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Mapping with laser-induced breakdown spectroscopy (LIBS) can offer more than just the spatial distribution of elements: the rich spectral information also enables mineral recognition. In the present study, statistical approaches were used for the recognition of the spodumene from lithium pegmatite ores. A broad spectral range (280–820 nm) with multiple lines was first used to establish the methods based on vertex component analysis (VCA) and K-means and DBSCAN clusterings. However, with a view to potential on-site applications, the dimensions of the datasets must be reduced in order to accomplish fast analysis. Therefore, the capability of the methods in mineral identification was tested with a limited spectral range (560–815 nm) using Li-pegmatites with various mineralogical characters.

Optimization of spodumene identification by statistical approach for laser-induced breakdown spectroscopy data of lithium pegmatite ores