Application of visible and near-infrared spectroscopy for identification of cadmium (Cd) and lead (Pb) pollution in soil using regression models and ANN

The aims of this study were to determine the distribution of cadmium and lead in topsoil in Bahar city of Hamadan and to evaluate pollution of these metals in agricultural lands which cultivated potato. Therefore, systematic sampling was used, soil samples were taken from depth 0-45 cm. Visible and near-infrared (VIS-NIR) spectroscopy was provided as a quick and accurate method in 370 -2000 nm range. The reflectance spectrum of 95 soil samples were collected to estimate the concentration of cadmium and lead. To reduce noise on soil spectra, MSC, SNV and derivative preprocessing methods were used. The results showed contamination usually occurs due to combinations of sewage irrigation, it accumulates in the topsoil. Prediction of heavy metals were estimated by partial least squares regression and artificial neural network (R2PLSR = 0/90, R2BPNN = 0/95).