## 3 Results and Discussion
### PLSR by Preprocessing Using the Standard Normal Variate  
Table 3 shows the results of PLSR analysis with SNVs applied to the dry and wet soil samples within the VIS and NIR spectral regions. To develop the regression model for wet soil, analysis was performed with two factor counts: the same number of factors fitted with SG smoothing and the same number of factors in the dry soil regression model. The results of PLSR analysis using preprocessing SNVs for dry clay showed RPD values for pH, EC, SOM, TN, TOC, and clay of 1.40-1.96, 1.31-1.70, 1.16-1.31, 1.20-1.44, 1.16-1.32, and 1.72-2.21, respectively, and all the properties were evaluated as the best in the VIS spectral region. In addition, clay met the evaluation criteria of a good model, while the pH, EC, and TN met the evaluation criteria of a fair model. The PLSR analysis of wet soil showed the following RPD values for pH, EC, SOM, TN, TOC, and clay of 1.11-1.17, 1.02-1.13, 1.03-1.05, 1.11-1.14, 1.00-1.10, and 1.19, respectively. The results of RPD for pH, EC, SOM, TN, TOC, and clay were 1.13-1.19, 1.10-1.13, 1.04-1.08, 1.13-1.14, 1.01-1.10, and 1.21-1.24, respectively, when the model was set to the appropriate number of factors. The regression model analysis of wet soils showed the highest statistical values in the NIR region for all the soil properties except EC and TN, but both the regression  
\begin{table}
\begin{tabular}{c c c c c c c c} \hline \hline \multicolumn{2}{c}{**Soil Properties**} & \multicolumn{1}{c}{**Spectral Band 1**} & \multicolumn{1}{c}{**No.F 2**} & \multicolumn{1}{c}{**R2\({}^{\text{c}}\) 3**} & \multicolumn{1}{c}{**RMSEC 4**} & \multicolumn{1}{c}{**R2\({}^{\text{p}}\) 5**} & \multicolumn{1}{c}{**RMSEP 6**} & \multicolumn{1}{c}{**RPD**} \\ \hline \multirow{6}{*}{Dried Soil} & \multirow{2}{*}{pH} & VIS & 7 & 0.81 & 0.16 & 0.74 & 0.19 & 1.96 \\  & & NIR & 4 & 0.60 & 0.21 & 0.49 & 0.26 & 1.40 \\ \cline{2-8}  & EC & VIS & 7 & 0.76 & 0.38 & 0.66 & 0.46 & 1.70 \\  & [dS/m] & NIR & 6 & 0.67 & 0.45 & 0.41 & 0.60 & 1.31 \\ \cline{2-8}  & SOM & VIS & 5 & 0.53 & 3.64 & 0.42 & 4.09 & 1.31 \\  & [g/kg] & NIR & 7 & 0.63 & 3.23 & 0.29 & 4.61 & 1.16 \\ \cline{2-8}  & TN & VIS & 6 & 0.69 & 0.01 & 0.55 & 0.02 & 1.44 \\  & [g/kg] & NIR & 3 & 0.41 & 0.02 & 0.32 & 0.02 & 1.20 \\ \cline{2-8}  & TOC & VIS & 5 & 0.53 & 0.21 & 0.44 & 0.24 & 1.32 \\  & [\%] & NIR & 3 & 0.31 & 0.26 & 0.26 & 0.27 & 1.16 \\ \cline{2-8}  & Clay & VIS & 6 & 0.84 & 0.01 & 0.80 & 0.01 & 2.21 \\  & [\%] & NIR & 5 & 0.79 & 0.01 & 0.66 & 0.02 & 1.72 \\ \hline \multirow{6}{*}{Wet Soil} & \multirow{2}{*}{pH} & VIS & 7 (5) 7 & 0.38 (0.32) & 0.29 (0.30) & 0.22 (0.24) & 0.33 (0.33) & 1.11 (1.13) \\  & NIR & 4 (3) & 0.46 (0.44) & 0.27 (0.27) & 0.29 (0.31) & 0.31 (0.31) & 1.17 (1.19) \\ \cline{2-8}  & EC & VIS & 7 (6) & 0.35 (0.35) & 0.63 (0.63) & 0.23 (0.23) & 0.69 (0.69) & 1.13 (1.13) \\  & [dS/m] & NIR & 6 (2) & 0.51 (0.24) & 0.55 (0.68) & 0.06 (0.19) & 0.77 (0.71) & 1.02 (1.10) \\ \cline{2-8}  & SOM & VIS & 5 (3) & 0.16 (0.15) & 4.88 (4.93) & 0.09 (0.09) & 5.18 (5.15) & 1.03 (1.04) \\  & [g/kg] & NIR & 7 (2) & 0.37 (0.21) & 4.24 (4.75) & 0.14 (0.17) & 5.08 (4.97) & 1.05 (1.08) \\ \cline{2-8}  & TN & VIS & 6 (6) & 0.30 & 0.02 & 0.23 & 0.02 & 1.14 \\  & [g/kg] & NIR & 3 (2) & 0.39 (0.27) & 0.02 (0.02) & 0.21 (0.23) & 0.02 (0.02) & 1.11 (1.13) \\ \cline{2-8}  & TOC & VIS & 5 (2) & 0.15 (0.09) & 0.29 (0.29) & 0.03 (0.04) & 0.31 (0.31) & 1.00 (1.01) \\  & [\%] & NIR & 3 (3) & 0.34 & 0.25 & 0.18 & 0.28 & 1.10 \\ \cline{2-8}  & Clay & VIS & 6 (5) & 0.45 (0.40) & 0.02 (0.02) & 0.31(0.33) &model with the same number of factors as dry soils and the regression model with an appropriate number of factors were rated as poor models. The model with the right number of factors showed increasing R2 and RPD values for the soil properties, which were comparable to those of the model with the same number of factors as the dry soil model, with RPD values increasing by a minimum of 1% and a maximum of 8%.