Abstract/Summary

Soil analysis for agriculture, pollution assessment/remediation or resource exploration requires rapid procedures that are reliable, fast and cheap. This study examined the potential of visible near infrared diffuse reflectance spectroscopy (VNIR DRS) for soil analysis with emphasis on soil organic carbon (SOC) and extractible total petroleum hydrocarbon (ETPH). Preliminary laboratory studies were conducted to determine if visible near infrared diffuse reflectance spectral data contain adequate information for characterising SOC and ETPH and to identify sensitive wavelength regions best suited for quantitative modeling. It was concluded that VNIR DR spectra contained adequate information to quantify both SOC and ETPH in soils. Modelling with the whole spectrum was also found to give better predictions compared to modelling with portions of the spectrum. A 76/24 dataset split pattern was identified as an optimal split, ensuring that significant proportions of datasets are used for both model calibration and testing. Soil is inherently heterogeneous varying in space. The prediction performances of VNIR DRS models were observed to reduce with an increase in the geographical size of soil collection sites indicating that the best calibration models will likely be generated from spectral data derived from local soils with similar geology. Performance of VNIR DRS for characterizing ETPH was affected by SOC content. Higher model performances were observed at low organic carbon content, though all models developed for the SOC range studied (0.94 – 26.5%) had good prediction qualities (RPD > 2). Similarly, model performances were also affected by the type of petroleum hydrocarbon product that had been used to contaminate soils. This study provides evidence that VNIR DRS can be an important analytical approach to soil analysis particularly when and where costs and time are limiting conditions.