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This article in SSSAJ

  1. Vol. 73 No. 1, p. 176-184
    Received: Jan 19, 2008

    * Corresponding author(s): sabgru@ufl.edu
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Modeling of Soil Organic Carbon Fractions Using Visible–Near-Infrared Spectroscopy

  1. Gustavo M. Vasquesa,
  2. Sabine Grunwald *a and
  3. James O. Sickmanb
  1. 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


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 v 2) of 0.86, followed by RC (R v 2 = 0.82), both using PLSR. The SC fraction was modeled best by SMLR (R v 2 = 0.70), while PLSR produced the best models of MC (R v 2 = 0.65) and HC (R v 2 = 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.

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