Abstract
Methods to quantify organic carbon (OC) in soil fractions of different stabilities often involve time-consuming physical and chemical treatments. The aim of the present study was to test a more rapid alternative, which is based on the spectroscopic analysis of bulk soils in the mid-infrared region (4000–400 cm −1), combined with partial least-squares regression (PLS). One hundred eleven soil samples from arable and grassland sites across Switzerland were separated into fractions of dissolved OC, particulate organic matter (POM), sand and stable aggregates, silt and clay particles, and oxidation resistant OC. Measured contents of OC in each fraction were then correlated by PLS with infrared spectra to obtain prediction models. For every prediction model, 100 soil spectra were used in the PLS calibration and the residual 11 spectra for validation of the models. Correlation coefficients ( r) between measured and PLS-predicted values ranged between 0.89 and 0.97 for OC in different fractions. By combining different fractions to one labile, one stabilized and one resistant fraction, predictions could even be improved ( r = 0.98 , standard error of prediction=16%). Based on these statistical parameters, we conclude that mid-infrared spectroscopy in combination with PLS is an appropriate and very fast tool to quantify OC contents in different soil fractions.
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