## 3 Results and Discussion
### Identification of Diseased Samples with Different Degrees of Severity  
A total of 89 samples were collected at three angles in this experiment, of which 54 random samples were used as training samples to construct models and 35 samples were used as test samples for model validation. According to the correlation analysis and the independent sample T-test method, the spectral features sensitive to different disease severity were used as input variables. The FLDA, SVM, and LDA-SVM models were used to construct the identification model. The confusion matrix for classification based on the validation samples and the various accuracy evaluation indicators are shown in Table 9. \begin{table}
\begin{tabular}{c c c c c c c c c c c} \hline \hline \multirow{2}{*}{**Vegetation Index**} & \multicolumn{4}{c}{**Front**} & \multicolumn{4}{c}{**Side**} & \multicolumn{4}{c}{**Erect**} \\ \cline{2-11}  & **R** & **R\({}^{2}\)** & **\(p\)-Value** & **R** & **R\({}^{2}\)** & **\(p\)-Value** & **R** & **R\({}^{2}\)** & **\(p\)-Value** \\ \hline PSRI & 0.796 & 0.634 & 0.000 & 0.769 & 0.592 & 0.000 & 0.736 & 0.541 & 0.000 \\ SIPI & \(-\)0.722 & 0.522 & 0.000 & \(-\)0.794 & 0.631 & 0.000 & \(-\)0.703 & 0.494 & 0.000 \\ NPCI & 0.711 & 0.505 & 0.000 & 0.712 & 0.508 & 0.000 & 0.640 & 0.410 & 0.000 \\ RVSI & 0.657 & 0.432 & 0.000 & 0.614 & 0.377 & 0.000 & 0.478 & 0.229 & 0.033 \\ TCARI & \(-\)0.511 & 0.262 & 0.000 & \(-\)0.224 & 0.050 & 0.000 & 0.227 & 0.051 & 0.138 \\ CARI & \(-\)0.125 & 0.016 & 0.243 & 0.017 & 0.000 & 0.873 & \(-\)0.158 & 0.025 & 0.021 \\ GI & \(-\)0.775 & 0.601 & 0.000 & \(-\)0.694 & 0.482 & 0.000 & \(-\)0.243 & 0.059 & 0.000 \\ MSR & \(-\)0.718 & 0.515 & 0.000 & \(-\)0.786 & 0.617 & 0.000 & \(-\)0.706 & 0.498 & 0.000 \\ \hline \hline \end{tabular} Note: R is the correlation coefficient; R\({}^{2}\) is the determination coefficient.  
\end{table} 
Table 7: _Cont._  
\begin{table}
\begin{tabular}{c c c c c c c c c c c c c} \hline \hline \multirow{2}{*}{**Category**} & \multirow{2}{*}{**Variables**} & \multicolumn{4}{c}{Front} & \multicolumn{4}{c}{Side} & \multicolumn{4}{c}{**Erect**} \\ \cline{3-14}  & & **Order** & **H\&M** & **M\&S** & **H\&S** & **Order** & **H\&M** & **M\&S** & **H\&S** & **Order** \\ \hline \multirow{6}{*}{
\begin{tabular}{c} First order \\ derivative \\ (SDr \(-\) SDr)(SDr) \\ (SDr) \\  
\begin{table}
\begin{tabular}{c c c c c c c c c c c c c c c c c c c c c c} \hline \hline \multirow{2}{*}{**Models**} & \multicolumn{6}{c}{**Pront**} & \multicolumn{6}{c}{**Side**} & \multicolumn{6}{c}{**Pront**} \\ \cline{2-13}  & & **Heability** & **Midal** & **Score** & **Sum** & (V@V@) & **OA** (F@) & **Keppe** & **Heability** & **Midal** & **Score** & **Sum** & **U**\#V@) & **OA** (F@) & **Keppe** & **Heability** & **Midal** & **Score** & **Sum** & (V@) & **OA** (F@) & **Keppe** \\ \hline \multirow{4}{*}{FLDA} & Healthy & 12 & 1 & 13 & 70.6 & & & 8 & 2 & 1 & 11 & 100 & & & 8 & 3 & 1 & 50.0 & \\  & Mild & 5 & 10 & 1 & 16 & 83.3 & & & 17 & 1 & 18 & 85.0 & & & 9 & 1 & 18 & 69.2 & \\  & Severe & 1 & 5 & 6 & 83.3 & & 77.1 & 0.69 & & 1 & 5 & 6 & 71.4 & 85.7 & 0.782 & 1 & 5 & 6 & 83.3 & 62.9 & 0.416 \\  & Som & 17 & 12 & 6 & 35 & & & & 8 & 20 & 7 & 35 & & & 16 & 13 & 6 & 35 & \\  & F(U) & 92.3 & 62.5 & 83.3 & & & & 77.2 & 94.4 & 03.3 & & & & 72.7 & 50.0 & 83.3 & & & \\ \hline \multirow{4}{*}{SVM} & Healthy & 12 & 1 & 13 & 75.0 & & & 9 & 2 & 11 & 90.0 & & & 8 & 3 & 11 & 57.1 & \\  & Mild & 4 & 1 & 1 & 16 & 84.6 & & 1 & 14 & 3 & 18 & 87.5 & & & 6 & 12 & 18 & 66.7 & \\  & Som & 16 & 13 & 6 & 35 & & & & 10 & 16 & 9 & 35.5 & & & 14 & 18 & 3 & 35 & \\  & P(s) & 92.3 & 68.8 & 83.3 & & & & & 81.8 & 77.8 & 100 & & & & 72.7 & 66.7 & 50.0 & \\ \hline \multirow{4}{*}{LDA-SVM} & Healthy & 12 & 1 & 13 & 80.0 & & & 9 & 2 & 11 & 100 & & & 9 & 2 & 11 & 18 & 66.3 & \\  & Mild & 3 & 13 & 5 & 16 & 86.7 & & & 100 & 85.7 & 0.70 & & 1 & 88.3 & 88.6 & 0.888 & 7 & 10 & 1 & 18 & 26.5 & \\  & Severe & 15 & 15 & 5 & 5 & & & & 9 & 2 & 6 & 83.3 & 88.6 & 0.888 & 0.888 & 0.888 & 0.888 & 0.888 & 0.888 & 0.888 & 0.883 & 0.883 & 0.886 & 0.