## 4 Results
### Comparative Analysis of Soil Organic Matter Content Inversion Model Accuracy
The remaining models had RPD values ranging from 1.4 to 2.0, indicating a moderate level of reliability and the ability to provide rough estimations of the SOM content in the study area. \begin{table}
\begin{tabular}{c c c c c c c c} \hline \hline \multicolumn{2}{c}{**Spectral**} & \multirow{2}{*}{**Model**} & \multicolumn{3}{c}{**Training Set**} & \multicolumn{3}{c}{**Testing Set**} \\ \cline{3-8} \multicolumn{1}{c}{**Transformation Form**} & & \(\mathbf{R^{2}}\) & **RMSE** & **RPD** & \(\mathbf{R^{2}}\) & **RMSE** & **RPD** \\ \hline \multirow{8}{*}{N} & MLR & 0.62 & 2.16 & 1.63 & 0.51 & 3.12 & 1.43 \\  & PLSR & 0.60 & 2.27 & 1.59 & 0.60 & 2.62 & 1.58 \\  & SVR & 0.53 & 2.71 & 1.45 & 0.44 & 2.57 & 1.34 \\  & RF & 0.36 & 2.95 & 1.25 & 0.27 & 3.29 & 1.17 \\  & MPARF & 0.70 & 2.02 & 1.82 & 0.65 & 2.58 & 1.77 \\ \hline \multirow{8}{*}{FD} & MLR & 0.76 & 1.91 & 2.05 & 0.66 & 2.56 & 1.72 \\  & PLSR & 0.73 & 1.82 & 1.94 & 0.69 & 2.18 & 1.79 \\  & SVR & 0.77 & 1.65 & 2.08 & 0.63 & 2.72 & 1.64 \\  & RF & 0.85 & 1.51 & 2.61 & 0.59 & 2.26 & 1.56 \\  & MPARF & 0.88 & 1.47 & 2.80 & 0.86 & 1.55 & 2.40 \\ \hline \multirow{8}{*}{SD} & MLR & 0.85 & 1.40 & 2.59 & 0.61 & 2.52 & 1.60 \\  & PLSR & 0.70 & 2.08 & 2.98 & 0.65 & 2.32 & 1.70 \\  & SVR & 0.54 & 2.87 & 1.48 & 0.49 & 2.96 & 1.39 \\  & RF & 0.52 & 2.71 & 1.44 & 0.39 & 2.98 & 1.28 \\  & MPARF & 0.92 & 1.27 & 3.14 & 0.90 & 1.32 & 3.02 \\ \hline \multirow{8}{*}{RFD} & MLR & 0.70 & 2.02 & 1.83 & 0.63 & 2.49 & 1.65 \\  & PLSR & 0.75 & 2.00 & 1.98 & 0.67 & 2.20 & 1.73 \\  & SVR & 0.69 & 2.21 & 1.80 & 0.58 & 2.24 & 1.54 \\  & RF & 0.80 & 1.66 & 2.23 & 0.70 & 2.00 & 1.82 \\  & MPARF & 0.85 & 1.41 & 2.57 & 0.78 & 1.80 & 2.11 \\ \hline \multirow{8}{*}{RSD} & MLR & 0.63 & 2.19 & 1.65 & 0.54 & 2.54 & 1.47 \\  & PLSR & 0.77 & 1.84 & 2.09 & 0.75 & 1.83 & 2.00 \\  & SVR & 0.68 & 2.28 & 1.77 & 0.75 & 1.54 & 2.02 \\  & RF & 0.61 & 2.34 & 1.60 & 0.57 & 2.50 & 1.52 \\  & MPARF & 0.90 & 1.32 & 1.27 & 0.85 & 1.42 & 2.40 \\ \hline \multirow{8}{*}{LRFD} & MLR & 0.82 & 1.52 & 2.35 & 0.72 & 2.26 & 1.89 \\  & PLSR & 0.74 & 1.99 & 1.98 & 0.74 & 1.79 & 1.94 \\  & SVR & 0.76 & 1.91 & 2.05 & 0.63 & 2.16 & 1.65 \\  & RF & 0.71 & 1.75 & 1.86 & 0.53 & 2.97 & 1.47 \\  & MPARF & 0.84 & 1.46 & 2.57 & 0.77 & 1.75 & 2.03 \\ \hline \multirow{8}{*}{LRSD} & MLR & 0.74 & 1.97 & 1.94 & 0.64 & 2.09 & 1.67 \\  & PLSR & 0.77 & 1.74 & 2.08 & 0.73 & 1.98 & 1.94 \\  & SVR & 0.66 & 2.20 & 1.71 & 0.58 & 2.50 & 1.54 \\  & RF & 0.61 & 2.13 & 1.60 & 0.55 & 2.96 & 1.48 \\  & MPARF & 0.88 & 1.36 & 2.97 & 0.85 & 1.53 & 2.55 \\ \hline \multirow{8}{*}{RLFD} & MLR & 0.77 & 1.89 & 2.09 & 0.68 & 2.05 & 1.76 \\  & PLSR & 0.83 & 1.56 & 2.39 & 0.52 & 2.71 & 1.44 \\  & SVR & 0.81 & 1.59 & 2.32 & 0.66 & 2.41 & 1.71 \\  & RF & 0.74 & 1.84 & 1.95 & 0.75 & 2.10 & 2.00 \\  & MPARF & 0.89 & 1.41 & 2.88 & 0.81 & 1.54 & 2.31 \\ \hline \multirow{8}{*}{RLSD} & MLR & 0.71 & 2.06 & 1.87 & 0.67 & 2.07 & 1.74 \\  & PLSR & 0.81 & 1.58 & 2.31 & 0.76 & 1.87 & 2.04 \\ \cline{1-1}  & SVR & 0.75 & 1.69 & 2.01 & 0.69 & 2.48 & 1.78 \\ \cline{1-1}  & RF & 0.63 & 2.13 & 1.63 & 0.52 & 3.01 & 1.44 \\ \cline{1-1}  & MPARF & 0.91 & 1.31 & 3.11 & 0.87 & 1.35 & 2.94 \\ \hline \hline \end{tabular}
\end{table} 
Table 5: Comparison of accuracy of SOM content inversion models. Based on the above, different spectral transformation methods can improve the modeling accuracy to varying degrees. Spectral transformation alters the characteristics of the original spectral data, thereby influencing the performance of the models. Therefore, taking the MPARF model with better experimental results as an example, this study presents the model fitting accuracy plots for various spectral transformations, as shown in Figure 10. Overall, the predicted values for the training and testing sets are mostly distributed around the 1:1 line, indicating good prediction results. Among the individual spectral transformations, the SD transformation exhibits the best fit for the training set, with an R\({}^{2}\) value of 0.92.