A novel approach for discovering correlations between elemental and molecular composition using laser-based spectroscopic techniques.

Abstract

Modern analytical techniques, including laser-induced breakdown spectroscopy (LIBS) and Raman spectroscopy, yield multidimensional data, which are most efficiently used in conjunction with chemometric techniques, including multi-block algorithms. In this study, we use several algorithms for the processing of laser-induced breakdown and Raman spectra of zooplankton organisms, which are found to accumulate lithium for an unknown reason. Correlations between elemental and molecular composition of zooplankton have been found. We studied 29 samples: crustaceans, arrow worms, and sea snails. The obtained spectra were examined by principal component analysis (PCA), non-negative matrix factorization (NMF), consensus PCA (CPCA), and analysis of common components and specific weights (CCSWA, or ComDim). LIBS spectra are more sensitive towards taxonometric differences than Raman spectra. All the algorithms gave similar results, although still differing in details. Data fusion revealed a number of relationships, including the correlation of Li with potassium (R = 0.83, n = 14), with Raman bands of carotenoids (R = 0.89, n = 11) and tryptophan (R = 0.94, n = 9). The correlations were most pronounced in light-coloured parts of the inhomogeneous biological material. Ratios of fatty acids are associated with Li concentration if above 200 mg kg-1. Valine is also related to the Li accumulation. Thus, it is shown that the combination of LIBS and Raman spectroscopy, followed by appropriate mathematical treatment, is a convenient tool for comprehensive studies of environmental objects.