## 3 Results and Discussion
### Optimisation of HS-SPME-GC-MS Conditions
Discrimination of plant samples from the same species but different geographical regions might help control the type and concentration of metabolites produced by plants. It also lets one determine the best antioxidant profile of volatile compounds of plant origin. Therefore, a numerical classification of the _Arctostaphylos uwa-ursi_ leaves samples was performed using principal component analysis. The classes corresponding to each type of sample were modelled. Figure 2 shows the results of the PCA analysis. The PCA (Figure 2a) shows that samples collected from Huetor (Granada) and Los Velez (Almeria) formed a cluster. After connecting of this data with information from Table 1 some interesting conclusions can be reached. The observed results can be related to geographical closeness and the similar altitude of the harvest areas. Even though samples were collected in two different months the insolation was similar, also influencing the obtained results. Another cluster is observed in case of samples from Chelva (Valencia) and El Toro (Castellon). Although these two harvest areas are not located closely to each other their insolation and altitude were the same. Moreover, it has been seen that there is no cluster in case of Pina de Montalgrao and El Toro, locations from the same province (Castellon). Even though they are geographically close and exposed to the same solar radiation in September, the different altitudes influenced the chemical composition of _Arctostaphylos uwa-ursi_ collected from these areas. Then samples from Loarre (Huesca) collected during two different months were not grouped into cluster. This is attributed to the fact the solar radiation that in November is half of that in September. \begin{table}
\begin{tabular}{l l} \hline \hline
**Number** & **Compound** \\ \hline
39 & Phenol \\ \hline
40 & 6,10,14-Trimethyl-2-pentadecanone \\ \hline
41 & 2-Propanone \\ \hline
42 & Fumaric acid 2-decyl dodecyl ester \\ \hline
43 & dihydromethyljasmonate \\ \hline
44 & 2,4-di-_tert_-Butylphenol \\ \hline
45 & 1,2-Benzenedicarboxilic acid \\ \hline
46 & 5,6,7,7a-Tetrahydro-4,4,7a-trimethyl-2(4\(H\))-benzofuranone \\ \hline
47 & Butyl octyl phthalate \\ \hline \hline \end{tabular}
\end{table} 
Table 2: _Cont._On the other hand, samples from Albarracin (Teruel) and Lierta (Huesca) didn't cluster with any other sample. Samples from Albarracin are close on the score plot to the Pina de Montalgrao (Castellon) one, however they didn't cluster together probably because there is a difference in the altitude of the harvest sites, while in case of samples from Lierta it may be due to the lowest altitude of all locations. Figure 2b of the loading plot shows how strongly each characteristic (each compound) influences a principal component. First, the distribution of variables indicates which are significantly different and important. Variables placed close to the loading graph centre play a minor role in the analyzed samples. Moreover, the correlation between each characteristic can be read, checking the variables angles. It can be done using vectors, starting at the origin of PCs (PC-1 = 0 and PC-2 = 0) and finishing at the points of variables. When the small angle is created between two vectors, and therefore variables are closed, they are positively correlated. In this case it is true for numbers 58, 99, 105 (group 1), 17, 53, 62, 102 (group 2) and 56, 97 (group 3) representing compounds as: group 1 (mequinol, 5-pentyl-1,3-benzenediol and benzoic acid); group 2 (2,4-di-_tert_-butylphenol, hexadecane, 2,3,6-trimethyldecane and 2,4-heptalenal); group 3 (4-(1-hydroxallyl)-2-methoxyphenol and 1-ethylcyclohexene). Then, when the two variables angle is 90\({}^{\circ}\), there is no correlation. An example can be numbers 21 and 98 representing 2-propanone and tridecane. Finally, when two variables diverge and form a large angle (close to 180\({}^{\circ}\)), they are negatively correlated. The example can be numbers 50 and 105 representing mequinol and 1,3-bis(1,1-dimethylethyl)-benzene.