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Combining Laser-Induced Breakdown Spectroscopy and Visible Near-Infrared Spectroscopy for Predicting Soil Organic
Alex Wangeci1,2, Daniel Adén2, Thomas Nikolajsen2
1Department of Agroecology, Aarhus University, Blichers Allé 20, 8830 Tjele, Denmark.
Sensors (Basel, Switzerland)
|July 27, 2024
Summary
Laser-induced breakdown spectroscopy (LIBS) and visible near-infrared spectroscopy (vis-NIRS) accurately predict soil properties. LIBS, especially with variable selection, showed superior accuracy for soil organic carbon and texture compared to combined methods.
Area of Science:
- Soil Science
- Analytical Chemistry
- Spectroscopy
Background:
- Traditional laboratory methods for soil analysis are time-consuming and costly.
- Spectroscopic techniques like LIBS and vis-NIRS offer rapid, cost-effective alternatives for large-scale soil property determination.
- Combining LIBS and vis-NIRS can potentially improve prediction accuracy over single-sensor approaches.
Purpose of the Study:
- To evaluate the performance of LIBS and vis-NIRS, individually and combined, for predicting soil organic carbon (SOC) and texture.
- To assess the impact of variable selection using interval partial least squares regression (iPLSR) on prediction accuracy.
- To compare the predictive capabilities of single-sensor, combined-sensor, and variable-selected models.
Main Methods:
- Development of partial least squares regression (PLSR) models for LIBS and vis-NIRS spectra.
- Merging LIBS and vis-NIRS spectral data for combined PLSR modeling.
- Application of interval partial least squares regression (iPLSR) for variable selection and accuracy assessment.
- Utilizing a comprehensive Danish national-scale soil dataset.
Main Results:
- LIBS and vis-NIRS showed comparable prediction performance for soil texture and SOC.
- Combined LIBS-vis-NIRS spectra improved prediction accuracy compared to single-sensor LIBS.
- Vis-NIRS single-sensor predictions showed significant improvements over LIBS.
- iPLSR significantly enhanced prediction accuracy for both LIBS and vis-NIRS.
- LIBS iPLSR models demonstrated superior prediction accuracy compared to combined LIBS-vis-NIRS models.
Conclusions:
- LIBS and vis-NIRS are effective spectroscopic methods for soil property prediction.
- Variable selection using iPLSR provides substantial benefits, particularly for LIBS.
- LIBS coupled with variable selection offers a highly accurate approach for soil analysis, potentially outperforming combined spectral methods.
- Further research should consider the influence of reference method uncertainty on prediction accuracy.
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