Quantitative analysis of soil cadmium content based on the fusion of XRF and Vis-NIR data

Abstract

Anthropogenic activities, such as sewage irrigation and the application of pesticides and fertilizers, are the main causes of Cadmium (Cd) pollution, which reduces soil quality and threatens the environment and human health. Although the traditional cadmium measurement methods are accurate, it involves complicated sample processing steps and complicated laboratory analysis, which is time-consuming and costly, and is often unfriendly to the environment. X-ray fluorescence (XRF) and visible near-infrared (vis–NIR) spectroscopy have been recognized as alternatives to measure soil heavy metal contamination in a cheap, fast, non-destructive, and environmentally conscious manner. In this study, 370 paddy soil samples from the Nanji area of Poyang Lake were taken as the research object, and the feasibility and effectiveness of XRF and vis-NIR spectroscopy for estimating soil chromium content were discussed, respectively, and the combination of the two was used to estimate soil Cd content. Combined with some spectral preprocessing methods, the quantitative analysis model of least squares support vector machine (LS-SVM) and leave-one-out cross validation with three different data fusions (Equal Weight Fusion, Coaddition Fusion and Outer Product Fusion) was established. The results showed the accuracy and stability of Equal Weight Fusion and Outer Product Fusion was better than the single spectrum quantitative analysis model. The model of Outer Product Fusion at LOOCV set had the best performance with the determination coefficient (R2) of 0.91, root mean square error of cross validation (RMSECV) of 0.12 ​mg/kg and the relative percent deviation (RPD) of 3.27, with R2 ​= ​0.90, RMSEP ​= ​0.13 ​mg/kg and RPD ​= ​3.11 in Prediction set, which can satisfy the detection requirements. This method was accurate, reliable, and can provide a reference for the research of soil heavy metal distribution investigation methods.