Feasibility of vis-NIR spectroscopy for estimating thermally defined soil organic carbon fractions

Soil organic carbon (SOC) is an important soil health indicator. The SOC directly influences major soil functions such as nutrient cycling, fertility, soil structure, and water and air regulation. As a result, it is important to understand both the soil’s storage capacity and the stability of this carbon. Several methods have been developed to assess distinct SOC pools based on different physical, biological, and thermal definitions. Rock Eval 6 thermal analysis partitions SOC into four operational fractions (S1 to S4), which serve as proxies for organic compounds of increasing thermal stability. Thus is S1 the most labile and easily decomposable, S2 and S3 reflecting progressively more stable organic carbon pools, and the residual refractory carbon measured as S4. Although Rock Eval 6 provides accurate and reproducible estimates of thermally defined SOC fractions, the high initial investment cost and low analytical throughput limit its application for large scale monitoring. Despite the promising application of soil diffuse reflectance spectroscopy for predicting various soil properties, a comprehensive evaluation of this method for estimating Rock Eval 6 derived SOC fractions is lacking. In this presentation, we evaluate the feasibility of vis-NIR spectroscopy as a non-destructive and cost-effective alternative method to predict Rock Eval 6 SOC fractions (S1 to S4). A total of 131 soil samples were collected from lowland areas across Denmark under different land-use types. Partial least squares regression and interval partial least squares regression were applied to relate soil reflectance spectra measured between 400 and 2500 nm to thermally defined SOC fractions. Our results indicate that vis-NIR spectroscopy can reliably estimate thermally defined SOC fractions derived from Rock Eval 6 analysis, with R² values of 0.79, 0.81, 0.78, and 0.53 for S1, S2, S3 and S4, respectively. Among the individual fractions, S2 was estimated with the highest accuracy, while S1 and S3 showed moderate predictive performance and S4 exhibited lower accuracy. Based on these statistical parameters, we conclude that vis-NIR spectroscopy is a feasible and rapid tool for estimating thermally defined SOC fractions.