Abstract
Laser-induced breakdown spectroscopy spectra of bacterial spores, molds, pollens and nerve agent simulants have been acquired. The performance of several statistical methodologies–linear correlation, principal components analysis, and soft independent model of class analogy–has been evaluated for their ability to differentiate between the various samples. The effect of data selection (total spectra, peak intensities, and intensity ratios) and pre-treatments (e.g., averaging) on the statistical models have also been studied. Results indicate the use of spectral averaging and weighting schemes may be used to significantly improve sample differentiation.
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