Simulated in situ characterization of soil organic and inorganic carbon with visible near-infrared diffuse reflectance spectroscopy

Visible and near-infrared (VisNIR, 400–2500 nm) diffuse reflectance spectroscopy (DRS) is a rapid, inexpensive sensing method that has shown promise for lab-based soil characterization. However, little has been reported on how DRS will work in a field setting on intact soil cores. Seventy-two soil cores, representing 21 soil series and four parent materials, were extracted from six fields in Central Texas. Each soil core was scanned with a VisNIR spectrometer with a spectral range of 350–2500 nm in four combinations of moisture content and pre-treatment, including field-moist intact, air-dried intact, field-moist smeared intact, and air-dried ground. Visible near-infrared spectra were then used to predict soil organic and inorganic carbon (C) using partial least squares (PLS) regression. The PLS model was validated with 30% of the original soil cores that were randomly selected and withheld from the calibration model. The organic C validation had a root mean squared deviation (RMSD) of 5.4 g kg− 1 and 4.1 g kg− 1 for the field-moist and air-dried intact scans, respectively. The RMSD values for inorganic C were 8.7 g kg− 1 and 7.8 g kg− 1 for the field-moist and air-dried intact scans, respectively. Smearing the samples had minimal effects on prediction accuracies for organic and inorganic C. Variable soil moisture did reduce prediction accuracies. Soil color, pH, and soil reaction to 1 N HCL were added as auxiliary predictors. Soil color improved organic C predictions by 0.2 to 0.4 g kg− 1. The field-moist intact inorganic C model improved with soil color (RMSD = 8.0 g kg− 1), soil pH (8.3 g kg− 1), and soil reaction to HCl (6.5 g kg− 1). These results show that in situ spectroscopy can measure organic and inorganic C with some loss of accuracy compared to dried ground samples. In inorganic C predictions, an easy-to-measure auxiliary variable, like soil reaction with 1 N HCl, can improve in situ predictions compared to dried ground predictions.