National calibration of soil organic carbon concentration using diffuse infrared reflectance spectroscopy

摘要

This study presents the potential of infrared diffuse reflectance spectroscopy (DRS) to predict soil organic carbon (SOC) content. A large national soil library was used, including about 3800 samples collected at two soil depths (0-30 and 30-50 cm) using a 16 x 16 km plot grid over the French metropolitan territory (552,000 km(2)). Reflectance spectra were collected in the laboratory using visible and near infrared (VNIR), near infrared (NIR) and mid infrared (MIR) spectrophotometers. The soil data library was broken down into calibration and validation sets through sample selection at random or based on spectral representativeness. The calibration intensity was investigated in order to assess the optimum number of calibration samples required to obtain accurate models. Predictions were achieved using global or local partial least square regression (PLSR) built using VNIR, NIR and MIR spectra separately or in combination. Local PLSR uses only calibration samples that are spectral neighbors of each validation sample, thus builds one model per validation sample. Model performance was evaluated on the validation set based on the standard error of prediction (SEP), the ratio of performance to deviation (RPDv), and the ratio of performance to interquartile range (RPIQ(v)).