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Estimation of metal elements content in soil using x-ray fluorescence based on multilayer perceptron

文献类型： 外文期刊

作者： Li, Fang 1 ; Zhang, Xiaofeng 3 ; Lu, Anxiang 2 ; Xu, Li 2 ; Ren, Dong 3 ; You, Tianyan 1 ;

作者机构： 1.Jiangsu Univ, Sch Agr Engn, Zhenjiang 212013, Jiangsu, Peoples R China

2.Beijing Acad Agr & Forestry Sci, Beijing 100097, Peoples R China

3.Three Gorges Univ, Coll Comp & Informat Technol, Yichang 443002, Hubei, Peoples R China

关键词： X-ray fluorescence; Heavy metal; Soil; Multilayer perceptron

期刊名称：ENVIRONMENTAL MONITORING AND ASSESSMENT （ 影响因子：3.307； 五年影响因子：3.42 ）

ISSN： 0167-6369

年卷期： 2022 年 194 卷 2 期

页码：

收录情况： SCI

摘要： X-ray fluorescence (XRF) is widely used to rapidly detect heavy metals in soil. Spectra processing has been an important research topic to improve accuracy. In this study, 80 soil samples were analyzed by XRF under indoor conditions, where different preprocessing and quantitative analysis methods were compared in terms of prediction accuracy. Denoising algorithms were used to preprocess the soil spectra before establishing prediction models for As, Pb, Cu, Cr, and Cd in soil. The influence of denoising methods on the prediction effects of different models was compared and discussed. The results on five heavy metal spectra show that the proper spectral preprocessing method can effectively improve the prediction performance of the model. The multilayer perceptron model provides promising analysis and modeling for the five metal elements. The determination coefficients (R-2) of the models were 0.857, 0.976, 0.977, 0.995, and 0.886, respectively. The proposed method provides the potential to support accurate quantitation by XRF analysis.

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