Improved Intact Soil-Core Carbon Determination Applying Regression Shrinkage and Variable Selection Techniques to Complete Spectrum Laser-Induced Breakdown Spectroscopy (LIBS)

2013 ◽  
Vol 67 (10) ◽  
pp. 1185-1199 ◽  
Author(s):  
Ross S. Bricklemyer ◽  
David J. Brown ◽  
Philip J. Turk ◽  
Sam M. Clegg
2017 ◽  
Vol 32 (6) ◽  
pp. 1166-1176 ◽  
Author(s):  
Xiao Fu ◽  
Fa-Jie Duan ◽  
Ting-Ting Huang ◽  
Ling Ma ◽  
Jia-Jia Jiang ◽  
...  

A fast variable selection method combining iPLS and mIPW-PLS is proposed to reduce the dimensions of the spectrum for LIBS quantitative analysis.


Sensors ◽  
2020 ◽  
Vol 20 (18) ◽  
pp. 5419 ◽  
Author(s):  
Sara Sánchez-Esteva ◽  
Maria Knadel ◽  
Sergey Kucheryavskiy ◽  
Lis W. de Jonge ◽  
Gitte H. Rubæk ◽  
...  

Conventional wet chemical methods for the determination of soil phosphorus (P) pools, relevant for environmental and agronomic purposes, are labor-intensive. Therefore, alternative techniques are needed, and a combination of the spectroscopic techniques—in this case, laser-induced breakdown spectroscopy (LIBS)—and visible near-infrared spectroscopy (vis-NIRS) could be relevant. We aimed at exploring LIBS, vis-NIRS and their combination for soil P estimation. We analyzed 147 Danish agricultural soils with LIBS and vis-NIRS. As reference measurements, we analyzed water-extractable P (Pwater), Olsen P (Polsen), oxalate-extractable P (Pox) and total P (TP) by conventional wet chemical protocols, as proxies for respectively leachable, plant-available, adsorbed inorganic P, and TP in soil. Partial least squares regression (PLSR) models combined with interval partial least squares (iPLS) and competitive adaptive reweighted sampling (CARS) variable selection methods were tested, and the relevant wavelengths for soil P determination were identified. LIBS exhibited better results compared to vis-NIRS for all P models, except for Pwater, for which results were comparable. Model performance for both the LIBS and vis-NIRS techniques as well as the combined LIBS-vis-NIR approach was significantly improved when variable selection was applied. CARS performed better than iPLS in almost all cases. Combined LIBS and vis-NIRS models with variable selection showed the best results for all four P pools, except for Pox where the results were comparable to using the LIBS model with CARS. Merging LIBS and vis-NIRS with variable selection showed potential for improving soil P determinations, but larger and independent validation datasets should be tested in future studies.


Author(s):  
Weiran Song ◽  
Zongyu Hou ◽  
Muhammad Sher Afgan ◽  
Weilun Gu ◽  
Hui Wang ◽  
...  

Variable selection based on ensemble learning and validation for rapid and low-cost analysis of coal properties using laser-induced breakdown spectroscopy.


2017 ◽  
Vol 409 (11) ◽  
pp. 3017-3024 ◽  
Author(s):  
Fabiano Barbieri Gonzaga ◽  
Lescy Romulo Braga ◽  
Alexandre Pimentel Sampaio ◽  
Thiago de Souza Martins ◽  
Charles Giovani de Oliveira ◽  
...  

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