# Classification of Potato Varieties Drought Stress Tolerance Using Supervised Learning
## 3 Results
### Machine Learning Models for Potato Variety Tolerance to Soil Drought Groups Classification  
Additionally, as it could be spotted in Figure 3, despite some promising correlation coefficients for several analyzed relations, a description of the studied phenomena using linear univariate models is not possible. To get statistically significant models, one has to propose a method that could include many measured parameters altogether. \begin{table}
\begin{tabular}{c c c c c c c} \hline \hline
**(a) Climatic Water Balance** & \(p\)**-Val.1** & **r** & **R2** & **Std. Err.** & **a** & **b** \\ \hline very dry & 0.063 & 0.21 & 0.05 & 0.000 & 0.001 & 0.521 \\ dry & 0.469 & 0.08 & 0.00 & 0.001 & 0.000 & 1.134 \\ optimal & 0.004 & 0.50 & 0.25 & 0.002 & 0.009 & \(-1.736\) \\ wet & 0.086 & 0.27 & 0.07 & 0.000 & 0.001 & 0.504 \\ \hline
**(b) Tolerance to Soil Drought** & \(p\)**-Val.** & **r** & **R2** & **Std. Err.** & **a** & **b** \\ \hline group I & 0.450 & 0.08 & 0.01 & 0.000 & 0.000 & 0.892 \\ group II & 0.029 & 0.24 & 0.06 & 0.001 & 0.002 & 0.272 \\ group III & 0.021 & 0.32 & 0.10 & 0.001 & 0.003 & 0.208 \\ \hline
**(c) Climatic Water Balance** & \(p\)**-Val.** & **r** & **R2** & **Std. Err.** & **a** & **b** \\ \hline very dry & 0.000 & 0.56 & 0.32 & 0.109 & 0.856 & 838.341 \\ dry & 0.000 & 0.62 & 0.39 & 0.262 & 1.686 & 568.129 \\ optimal & 0.000 & 0.51 & 0.26 & 0.145 & 0.984 & 772.845 \\ wet & 0.000 & 0.71 & 0.50 & 0.113 & 1.010 & 740.277 \\ \hline
**(d) Tolerance to Soil Drought** & \(p\)**-Val.** & **r** & **R2** & **Std. Err.** & **a** & **b** \\ \hline group I & 0.000 & 0.55 & 0.30 & 0.10 & 0.840 & 876.896 \\ group II & 0.000 & 0.62 & 0.39 & 0.13 & 1.207 & 722.849 \\ group III & 0.000 & 0.64 & 0.40 & 0.16 & 1.203 & 553.225 \\ \hline
**(e) Climatic Water Balance** & \(p\)**-Val.** & **r** & **R2** & **Std. Err.** & **a** & **b** \\ \hline very dry & 0.000 & 0.56 & 0.32 & 0.07 & 0.561 & 817.262 \\ dry & 0.000 & 0.60 & 0.36 & 0.17 & 1.004 & 498.879 \\ optimal & 0.000 & 0.44 & 0.20 & 0.09 & 0.527 & 752.745 \\ wet & 0.000 & 0.74 & 0.55 & 0.07 & 0.66 & 675.698 \\ \hline
**(f) Tolerance to Soil Drought** & \(p\)**-Val.** & **r** & **R2** & **Std. Err.** & **a** & **b** \\ \hline group I & 0.000 & 0.52 & 0.27 & 0.06 & 0.507 & 847.884 \\ group II & 0.000 & 0.58 & 0.34 & 0.08 & 0.686 & 692.679 \\ group III & 0.000 & 0.54 & 0.29 & 0.11 & 0.629 & 573.185 \\ \hline
**(g) Climatic Water Balance** & \(p\)**-Val.** & **r** & **R2** & **Std. Err.** & **a** & **b** \\ \hline very dry & 0.000 & 0.50 & 0.25 & 0.01 & 0.049 & 846.578 \\ dry & 0.000 & 0.63 & 0.39 & 0.02 & 0.104 & 558.749 \\ optimal & 0.000 & 0.50 & 0.25 & 0.01 & 0.049 & 816.544 \\ wet & 0.000 & 0.69 & 0.48 & 0.01 & 0.059 & 781.220 \\ \hline
**(h) Tolerance to Soil Drought** & \(p\)**-Val.** & **r** & **R2** & **Std. Err.** & **a** & **b** \\ \hline group I & 0.000 & 0.57 & 0.32 & 0.01 & 0.052 & 887.597 \\ group II & 0.000 & 0.64 & 0.41 & 0.01 & 0.067 & 727.828 \\ group III & 0.000 & 0.53 & 0.28 & 0.01 & 0.060 & 611.761 \\ \hline \hline \end{tabular}
\end{table} 
Table 4: Linear modeling results for relation between agronomic parameters against categories: climatic water balance or against tolerance to soil drought group, presented for parameters sets: (a) & (b) leaves mass and MSTI, (c) & (d) leaves mass and yield per plant, (e) & (f) stem and leaves mass and yield per plant, (g) & (h) assimilation area and yield per plant. At the beginning of the study, using only the part of the measurements, the potato varieties were assigned into one of three groups of tolerance to soil drought. The other part of the measurements (\(n=479\)) was used to verify that the implementation of an automatic method of classification of the potato variety using the proper configuration of the measured parameters is possible and, finally, could let one assess the cultivar tolerance to soil drought group for new, upcoming varieties.