An investigation into the use of an electronic nose to predict the class and growth phase of two potentially pathogenic microorganisms , Eschericha coli (E. coli) and Staphylococcus aureus (S. aureus), has been performed. In order to do this we have developed an automated system to sample, with a high degree of reproducibility, the head space of bacterial cultures grown in a standard nutrient medium. Head spaces have been examined by using an array of six different metal oxide semiconducting gas sensors and classified by a multi-layer perceptron (MLP) with a back-propagation (BP) learning algorithm. The performance of 36 different pre-processing algorithms has been studied on the basis of nine different sensor parameters and four different normalization techniques. The best MLP was found to classify successfully 100% of the unknown S. aureus samples and 92% of the unknown E. coli samples, on the basis of a set of 360 training vectors and 360 test vectors taken from the lag, log and stationary growth phases. The real growth phase of the bacteria was determined from optical cell counts and was predicted from the head space samples with an accuracy of 81%. We conclude that these results show considerable promise in that the correct prediction of the type and growth phase of pathogenic bacteria may help both in the more rapid treatment of bacterial infections and in the more efficient testing of new antibiotic drugs.

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The influence of adsorbed proteins on electrochemical properties of the nitrobenzene‐aqueous interface has been investigated using cyclic voltammetric and impedance techniques. Upon addition of 4 μg/ml ovalbumin cyclic voltammetric normalΔEP values for Cs+ transfer shifted from nearly temperature independent reversible values to more temperature‐dependent irreversible values. These effects were especially pronounced at lower temperatures and suggested formation of a surface film. The cyclic voltammetry of a wide range of concentrations of bovine serum albumin (BSA) in base L/L electrolytes was also studied. Interfacial ac impedance measurements indicated an increase in diffuse layer capacitance accompanied initial BSA adsorption. At high protein concentrations, an adsorbed phase was formed which facilitates faradaic transfer of ions across an otherwise blocked interface.

This paper describes the design and performance of an automated rapid static headspace sampler and a new axisymmetric temperature- controlled sensor chamber. The system is controlled via a virtual instrument embedded within a microcomputer and is capable of taking several hundred measurements per day. The headspace sampler has a repeatability of better than 1% with a dead-volume of only 3.1 ml and lag time of about 470 ms. The new sensor chamber operated at a constant temperature to better than ± 0.1° and gave a marked improvement in both sensor stability and response time, This new design of analytical instrument should provide for the superior analysis of odorant materials.