We have investigated the feasibility of laser-induced breakdown spectroscopy (LIBS) as a fast, reliable classification tool for sea salts. For 11 kinds of sea salts, potassium (K), magnesium (Mg), calcium (Ca), and aluminum (Al), concentrations were measured by inductively coupled plasma-atomic emission spectroscopy (ICP-AES), and the LIBS spectra were recorded in the narrow wavelength region between 760 and 800 nm where K (I), Mg (I), Ca (II), Al (I), and cyanide (CN) band emissions are observed. The ICP-AES measurements revealed that the K, Mg, Ca, and Al concentrations varied significantly with the provenance of each salt. The relative intensities of the K (I), Mg (I), Ca (II), and Al (I) peaks observed in the LIBS spectra are consistent with the results using ICP-AES. The principal component analysis of the LIBS spectra provided the score plot with quite a high degree of clustering. This indicates that classification of sea salts by chemometric analysis of LIBS spectra is very promising. Classification models were developed by partial least squares discriminant analysis (PLS-DA) and evaluated. In addition, the Al (I) peaks enabled us to discriminate between different production methods of the salts.
We investigated feasibility of a compact, low-cost, laser-induced breakdown spectroscopy (LIBS) device made up of a Q-switched, diode-pumped, solid-state laser and a nongateable miniature spectrometer for the classification of edible salts. LIBS spectra of edible salts from 12 different geographic origins were obtained by this compact LIBS device. The detection limits of the compact LIBS device for potassium, magnesium, and calcium with effective discrimination power were sufficient to classify the edible salts. The classification model was developed by the multivariate analysis of the LIBS spectra. The comparison of the LIBS results with inductively coupled plasma-atomic emission spectroscopy analysis indicates that the clustering of principal component scores was well dominated by chemical compositions of the salts. The cross-and external validations of the classification model showed reasonable performance (98.3 and 87.5% correctness, respectively). Our results indicate that rapid classification of edible salts can be realized by a compact, low-cost LIBS device.
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