LIBS combined with TrAdaBoost based transfer learning for quantitative analysis of heavy metals in soil particles

Maogang Li; Kui Zhou; Mengfan Zhang; Xuedong Chen; Chunhua Yan; Tianlong Zhang; Hua Li

doi:10.1039/d5ja00227c

January 1, 2025Journal of Analytical Atomic Spectrometry

LIBS combined with TrAdaBoost based transfer learning for quantitative analysis of heavy metals in soil particles

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Key Points

The combination of LIBS and TrAdaBoost enhances quantitative analysis of heavy metals in soil particles, improving detection capabilities.
LIBS shows rapid on-site analysis potential, and transfer learning aids in better feature extraction for accurate quantification.
This method presents a promising approach for environmental monitoring, potentially benefitting agricultural practices.
Further exploration and validation of this method could lead to widespread adoption in soil quality assessment.

Implication

Observational analysis demonstrates improved detection of heavy metals in soil, suggesting a novel method using LIBS with transfer learning.

Abstract

Laser induced breakdown spectroscopy (LIBS) has been proven to be a feasible technique for rapid on-site analysis of soil heavy metals in recent years. However, despite advantages like no complex...

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Cite This Study

Li et al. (2025) studied this question.

synapsesocial.com/papers/68c1ae7f54b1d3bfb60e6c2d https://doi.org/10.1039/d5ja00227c

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LIBS combined with TrAdaBoost based transfer learning for quantitative analysis of heavy metals in soil particles

Key Points

Implication

Abstract

Discussion

Cite This Study

LIBS combined with TrAdaBoost based transfer learning for quantitative analysis of heavy metals in soil particles

Key Points

Implication

Abstract

Discussion

Cite This Study

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