Water-based measured-value fuzzification improves the estimation accuracy of soil organic matter by visible and near-infrared spectroscopy

Abstract

Visible and near-infrared (Vis-NIR) reflectance spectroscopy continues to emerge as a rapid and effective approach for estimating several soil physical and chemical properties including soil organic matter (SOM), but its accuracy is restricted by many factors including soil water. This study proposed the water-based measured-value fuzzification (WMF) method to decrease the influence of soil water, and combined with the partial least squares regression (PLSR) to develop SOM models. Vis-NIR spectral data was measured by an ASD FieldSpec 3 spectrometer. After WMF analysis, the PLSR method was used to develop SOM models. By comparison with the PLSR model, the WMF-PLSR model produced markedly better results (root mean square error of validation [RMSEV] = 2.776 g/kg, mean relative error of validation [MREV] = 8.111%, and ratio of performance to interquartile range [RPIQv] = 4.729). With these, the WMF method combined with PLSR shows the potential for estimating SOM content and expands the range of observation methods.