## 3 Results
### Partial Least Squares Regression (PLS-R) to Predict Leaf Physiology
\begin{table}
\begin{tabular}{c c c c c c c c c} \hline \hline \multirow{2}{*}{**Hyper**} & \multirow{2}{*}{**Crop**} & \multirow{2}{*}{\(\mathbf{R^{2}_{val}}\)} & \multirow{2}{*}{\(\mathbf{R^{2}_{val}}\)} & \multirow{2}{*}{\(\mathbf{NRMSE_{val}}\)} & \multirow{2}{*}{\(\mathbf{NRMSE_{val}}\)} & \multirow{2}{*}{\(\mathbf{bias_{val}}\)} & \multirow{2}{*}{\(\mathbf{bias_{val}}\)} \\  & & & & & & & & (\%) & (\%) \\ \hline \multirow{3}{*}{A (\(\mathrm{\mu mol~{}CO_{2}~{}m^{-2}~{}s^{-1}}\))} & Soybean & 0.79 & 0.67 & 12 & 15 & 2.9 & 3.4 & 8 \\  & Maize & 0.87 & 0.79 & 8 & 10 & 1.1 & 1.4 & 5 \\  & Soybean + Maize & 0.94 & 0.92 & 7 & 9 & 4.1 & 4.8 & 11 \\ \hline \multirow{3}{*}{\(\mathrm{gs~{}mol~{}H_{2}O~{}m^{-2}~{}s^{-1}}\)} & Soybean & 0.71 & 0.54 & 14 & 18 & 3.5 & 4.2 & 8 \\  & Maize & 0.65 & 0.58 & 13 & 15 & 1.3 & 1.5 & 2 \\  & Soybean + Maize & 0.82 & 0.77 & 11 & 13 & 3.6 & 3.9 & 10 \\ \hline \multirow{3}{*}{\(\mathrm{Tr~{}(\mathrm{\mu mol~{}CO_{2}~{}m^{-2}~{}s^{-1}})}\)} & Soybean & 0.82 & 0.68 & 12 & 15 & 2.6 & 3.9 & 9 \\  & Maize & 0.85 & 0.75 & 9 & 12 & 1.3 & 1.7 & 5 \\  & Soybean + Maize & 0.89 & 0.86 & 10 & 11 & 2.9 & 3.6 & 10 \\ \hline \multirow{3}{*}{\(\mathrm{\textbf{Hyper + T}_{L,Rad}}\)} & \multirow{3}{*}{**Crop**} & \multirow{3}{*}{\(\mathbf{R^{2}_{val}}\)} & \multirow{3}{*}{\(\mathbf{NRMSE_{val}}\)} & \multirow{3}{*}{\(\mathbf{NRMSE_{val}}\)} & \multirow{3}{*}{\(\mathbf{NRMSE_{val}}\)} & \multirow{3}{*}{\(\mathbf{bias_{val}}\)} & \multirow{3}{*}{\(\mathbf{bias_{val}}\)} \\  & & & & & & & & \\ \hline \multirow{3}{*}{A (\(\mathrm{\mu mol~{}CO_{2}~{}m^{-2}~{}s^{-1}}\))} & Soybean & 0.78 & 0.68 & 13 & 15 & 3.0 & 3.6 & 8 \\  & Maize & 0.87 & 0.79 & 8 & 11 & 1.1 & 1.5 & 5 \\  & Soybean + Maize & 0.94 & 0.92 & 7 & 8 & 4.1 & 4.9 & 11 \\ \hline \multirow{3}{*}{\(\mathrm{gs~{}mol~{}H_{2}O~{}m^{-2}~{}s^{-1}}\)} & Soybean & 0.81 & 0.68 & 12 & 15 & 3.1 & 3.8 & 8 \\  & Maize & 0.65 & 0.57 & 14 & 15 & 1.3 & 1.5 & 2 \\  & Soybean + Maize & 0.86 & 0.82 & 10 & 11 & 3.3 & 3.9 & 10 \\ \hline \multirow{3}{*}{\(\mathrm{Tr~{}(\mathrm{\mu mol~{}CO_{2}~{}m^{-2}~{}s^{-1}})}\)} & Soybean & 0.83 & 0.70 & 11 & 15 & 2.7 & 3.7 & 9 \\  & Maize & 0.83 & 0.74 & 10 & 12 & 1.4 & 1.9 & 5 \\  & Soybean + Maize & 0.90 & 0.86 & 9 & 11 & 3.0 & 3.4 & 10 \\ \hline \multirow{3}{*}{\(\mathrm{\textbf{Hyper + T}_{L,Rad}+h_{c}}\)} & \multirow{3}{*}{**Crop**} & \multirow{3}{*}{\(\mathbf{R^{2}_{val}}\)} & \multirow{3}{*}{\(\mathbf{R^{2}_{val}}\)} & \multirow{3}{*}{\(\mathbf{NRMSE_{val}}\)} & \multirow{3}{*}{\(\mathbf{NRMSE_{val}}\)} & \multirow{3}{*}{\(\mathbf{bias_{val}}\)} & \multirow{3}{*}{\(\mathbf{bias_{val}}\)} \\  & & & & & & & \\ \hline \multirow{3}{*}{A (\(\mathrm{\mu mol~{}CO_{2}~{}m^{-2}~{}s^{-1}}\))} & Soybean & 0.79 & 0.66 & 12 & 16 & 2.9 & 3.7 & 7 \\  & Maize & 0.86 & 0.79 & 8 & 11 & 1.1 & 1.5 & 5 \\  & Soybean + Maize & 0.94 & 0.92 & 7 & 8 & 4.1 & 4.7 & 11 \\ \hline \multirow{3}{*}{\(\mathrm{gs~{}mol~{}H_{2}O~{}m^{-2}~{}s^{-1}}\)} & Soybean & 0.79 & 0.65 & 12 & 16 & 3.3 & 3.7 & 8 \\  & Maize & 0.69 & 0.61 & 13 & 14 & 1.2 & 1.4 & 3 \\ \cline{1-1}  & Soybean + Maize & 0.86 & 0.82 & 10 & 11 & 3.4 & 3.9 & 10 \\ \hline \multirow{3}{*}{\(\mathrm{Tr~{}(\mathrm{\mu mol~{}CO_{2}~{}m^{-2}~{}s^{-1}})}\)} & Soybean & 0.83 & 0.71 & 11 & 15 & 2.6 & 3.8 & 8 \\ \cline{1-1}  & Maize & 0.91 & 0.81 & 7 & 10 & 0.8 & 1.2 & 7 \\ \cline{1-1}  & Soybean + Maize & 0.91 & 0.87 & 9 & 11 & 2.7 & 3.3 & 10 \\ \hline \hline \end{tabular}
\end{table} 
Table 5: Fit statistics for 500 bootstrapped PLS-R model for each crop and both crops (soybean + maize) together when applying PLS-R for hyperspectral data (Hyper) only, including leaf radiometric temperature (\(\mathrm{T_{L,Rad}}\)), and finally adding canopy height (\(\mathrm{h_{c}}\)). The coefficient of determination (\(\mathrm{R^{2}}\)), normalized root mean squared error (NRMSE) and bias are provided for PLS-R Calibration fitting (cal) during the PLS-R model development with 70% of the data and for PLS-R validation (val) with 30% of the data.