Evaluating the characteristics of soil vis-NIR spectra after the removal of moisture effect using external parameter orthogonalization

Abstract Timely and accurate monitoring of specific soil properties is essential. Visible and near-infrared (vis-NIR) reflectance spectroscopy has been suggested as a powerful tool to estimate soil properties, but the accuracy of soil property estimates can be strongly affected by soil moisture. External parameter orthogonalization (EPO) has been proposed to be an effective method to alleviate the effects of soil moisture on soil property estimation. The EPO algorithm decomposes the spectra into the useful (containing soil characteristics) part and the external part (affected by moisture). Most studies have focused on the useful part of spectra which contain soil information. However, it remains unclear whether the EPO process could also remove other useful soil information. Thus, the objectives of this study were to investigate the shape of the external part of the spectra, verify the relationship between soil moisture content and the external part, test whether other soil factors (e.g., soil texture) were removed by the EPO process, and propose a model for soil moisture using the spectra angle (EPO-SA) method. Soil samples with various soil moisture contents were analyzed. The results showed that the spectra of the external part, after the EPO process, were mainly correlated with the soil moisture content, with absolute correlation coefficients (|r|) greater than 0.8. These external spectra were not related to inherent soil properties, such as soil organic matter and clay content, with absolute correlation coefficients of less than 0.2. Furthermore, we proposed the EPO-SA method, which can be used to quantitatively predict the soil moisture content (R2 = 0.77, RMSE = 0.09 g kg−1). This approach clarified that useful soil spectral information was not removed by EPO, and it also proved the effectiveness of the EPO algorithm. Additionally, it is also demonstrated that the external spectra are useful for predicting the external factors since they are highly correlated with soil moisture.