Multivariate Analysis of Laser-Induced Breakdown Spectroscopy Spectra of Soil Samples

Abstract

Laser-induced breakdown spectroscopy (LIBS) is a rapid quantitative analytical technique that can be used to determine the elemental composition of numerous sample matrices, and it has been successfully applied in many types of samples. However, for chemically and physically complex soil samples, its quantitative analytical ability is controversial. Multivariate analytical techniques have great potential for analyzing the complex LIBS spectra. To demonstrate the feasibility of LIBS as an alternative technique to quantitatively analyze soil samples, the univariate and the partial least square (PLS) techniques are used to analyze the LIBS spectra of 12 soil samples and to build calibration models predicting Cu and Zn concentrations. The results show that PLS can significantly improve the analytical results compared with the univariate technique. The normalized root mean square error (NRMSE) and r 2 of the univariate models are 16.60% and 0.71 in calibration and 18.80% and 0.62 in prediction for Cu and 18.97% and 0.62 in calibration and 22.81% and 0.45 in prediction for Zn. For the PLS models using the spectral range 300 to 350 nm, the NRMSE and r 2 are 1.94% and 0.99 for both Cu and Zn in calibration and 7.90% and 0.94 for Cu and 8.14% and 0.94 for Zn in prediction, respectively. Compared with the univariate technique, PLS improves the NRMSE 87.53% and 87.78% in calibration and 44.47% and 53.44% in prediction for Cu and Zn, respectively. The results indicate that PLS can improve the quantitative analytical ability of LIBS for soil sample analysis.

Calibration Methods of Laser-Induced Breakdown Spectroscopy

“…There is no doubt that the multivariate analysis is superior to univariate analysis. This has been proven by numerous researchers, for instance, the analysis of rocks [49], rare earth elements [38], glass [50], cerium oxide [51], alloy steel [52], liquid steel [53], soil [54,55], soybean oil [56], PZT (Lead Zirconate Titanate) ceramics [57], Pb in navel orange [58], Marcellus Shale [59], tailing cores [60], geologically diverse samples [49], steel melt [61], slurry [62], iron ore [63] and pellets of plant materials [64].…”

Applications of High Resolution Laser: Induced Breakdown Spectroscopy for Environmental and Biological Samples

“…A number of authors [18][19][20][21][22][23] have revealed that the technique of LIBS when accompanied by the use of multivariate statistical analysis for the analysis of a large number of LIBS spectra is a very powerful tool to help us to understand the clustering of the samples into specific groups based on their chemistry. Principal component analysis (PCA) is commonly used to isolate the spectral wavelength that is a fingerprint for the presence of an element that can be correlated with chemical differences between the samples.…”

Effects of sample pretreatment and particle size on the determination of nitrogen in soil by portable LIBS and potential use on robotic-borne remote Martian and agricultural soil analysis systems

“…This is challenging because, as mentioned above 8 the quality of LIBS results obtained is enormously inuenced by the chemical and physical properties of the sample, which in turn depend on how the sample was pretreated prior to analysis. [33][34][35][36][37][38][39][40] Various methods of soil sample preparation have been developed to achieve the homogeneity required for LIBS analysis, including mechanical pressure, 41 grinding and sieving 42 and a combination of these. 39,[43][44][45] However, these potentially may be difficult to replicate in a eld setting, especially using an autonomous rover analytical platform.…”