Near-infrared spectroscopy for analysis of chemical and microbiological properties of forest soil organic horizons in a heavy-metal-polluted area

In industrial areas, heavy metals may accumulate in forest soil organic horizons, affecting soil microorganisms and causing changes in the chemical composition of the accumulated organic matter. The objectives of this study were to test the ability of near-infrared spectroscopy (NIRS) to detect heavy metal effects on the chemical composition of forest soil O horizons and to test whether NIRS may be used to quantitatively determine total and exchangeable concentrations of Zn and Pb (Zn_t, Pb_t, Zn_ex, Pb_ex) and other chemical and microbial properties in forest soil O horizons polluted with heavy metals. The samples of O horizons (n = 79) were analyzed for organic C (C_org), total N and S (N_t, S_t), Zn_t, Pb_t, Zn_ex, Pb_ex, basal respiration (BR), microbial biomass (C_mic) and C_mic-to-C_org ratio. Spectra of the samples were recorded in the Vis-NIR range (400–2,500 nm). To detect heavy-metal-induced changes in the chemical composition of O horizons principal components (PC1–PC7) based on the spectral data were regressed against Zn_t + Pb_t values. A modified partial least squares method was used to develop calibration models for prediction of various chemical and microbial properties of the samples from their spectra. Regression analysis revealed a significant relationship between PC3 and PC5 (r = −0.27 and −0.34, respectively) and Zn_t + Pb_t values, indicating an effect of heavy metal pollution on the spectral properties of the O horizons and thus on their chemical composition. For quantitative estimations, the best calibration model was obtained for C_org-to-N_t ratio (r = 0.98). The models for C_org, N_t, and microbial properties were satisfactory but less accurate. NIRS failed to accurately predict S_t, C_org-to-S_t, Zn_t, Pb_t, Zn_ex, and Pb_ex.