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Measurement of potentially toxic elements in the soil through NIR, MIR, and XRF spectral data fusion

文献类型： 外文期刊

作者： Li, Fang 1 ; Xu, Li 1 ; You, Tianyan 2 ; Lu, Anxiang 1 ;

作者机构： 1.Beijing Res Ctr Agr Stand & Testing, Beijing 100097, Peoples R China

2.Jiangsu Univ, Sch Agr Engn, Inst Agr Engn, Zhenjiang 212013, Jiangsu, Peoples R China

关键词： X-ray fluorescence; Near-infrared; Mid-infrared; Successive projections algorithm; Partial least square regression

期刊名称：COMPUTERS AND ELECTRONICS IN AGRICULTURE （ 影响因子：5.565； 五年影响因子：5.494 ）

ISSN： 0168-1699

年卷期： 2021 年 187 卷

页码：

收录情况： SCI

摘要： This paper aims to investigate the feasibility combination of X-ray fluorescence (XRF), near-infrared (NIR), and mid-infrared (MIR) sensors for the detection of seven key monitoring elements in the soil. Two strategies for data fusion were adopted: (i) the XRF characteristic bands were fused with all spectral data of NIR and MIR separately, and (ii) the XRF characteristic bands were fused with the characteristic bands of NIR and MIR, respectively. Also, different feature extraction methods were compared. The best feature extraction methods for XRF-NIR and XRFMIR models were principal component analysis (PCA) and successive projections algorithm (SPA). The modeling results showed that strategy (ii) showed better performance, and the XRF-MIR model provided more accurate results than the XRF-NIR model. Both XRF-MIR and XRF-NIR methods improved the accuracy of As, Cr, Cu, Ni, and Zn. The XRF-MIR obtained the best predictions, and the determination coefficients (R2) were 0.93, 0.98, 0.98, 0.95, and 0.98. For Pb and Cd, the measurement could be obtained by XRF alone, and the corresponding R2 were both 0.98. The results confirmed that sensor fusion can effectively improve the accuracy of the spectrometer in detecting metal elements in the soil.

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