Prediction of organic carbon and nitrogen in forest soil using visible and near-infrared spectroscopy

The aim of this paper was to analyse the potential of laboratory Vis-NIR spectroscopy to determine organic carbon and nitrogen in a representative forest area of the Calabria region (south Italy). To do that, calibration models based on laboratory Vis-NIR spectroscopy and PLSR analysis were developed separately for soil organic carbon (SOC) and nitrogen (N). Soil samples (0-20 cm-depth) were collected at 216 locations, oven-dried and passed through a 2 mm sieve and and analyzed to estimate SOC and N concentrations. Subsequently the Vis-NIR reflectance of each soil sample was measured in laboratory, under artificial light, using an ASD FieldSpec IV 350 - 2500 nm spectroradiometer (Analytical Spectral Devices Inc., Boulder, Colorado, USA). In order, to develop models based on soil spectra and reference laboratory data of SOC and N, Partial least squares regression (PLSR) was used. Before applying the PLSR, spectra data were split into a calibration (144 samples) to develop the models and a validation set (72 samples) to assess the prediction accuracy of the calibration models. Results revealed a high level of agreement between measured and predicted values with high R2 and RMSE; model validation with independent data was satisfactory for both the studied soil properties.