# Simultaneous Analysis of Heavy Metal Concentration in Soil Samples
## 3 Results
### Qualitative Description of FT-IR Spectra
Calibration models describing the relationship between metal concentration and DRIFT spectra in the near IR are shown in Figure 7. In comparison to the previous results presented here and those obtained using FIR and MIR regions, in the case of the NIR region, a noticeable improvement in calibration and the %RMS values is observed in the cases of chromium, tin, zinc, barium, lead, selenium, as well as in mercury and nickel. However, analysis of the %RMSCV values indicates that the prediction possibilities for the NIR DRIFT calibration models were smaller. The error values %RMSCV were within the range 10.84-20.61%. The lowest values of %RMS and %RMSCV for the DRIFT NIR calibration models were achieved for mercury, nickel, and lead. In Table 4, errors achieved for each range were compared. Generally, all the investigated spectral techniques and infrared radiation ranges have similar applicability for analysis of the metal concentration in soil. However, results indicated that there were differences between models depending on IR ranges and metals. The best results and errors below 10% were achieved for following metals: chromium, zinc, barium, mercury, nickel, and lead. The highest linearity and lowest RMS values were achieved for the NIR range. Models created using spectra measured in the far-IR region allowed us to get better linearity and lower RMS and RMSCV values there than for the MIR region. The model based on FIR spectra were characterized by better prediction abilities than NIR only in case of cobalt (%RMS 13.78, %RMSCV 15.82). For the other metals, application of FIR region did not improve possibilities of the models in \begin{table}
\begin{tabular}{c c c c c c c} \hline \hline
**Metal/Error** & \multicolumn{3}{c}{**RMS \%**} & \multicolumn{3}{c}{**RMSCV \%**} \\ \hline
**Range** & **FIR** & **MIR** & **NIR** & **FIR** & **MIR** & **NIR** \\ \hline Co & 13.78 & 14.46 & 17.01 & 15.82 & 17.11 & 18.27 \\ Cr & 11.68 & 12.11 & 4.50 & 14.39 & 15.09 & 14.42 \\ Mo & 15.03 & 16.44 & 15.18 & 17.02 & 17.01 & 16.83 \\ Sn & 16.72 & 17.89 & 8.96 & 19.37 & 20.34 & 20.61 \\ Zn & 12.00 & 14.09 & 6.35 & 15.99 & 16.66 & 14.70 \\ Ba & 13.98 & 15.75 & 6.48 & 16.76 & 18.44 & 17.35 \\ Hg & 7.44 & 9.93 & 5.71 & 10.77 & 14.17 & 11.36 \\ As & 10.80 & 11.66 & 12.23 & 11.93 & 12.24 & 12.40 \\ Cd & 13.65 & 15.40 & 10.22 & 17.20 & 20.43 & 18.42 \\ Cu & 19.54 & 21.05 & 19.96 & 21.33 & 22.42 & 20.35 \\ Ni & 9.52 & 9.30 & 6.79 & 10.88 & 12.43 & 10.84 \\ Pb & 11.97 & 12.90 & 3.41 & 13.06 & 13.34 & 12.34 \\ Se & 12.97 & 15.26 & 9.96 & 15.41 & 17.73 & 17.10 \\ \hline \hline \end{tabular}
\end{table} 
Table 4: Comparison of RMS and RMSCV values for PLS models based on each infrared range. (highest values of errors were marked with dark colors). comparison to the NIR region. The %RMS values below 10% were achieved only for mercury (7.44%) and nickel (9.52%). The values of %RMSCV for models based on FIR and NIR spectra were similar. The satisfying model was not achieved for some metals like molybdenum and arsenic. Low concentrations of tin were impossible to predict, and a higher concentration of tin fair linearity and low RMS could only be observed in the NIR region. The outcome was similar for selenium - the linearity of the model was poor, especially for low concentrations. The model created for the copper was also not good - in the region of FIR and NIR for concentrations exceeding 1000 mg/kg predicted content was underestimated. For lower concentrations, NIR and FIR linearity was poor and there was a large spread of results. A similar observation was described for some heavy metals by [PERSON] et al. [9] and [PERSON] et al. [10]. They concluded that such underestimated results of high concentrations were due to the fact that heavy metals in industrial samples are partially present in the inorganic form. Comparison of the obtained results to the literature is difficult because of the broader scope of this paper (13 metals) and the much higher metal concentrations used. For example, [PERSON] et al.