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Rapid estimation of soil engineering properties using diffuse reflectance near infrared spectroscopy

Waruru, Bernard K., Shepherd, Keith D., Ndegwa, George M., Kamoni, Peter T., Sila, Andrew M.
Biosystems engineering 2014 v.121 pp. 177-185
air drying, basins, cation exchange capacity, civil engineering, clay, clay fraction, extensibility, laboratory techniques, least squares, materials testing, near-infrared spectroscopy, prediction, reflectance, shrinkage, soil mechanical properties, soil types, spectrometers, water content, Kenya, Lake Victoria
Materials testing involve complex reference methods and several soil tests have been used for indexing material functional attributes for civil engineering applications. However, conventional laboratory methods are expensive, slow and often imprecise. The potential of soil diffuse reflectance near infrared (NIR) spectroscopy for the rapid estimation of selected key engineering soil properties was investigated. Two samples sets representing different soils from across the Lake Victoria basin of Kenya were used for the study: A model calibration set (n = 136) was obtained using a conditioned Latin hypercube sampling, and a validation set (n = 120) using a spatially stratified random sampling strategy. Spectral measurements were obtained for air-dried (<2 mm) soil sub-samples using a Fourier-transform diffuse reflectance near infrared (NIR) spectrometer. Soil laboratory reference data were also obtained for liquid limit (LL), plastic limit (PL), plasticity index (PI), linear shrinkage (LS), coefficient of linear extensibility (COLE), volumetric shrinkage (VS), clay activity number (Ac), total clay content, air-dried moisture content, and cation exchange capacity (CEC). Soil reference data were calibrated to smoothed first derivative NIR spectra using partial least squares (PLS) regression. At the calibration stage, coefficient of determination for full cross-validation (R2) of ≥0.70 was obtained for CEC, mc, LL, PI, LS, COLE and VS. Further independent validation gave R2 ≥ 0.70 and RPD (ratio of reference data SD and root mean square error of prediction) 1.7–2.2 for LL, PI, mc and CEC. The results suggested that NIR–PLS has potential for the rapid estimation of several key soil engineering properties. Further work should focus on extending calibration libraries using more diverse soil types and testing alternative infrared diffuse reflectance based methods.