Evaluation of two methods to eliminate the effect of water from soil vis–NIR spectra for predictions of organic carbon

Abstract

Visible near infrared reflectance spectroscopy (vis–NIR) is an increasingly popular measurement method that can provide cheaper and faster predictions of soil properties, including soil organic carbon content (SOC). The spectroscopic prediction method relies significantly on the development of regressions of data in spectral databases or libraries. While the vis–NIR estimation of SOC was developed in controlled laboratory conditions, its natural development in recent years has been to perform the vis–NIR measurements in situ, where soil spectra are recorded under field conditions. However, environmental factors, such as soil moisture content, have been shown to affect soil spectra, making the use of regressions derived using soil spectral libraries difficult. Direct standardization (DS) and external parameter orthogonalisation (EPO) are two methods that were proposed for the correction of variable moisture conditions and other environmental factors. In this study, we compared DS and EPO on a set of 150 soil samples (3 depths from each of 50 soil cores) from a farm in New Zealand. The samples were re-wetted under controlled conditions, and spectra were recorded at nine different moisture levels. Our results show that DS and EPO are two effective strategies to mitigate the effects of soil water content on vis–NIR spectra. While DS and EPO results were similar when a large number of soil cores were reserved for calibrating the moisture correction methods, SOC predictions using the EPO correction significantly outperformed those using the DS correction for a lower number of cores (5 cores, 15 samples).