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PEDOLOGY

Modeling of Soil Organic Carbon Fractions Using Visible–Near-Infrared Spectroscopy

^a Soil and Water Science Dep., Univ. of Florida, 2169 McCarty Hall, P.O. Box 110290, Gainesville, FL 32611
^b Dep. of Environmental Sciences, Univ. of California, Riverside, CA 92521

^* Corresponding author (sabgru{at}ufl.edu).

There is a pressing need for rapid and cost-effective tools to estimate soil C across larger landscapes. Visible–near-infrared diffuse reflectance spectroscopy (VNIRS) offers comparable levels of accuracy to conventional laboratory methods for estimating various soil properties. We used VNIRS to estimate soil total organic C (TC) and four organic C fractions in 141 samples collected in the Santa Fe River watershed of Florida. The C fractions measured were (in order of decreasing potential residence time in soils): recalcitrant C (RC), hydrolyzable C (HC), hot-water-soluble C (SC), and mineralizable C (MC). Soil samples were scanned in the visible–near-infrared spectral range. Six preprocessing transformations were applied to the soil reflectance, and five multivariate techniques were tested to model soil TC and the organic C fractions: stepwise multiple linear regression (SMLR), principal components regression, partial least squares regression (PLSR), regression tree, and committee trees. Total organic C was estimated with the highest accuracy, obtaining a coefficient of determination using a validation set (R_v²) of 0.86, followed by RC (R_v² = 0.82), both using PLSR. The SC fraction was modeled best by SMLR (R_v² = 0.70), while PLSR produced the best models of MC (R_v² = 0.65) and HC (R_v² = 0.40). The addition of TC as a predictor improved the VNIRS models of the soil organic C fractions. Our study indicates the suitability of VNIRS to quantify soil organic C pools with widely varying turnover times in soils, which are important in the context of C sequestration and climate change.

Abbreviations: CT, committee trees • HC, hydrolyzable organic carbon • LOG, log(1/reflectance) transformation • MC, mineralizable organic carbon • NGD, Norris gap derivative across a seven-band window • NRA, normalization by the range • PCR, principal components regression • PLSR, partial least squares regression • RC, recalcitrant organic carbon • RMSE_c, root mean square error of calibration • RMSE_v, root mean square error of validation • RPD, residual prediction deviation • RT, regression tree • SC, hot-water-soluble organic carbon • SFRW, Santa Fe River watershed • SGD, Savitzky–Golay first derivative using a first-order polynomial across a nine-band window • SMLR, stepwise multiple linear regression • TC, total organic carbon • VNIRS, visible–near-infrared diffuse reflectance spectroscopy