Methods of bacteria recognition relying on simple hardware techniques.

Bacterial contamination puts the public at risk and is costly for the food-processing industry. Traditional (biochemical) methods of bacteria recognition require complicated sample preparation for reliable results. Automated technologies exist for the identification of bacterial cells in suspension, but are relatively expensive with only limited success. Therefore, an early warning system that could be applied with little effort and expenditure to give an indication of whether or not more in-depth analytical procedures would be commendable has a high potential on the market. The work presented here demonstrates two methods utilizing flexible and low-cost equipment together with pattern-recognition techniques to form a first-stage bacteria recognition system. Bacterial colonies are excited with laser light and electromagnetic power and their actions are recorded with simple optical sensors. The generated data are the basis for pattern generation algorithms and are evaluated statistically and with Fourier and Principal Component Analysis methods. Focusing on three bacteria species, namely Escherichia coli, Proteus mirabilis, and Bacillus subtilis, the two systems as described here distinguish the species and indicate typical classes to provide the user with a first impression on the sample content.