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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.

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An integrated amperometric fructose biosensor based on a gold electrode (AuE) modified with a self-assembled monolayer (SAM) of 3-mercaptopropionic acid (MPA) on which fructose dehydrogenase (FDH) and the mediator tetrathiafulvalene (TTF) are co-immobilized by cross-linking with glutaraldehyde is reported. Variables concerning the behavior of the biosensor were optimized by taking the slope value obtained for the fructose calibration plot in the 0.1-1.0 mM concentration range as a criterion of selection.At an applied potential of +0.20 V, a good repeatability of such slope values (RSD=6.7%, n=10) was obtained with no need to apply a cleaning or pretreatment procedure to the modified electrode. Moreover, results from five different TTF-FDH-MPA-AuEs yielded a RSD of 5.8%. The useful lifetime of one single biosensor was approximately 30 days, exhibiting a 93% of the original response on the 33rd day. A linear calibration graph was obtained for fructose over the 1.0×10 -5 -1.0×10 -3 M range, with a limit of detection of 2.4×10 -6 M. The effect of potential interferents was evaluated. The TTF-FDH-MPA-AuE also performed well in the flow-injection mode. The biosensor was used for the determination of fructose in real samples, and the results compared with those provided by using a commercial enzyme test kit.