## 3 Results and Discussion
### Full-Waveband Data Analysis and Modeling  
In this experiment, soil samples were divided into the calibration set and the prediction set according to the ratio of 2:1 using the (sample set partitioning based on joint x-y distance) SPXY method [39]. The raw spectra and the other five pretreated spectra were modeled and analyzed by PLS. Table 1 and Figure 3a present the prediction results under different drying temperatures using different preprocessing methods.  
First, when soil samples were detected after 40 \({}^{\circ}\)C, 60 \({}^{\circ}\)C, and 80 \({}^{\circ}\)C drying, the soil nitrogen detection accuracy (0.879 \(<R_{p}^{2}<\) 0.960, 0.221 g/kg \(<RMSE_{p}<\) 0.148 g/kg, 2.92 \(<RPD<\) 4.88) are better than that of 25 \({}^{\circ}\)C placement and 105 \({}^{\circ}\)C drying. However, soil nitrogen detection was the worst (0.373 \(<R_{p}^{2}<\) 0.585, 0.483 g/kg \(<RMSE_{p}<\) 0.573 g/kg \(1.24<RPD<\) 1.46) when soils were placed at 25 \({}^{\circ}\)C. Meanwhile, the detection effects (0.672 \(<R_{p}^{2}<\) 0.915, 0.276 g/kg \(<RMSE_{p}<\) 0.231 g/kg,  
Figure 3: (**a**) The determination coefficients of the partial least squares (PLS) method after different spectral pretreatments; (**b**) the prediction results of the RAW-PLS model at different temperatures.  
Figure 2: The average spectral of different drying temperatures when the soil nitrogen concentration is 2.5 g/kg.  
\(1.49<RPD<3.42\)) are not stable when the drying temperature is 105 \({}^{\circ}\)C. The reason might be that medium and high temperature could largely remove the soil water, but an extremely high drying temperature would destroy the soil urease activity as well [38]. Meanwhile, little soil water content was preserved (water content: 3.6%) when soils were placed at 25 \({}^{\circ}\)C for a long time. Compared with the O-H bonds in water, the N-H bonds exist mostly in the form of multiple frequency or combination frequency. Thus, the N-H bonds are relatively weak for extracting soil nitrogen information in soil [40].  
Second, from the aspects of the preprocessing methods with PLS, the ranking of prediction effects is RAW > S-G > DT > 1 st-Der > SNV > MSC. In general, the spectra with suitable pretreatments could improve the accuracy of modeling and prediction to a certain extent. However, since the NIR spectra have no obvious characteristic peaks or fingerprint peaks, the pretreated methods might remove some useful information of the raw spectra, which causes the problem of spectral signal distortion. Among them, the spectral preprocessing methods of MSC and SNV might have the problem of spectral over-correction. Besides this, 1 st-Der is very sensitive to a high-frequency signal but meanwhile it may ignore some useful spectral information [26; 27].  
Figure 2(b) displays the PLS prediction results of raw spectra dealing with different temperatures. The \(X\)-axis is the soil nitrogen content and the \(Y\)-axis is the predicted soil nitrogen content. It is  
\begin{table}
\begin{tabular}{c c c c c c c c} \hline \hline \multirow{2}{*}{**Methods**} & \multirow{2}{*}{**Group**} & \multicolumn{3}{c}{**Calibration Set**} & \multicolumn{3}{c}{**Prediction Set**} & \multirow{2}{*}{**N**} \\ \cline{3-3} \cline{5-8}  & & \(\mathbf{R_{e}^{2}}\) & & \(\mathbf{RMSECV\) (g/kg)} & \(\mathbf{R_{p}^{2}}\) & & \(\mathbf{RMSEP\) (g/kg)} & \(\mathbf{RPD}\) \\ \hline \multirow{5}{*}{RAW} & 25 \({}^{\circ}\)C & 0.639 & 0.315 & 0.585 & 0.483 & 1.46 & 6 \\  & 40 \({}^{\circ}\)C & 0.959 & 0.102 & 0.960 & 0.148 & 4.88 & 6 \\  & 60 \({}^{\circ}\)C & 0.956 & 0.112 & 0.916 & 0.197 & 3.29 & 7 \\  & 80 \({}^{\circ}\)C & 0.955 & 0.10 suggested that the fitting effects are better when the soil is detected after 40 \({}^{\circ}\)C, 60 \({}^{\circ}\)C, and 80 \({}^{\circ}\)C drying than that of a 25 \({}^{\circ}\)C placement and 105 \({}^{\circ}\)C drying. Additionally, the fitting effect is the worst with the soil at a 25 \({}^{\circ}\)C placement, which is consistent with the predicted \(R^{2}\) value.