of the classification of the examined monovarietal olive oils according to the cultivar. In order to restrict initial variables to a small number of new variables (known as principal components), the principal component analysis (PCA) is used to describe most of the original variations. The main goal of the key factor analysis is to identify the associated variables. The PCA score plot of Koroneiki versus Lianolia Kerkyras olive oils, according to their fatty acid and sterolic data set, is shown in Figure 2a,b respectively. In more detail, as shown in Figure 2a, the majority of K-points (corresponding to cv. Koroneiki) point to the left part of PC1, indicating that K has significant negative loads on component 2. Moreover, it can be observed that L-points (corresponding to cv. Lianolia Kerkyras) are shown on the right part of PC1, meaning that L has significant positive loads on component 1. Therefore, both K and L regions are independent and the data collection on fatty acids is not similar, impacting the two main regions. In accordance, the PCA score plot of Koroneiki vs. Lianolia Kerkyras olive oils' sterolic profile resulted in the creation of two separate clusters as shown in Figure 2b. In that case, we noted that L points are grouped very close to each other, depicting that the variability among Lianolia Kerkyras olive oils is very small compared to that of Koroneiki samples. A low variability for L points reveals that the samples appear to be very similar to the mean for the Lianolia Kerkyras, and therefore are not affected by any external factors.  
Figure 2: Score plot of principal component analysis (PCA) analysis based (**a**) on fatty acid (**b**) on the sterolic profiles of the examined monovarietal olive oils. K corresponds to Koroneiki olive oils (red spots) and L to Lianolia Kerkyras olive oils (blue spots).  
In general, a discrete separation between the two cultivars was detected by applying the PCA algorithm to the data set of fatty acids and sterols. The obtained results are in accordance with other relevant studies concentrating on olive oil major and minor compounds as effective tools for studying olive oil authentication. For example, fatty acid and triglyceride composition data have shown significant potential for olive oil classification according to cultivar [29; 30; 31; 32]. Likewise, clear differences have been observed in the content of the fatty acid as well as phenolic content of Tunisian olive varieties [33]. In addition, according to [PERSON] et al., botanical discrimination of olive oils can be achieved by examining the variables of stearic acid, campesterol, total sterols, and oxidative stability [42]. Another research group has recently used both sterol and phenolic fingerprints to discriminate Tunisian and Italian EVOOs, outlining their potential for authenticity evaluations [43].  
Finally, a combined PCA was performed using the variables of the fatty acid compositional and sterolic data (a total of 28 variables in 104 observations). As shown in the score plot of Figure 3, a complete separation according to the cultivar was achieved. Hence, it can be concluded that the discrimination of cv. Koroneiki and Lianolia Kerkyras samples in terms of cultivar could occur based on both fatty acid and sterolic profile data.