## 2 Results
### Correlation between the Climatic and Geographical Parameters and THC and CBD Quantity Variation  
We considered all 13 parameters including statistics of latitude, longitude, elevation, P, Tmean, Tmin, Tmax, RHmean, RHmin, RHmax, SD, WS, DP (abbreviations are explained in detail in the Materials and Methods section \"climatic and geographical data\"), and THC and CBD concentration (%) obtained for the plants of each location to estimate the Pearson correlation coefficient among these variables. Our results showed that there was a negative correlation between THC and CBD concentration, but this was not significant (r = \(-\)0.053). Latitude had a negative significant correlation with both THC and CBD (r = \(-\)0.157, \(p\leq 0.05\); r = \(-\)0.239, \(p\leq 0.01\), respectively). In addition, elevation correlated negatively with THC and CBD, and this was significant (r = \(-\)0.408, \(p\leq 0.01\); r = \(-\)0.222, \(p\leq 0.01\), respectively).  
Moreover, we observed a significant negative correlation for wind and THC concentration (r = \(-\)0.326, \(p\leq 0.01\)). All three statistics related to temperature, including Tmean, Tmin, and Tmax, showed a positive correlation with THC (r = 0.352, \(p\leq 0.01\), r = 0.292, \(p\leq 0.01\), r = 0.412, \(p\leq 0.01\), respectively; Table 1), as well as CBD content (r = 0.314, \(p\leq 0.01\), r = 0.311, \(p\leq 0.01\), r = 0.287, \(p\leq 0.01\), respectively; Table 1). Additionally, all three relative humidity statistics comprising RHmean, RHmin, and RHmax correlated negatively with CBD content (r = \(-\)0.201, \(p\leq 0.05\), r = \(-\)0.171, \(p\leq 0.05\), r = \(-\)0.188, \(p\leq 0.05\), respectively), and RHmin correlated negatively with THC content (r = \(-\)0.206, \(p\leq 0.01\)). In addition, to assess the correlation of each parameter, we performed PCA on THC and CBD content of all studied individuals and climatic and geographical variables of sampled regions (Figure 4). The PCA plot revealed a negative correlation for elevation and confirmed the positive correlations of the three temperature statistics including Tmean, Tmin, and Tmax with THC and CBD content (Figure 4).  
Figure 4: _Cont._Figure 4: Principal component biplot consist of PCA scores of individuals (dots-first graphic) and loadings of variables (vectors-second graphic) of THC and CBD contents of 20 Iranian cannabis populations and geographical/climatic variables of regions of origin. PC1 and PC2 explain most of the variance in the original variables. Average annual temperature and latitude strongly influences PC1, while elevation and sunlight duration have more say in PC2. The loading plot shows THC and CBD contents positively correlate with mean, min, and max annual temperature and negatively correlate with elevation, latitude, and humidity statistics.  
\begin{table}
\begin{tabular}{c c c c c c c c c c c c c c c c c c} \hline \hline  & \multicolumn{11}{c}{**Variables**} \\ \hline  & **THC** & **CBD** & \begin{tabular}{c} **Longitude** \\ **(B)** \\ \end{tabular} & \begin{tabular}{c} **Latitude** \\ **(B)** \\ \end{tabular} & \begin{tabular}{c} **Elevation** \\ **(N)** \\ \end{tabular} & \begin{tabular}{c} **V5 1** \\ **(m)** \\ \end{tabular} & \begin{tabular}{c} **Timean 2** \\ \end{tabular} & \begin{tabular}{c} **Train 3** \\ \end{tabular} & \begin{tabular}{c} **Tmax 4** \\ \end{tabular} & \begin{tabular}{c} **RHmean 5** \\ \end{tabular} & \begin{tabular}{c} **RHmin 6** \\ \end{tabular} & \begin{tabular}{c} **RHmax 7** \\ \end{tabular} & \begin{tabular}{c} **SD 8** \\ \end{tabular} & \
\begin{tabular}{c} **P 9** \\ \end{tabular} &
\begin{tabular}{c} **DP 10** \\ \end{tabular} \\ \hline
**THC** & \(1\) & \(\begin{array