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[Quantitative Analysis of Mn in Soil Based on LIBS with Multivariate Nonlinear Method].

Ping Wang, Dui-yuan Li

    Guang Pu Xue Yu Guang Pu Fen Xi = Guang Pu
    |July 28, 2018
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    Summary

    Laser-induced breakdown spectroscopy (LIBS) accurately measures manganese (Mn) in soil. A multivariate nonlinear calibration method significantly improves accuracy by reducing matrix effects, making LIBS a reliable tool for soil Mn analysis.

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    Area of Science:

    • Agricultural Science
    • Analytical Chemistry
    • Spectroscopy

    Background:

    • Manganese (Mn) is an essential micronutrient for plant growth.
    • Accurate soil Mn concentration is crucial for optimizing plant nutrition and yield.
    • Traditional methods for soil analysis can be time-consuming and labor-intensive.

    Purpose of the Study:

    • To determine the concentration of manganese (Mn) in soil samples using laser-induced breakdown spectroscopy (LIBS).
    • To evaluate the effectiveness of different calibration methods in mitigating matrix effects for accurate Mn quantification.
    • To establish LIBS as a viable technique for rapid and precise soil Mn analysis.

    Main Methods:

    • Acquisition of LIBS spectral data from 46 diverse soil samples.
    • Selection of the characteristic Mn line at 403.1 nm for analysis.
    • Comparison of a simple calibration curve method with a multivariate nonlinear calibration approach.

    Main Results:

    • Simple calibration resulted in a correlation coefficient of 0.78, heavily influenced by matrix effects.
    • Multivariate nonlinear calibration, considering interferences from C and Fe, yielded a prediction correlation coefficient of 0.97.
    • The relative measured error was reduced to 3.2%–10.3% with the advanced method.

    Conclusions:

    • Matrix effects significantly impact LIBS accuracy in complex soil samples.
    • Multivariate nonlinear calibration effectively reduces matrix effects and enhances Mn measurement precision.
    • LIBS combined with multivariate nonlinear calibration is a powerful tool for quantitative soil Mn analysis.