Visible–Near-Infrared Spectroscopy Can Predict the Clay/Organic Carbon and Mineral Fines/Organic Carbon Ratios

• Published in: Soil Science Society of America Journal
• Main Authors: Hermansen, Cecilie, Knadel, Maria, Møldrup, Per, Greve, Mogens Humlekrog, Gislum, René, de Jonge, Lis Wollesen
• Format: Article in Journal/Newspaper
• Language: English
• Published: 2016
• Subjects: greenlandic
• Online Access: https://pure.au.dk/portal/da/publications/visiblenearinfrared-spectroscopy-can-predict-the-clayorganic-carbon-and-mineral-finesorganic-carbon-ratios(5294bfe2-d178-4052-aeea-a71f1f9929d3).html; https://doi.org/10.2136/sssaj2016.05.0159

The ratios of mineral fines (<0.02 mm, clay + fine silt) to organic carbon (OC), consisting of the n-ratio (i.e., the clay/OC ratio) and m-ratio (i.e., the fines/OC ratio) have recently been used to analyze and predict soil functional properties such as tilth conditions, clay dispersibility, degree of preferential flow, water repellency, and chemical adsorption. Conventional texture and OC measurements are time consuming and expensive, and visible–near-infrared (vis-NIR) spectroscopy may provide a fast and inexpensive alternative for obtaining the n- and m-ratios. In this study, a total of 480 soil samples from seven Danish and one Greenlandic fields, with a large textural range (clay: 0.027–0.355 kg kg−1; OC: 0.011–0.084 kg kg−1; n-ratio: 0.49–16.80; m-ratio: 1.46–32.14), were analyzed for texture and OC and subsequently scanned with a vis-NIR spectrometer from 400 to 2500 nm. The spectral data were correlated to reference values of the n-ratio, m-ratio, clay, fine silt, fines, and OC with partial least squares regression. The vis-NIR models were developed on a regional dataset comprising the 480 soil samples divided into calibration and validation subsets. Further, we tested vis-NIR models developed on the individual eight fields using full cross-validation. Validation results from the regional models showed high predictive abilities with a root mean square error of prediction (RMSEP) of 0.64 and R2 of 0.97 for the n-ratio and RMSEP = 1.43 and R2 of 0.97 for the m-ratio. The regional clay, fine silt, fines, and OC models also yielded successful predictions (R2 = 0.88–0.95). The higher prediction accuracy for the n- and m-ratios compared with predictions of basic soil properties was confirmed from the field-specific models. Our results suggest vis-NIR spectroscopy as a precise, easily applicable, and fast method for simultaneously obtaining an ensemble of key parameters for soil structure and health.