## 3 Results
### Influence of Phenotypic Traits, Thermal, and Humidity Indices on Productivity and CWSI
\begin{table}
\begin{tabular}{c c c c c c c c c c} \hline \hline
**Variables Set** &
\begin{tabular}{c} **Response** \\ **Variable** \\ \end{tabular} & **Predictor Variables** & **B** & **SE B** & \(\beta\) & \(t\) & \(p\)**-Value** & \(\mathbf{R^{2}}_{\text{adj.}}\) & \(\mathbf{F}\) \\ \hline \multirow{3}{*}{Phenotypic traits} & \multirow{3}{*}{P} & (constant) & \(59.79\) & \(3.88\) & \(15.38\) & \(0.001\) & & \\  & & CR & \(-434.06\) & \(102.9\) & \(-0.47\) & \(-4.21\) & \(0.001\) & \(0.545\) & \(26.799\) \\  & & CWSI & \(-86.067\) & \(22.14\) & \(-0.43\) & \(-3.88\) & \(0.001\) & & \\ \hline \multirow{3}{*}{Thermal and humidity indices} & \multirow{3}{*}{P} & (constant) & \(54.28\) & \(2.86\) & \(18.96\) & \(0.001\) & & \\  & & T\({}_{\text{IQR}}\) canopy & \(-7.13\) & \(3.45\) & \(-0.29\) & \(-2.06\) & \(0.046\) & \(0.570\) & \(19.983\) \\  & & T\({}_{\text{IQR}}\) difference & \(-14.00\) & \(5.52\) & \(-0.34\) & \(-2.53\) & \(0.015\) & \(0.570\) & \(19.983\) \\  & & H\({}_{\text{IQR}}\) difference & \(-4.27\) & \(1.30\) & \(-0.35\) & \(-3.28\) & \(0.002\) & & \\ \hline \multirow{3}{*}{Combined model} & \multirow{3}{*}{P} & (constant) & \(54.39\) & \(5.29\) & \(10.27\) & \(0.001\) & & \\  & & HC & \(0.129\) & \(0.03\) & \(0.37\) & \(3.74\) & \(0.001\) & & \\ \cline{1-1}  & & CWSI & \(-49.01\) & \(20.12\) & \(-0.24\) & \(-2.43\) & \(0.020\) & \(0.711\) & \(27.384\) \\ \cline{1-1}  & & H\({}_{\text{IQR}}\) Side A & \(-3.04\) & \(1.02\) & \(-0.30\) & \(-2.98\) & \(0.005\) & & \\ \cline{1-1}  & & T\({}_{\text{IQR}}\) Side A & \(-8.19\) & \(3.12\) & \(-0.24\) & \(-2.62\) & \(0.012\) & & \\ \hline \hline \end{tabular}
\end{table} 
Table 2: Final models obtained from the multiple linear regression analyses for estimating productivity. All regression models were statistically significant (\(p<0.05\)). The slope of the predictor variable for the response variable (B), the standard error for the slope (SE B), the standardized beta (\(\beta\)), the \(t\)-test statistic (\(t\)), the probability value (\(p\)), the regression-adjusted coefficient for the regression model (\(\text{R}^{2}\)), and the predictive capability of the models (F). Figure 7: Effect plots of the impact of (**a**) cavity ratio (CR) and (**b**) crop water stress index (CWSI) on productivity. The \(x\)-axis represents varying CR and CWSI values, while the \(y\)-axis displays the corresponding predicted productivity values. As CR and CWSI increases there is a noticeable decrease in productivity, indicating a strong inverse relationship. Regarding CWSI, the linear model encompassing all variables exhibited statistical significance [F (3, 40) = 13.948, \(p\) < 0.05], with an adjusted R\({}^{2}\) of 47.5% (Table 3). The relative importance analysis highlighted P\({}_{\text{range}}\) with a Relative Importance of 62.78 as the most influential variable, trailed by H\({}_{\text{OPR}}\) difference (Relative Importance = 19.52) and T\({}_{\text{OPR}}\) difference (Relative Importance = 17.70). The impact of these variables is visually depicted in Figure 10, providing a clear illustration of their effects on CWSI. Figure 8: Effect plots of the impact of (**a**) canopy temperature interquartile range (T\({}_{\text{IQR}}\) canopy), (**b**) temperature interquartile range differences between side A and B (T\({}_{\text{IQR}}\) difference), and (**c**) humidity interquartile range differences between side A and B (H\({}_{\text{IQR}}\) difference), on productivity. The \(x\)-axis displays the values of these indices, while the \(y\)-axis indicates predicted productivity values. These indices exhibit a negative relationship with productivity, with higher values corresponding to lower productivity. Figure 9: Effect plots of the impact of (**a**) canopy health (HC), (**b**) crop water stress index (CWSI), (**c**) humidity interquartile range for side A (H\({}_{\text{IQR}}\) Side A), and (**d**) temperature interquartile range for side A (T\({}_{\text{IQR}}\) Side A) on productivity.