Optimization of measuring procedure of farmland soils using laser‐induced breakdown spectroscopy

Laser‐induced breakdown spectroscopy (LIBS) is an emerging multi‐elemental analytical technique offering fast and simultaneous quantification of soil properties with minimal sample preparation and effective cost. Due to soil heterogeneity, spectral variation however limits the quantitative robustnes...

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Veröffentlicht in:Soil Science Society of America journal 2020-07, Vol.84 (4), p.1307-1326
Hauptverfasser: Xu, Xuebin, Du, Changwen, Ma, Fei, Shen, Yazhen, Zhang, Yiqiang, Zhou, Jianmin
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Sprache:eng
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Zusammenfassung:Laser‐induced breakdown spectroscopy (LIBS) is an emerging multi‐elemental analytical technique offering fast and simultaneous quantification of soil properties with minimal sample preparation and effective cost. Due to soil heterogeneity, spectral variation however limits the quantitative robustness. In this study, 348 soil samples were collected and prepared for acquisition of LIBS spectra. Influences of shot layer and number on LIBS quality were evaluated by spectral intensity and relative standard deviation (RSD). Effects of shot layer and number and five normalization procedures on LIBS ability to measure soil organic matter (SOM), total nitrogen (TN), and total soluble salt content (TSC), were evaluated using partial least squares regression (PLSR). Increasing shot number reduced LIBS spectral variance, thereby improving the quantitative accuracy of selected soil properties. Deep shot layers (4th or 5th shot layers) reduced the intensities of soil spectra and thereby decreased the quantitative accuracy for TSC. However, deep shot layers improved the SOM and TN prediction performances. Among the normalization approaches, the method based on the correction of Si line (DS) showed superior performance for improving quantitation of SOM and TN. The arithmetic average method (AA) was best for TSC prediction. Optimization of shot layer, number and normalization procedures of LIBS spectra resulted in fair prediction of SOM (residual prediction deviation of validation set, RPDV = 1.608), good prediction of TN (RPDV = 1.836), and very good quantitative analysis of TSC (RPDV = 2.456). Therefore, our findings illustrate very good potential for improving the quantitative accuracy of the LIBS soil spectra.
ISSN:0361-5995
1435-0661
DOI:10.1002/saj2.20071