Identification and discrimination of bacterial strains by laser induced breakdown spectroscopy and neural networks.

A method based on laser induced breakdown spectroscopy (LIBS) and neural networks (NNs) has been developed and applied to the identification and discrimination of specific bacteria strains (Pseudomonas aeroginosa, Escherichia coli and Salmonella typhimurium). Instant identification of the samples is achieved using a spectral library, which was obtained by analysis using a single laser pulse of representative samples and treatment by neural networks. The samples used in this study were divided into three groups, which were prepared on three different days. The results obtained allow the identification of the bacteria tested with a certainty of over 95%, and show that only a difference between the bacteria can cause identification. Single-shot measurements were sufficient for clear identification of the bacterial strains studied. The method can be developed for automatic real time, fast, reliable and robust measurements and can be packaged in portable systems for non-specialist users.