Microorganisms, such as bacteria, which might be present as contamination inside an industrial food or pharmaceutical clean room process need to be identified on short time scales in order to minimize possible health hazards as well as production downtimes causing financial deficits. Here we describe the first results of single-particle micro-Raman measurements in combination with a classification method, the so-called support vector machine technique, allowing for a fast, reliable, and nondestructive online identification method for single bacteria.
Fast analysis of bioaerosols in clean room environments is necessary in order to prevent contamination of pharmaceutical products, minimize machine downtimes, or both. The detection and identification of microbes will be carried out in several steps: After impaction of the aerosol on a surface, the particles are presorted with glancing light illumination and fluorescence imaging in order to distinguish between abiotic and biotic particles. Since only the biotic particles are of interest, the analysis time can be minimized due to reduction of the data set. The biotic particles are then analyzed further with Raman spectroscopy and identified with a support vector machine.
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