## 3 Results and Discussion
### Quantification Analysis
From these graphs, it is evident that DNT signals are observed on the background matrix signals in all cases, including 2% DNT in NAT-S.  
Figure 3: DNT spectrum in the investigated soil matrices in K-M (K-M for T: K-M calculate from transmittance for red spectra): (**a**) BC; (**b**) SYN-S; (**c**) NAT-S, and (**d**) NAT-S Low. Figures of Merit (FM)  
The accuracies of the models were determined from the values of the RMSEE, RMSECV, and RMSEP. The results for each model (labeled by matrix) are listed in Table 1. The precision was inferred through the values of the relative standard deviation (RSD). The RSD values for the prediction of the same sample in the same site were calculated for different concentrations and their average to measure the repeatability (RSDr). The RSD values for the prediction of the same sample in various locations on the sample surfaces were calculated for different concentrations and their average to measure the mixture homogeneities (RSDh). The RSD values for different samples at the same concentration were calculated for different concentrations and their average to measure the reproducibility (RSDrd). From these values, which are listed in Table 2, it can be concluded that the technique has excellent repeatability, while the samples have excellent homogeneity. However, only good reproducibility was determined for the models. Another FM used for measuring precision was the RPD. As previously mentioned, the RPD is the ratio of the variation in the validation samples and the size of probable errors occurring during predictions. The RPD values are also listed in Table 2.  
The best models were the ones with the lowest RMSEP values and the highest RPD values. The values obtained for the RPD were excellent. It has been suggested that models with RPD values greater than 5 can be considered suitable for quality control. On the other hand, models with RPD values greater than 6.5 can be used for process monitoring. Moreover, models with RPD values greater than 8 can be used in any application [66]. All the models tested in this study had RPD values higher than 8. This result indicates that the proposed technique can be used for the direct analysis of HE in soils. At the same time, the detection of explosives and their respective effects over different soil types have not been studied in detail so far. We plan to expand the present study to include reliable models over various types of soils as part of our future work. In the context of determining HEs, sensitivity refers to the ability of a method or instrument to detect an analyte at a specified concentration. In contrast, the sensitivity of an analytical approach as defined in this study, is the capability of the method to discriminate between small differences in concentrations or masses of a target analyte. The sensitivity of each method studied was calculated according to Equations (1) and (2), and the results of these calculations are presented in Table 3. The SEN value calculated for a model with VN preprocessing should be interpreted differently from the one without preprocessing or employing other preprocessing steps. Thus, the sensitivity values were derived from two types of models: models with VN as the preprocessing step and models without preprocessing steps. When using VN preprocessing, the spectra were normalized such that the sum of squares of intensity is equal to one. In other words, the spectra are converted to unit vectors. The SEN parameters were calculated from the magnitude of the vector calibration functions \(\mathbf{b}\), which, in turn, were derived from the spectra and their respective concentrations of standards. VN directly affects the magnitude \(\|\mathbf{b}\|\) and value of SEN as a consequence. However, a better parameter for sensitivity can be obtained by calculating \(\gamma\) because this parameter is only affected by instrumental noises. The noise level was measured by collecting 20 spectra of a blank (target) and calculating an average of the standard