Chemical sensor arrays can be used to identify and classify complex gas mixtures or odors (Shurmer, H. V., An electronic nose: A sensitive and discriminating substitute for a mammalian olfactory system, IEEE proc. G 137, 197-204, 1990; Gardner, J. W. and Bartlett, P. N. (eds), Sensors and Sensory Systems for an Electronic Nose, Proc. NATO Advances Research Workshop, Reykjavik, 1992.). Chemical sensors are in general non-specific, but have different selectivity patterns towards the species in the odor. More specifically, it has been demonstrated how large sensing surfaces consisting of different catalytic metals in metal-oxide-semiconductor field effect structures can be used together with an optical evaluation technique to obtain visually identifiable images of odors (I. Lundström, R. Erlandsson, U. Frykman, E. Hedborg, A. Spetz, H. Sundgren, S. Welin, and F. Winquist, Artificial ‘olfactory’ images from a chemical sensor using a light-pulse technique Nature, 352, 47-50, 1991. It is important to note that this increased informational content is derived from the (continuous) varying selectivity profile along the sensing surface for the sensor array. No discrete recognition elements are known to exist. Different pattern recognition methods based on statistical approaches or artificial neural networks can be used to evaluate the signal patterns from these sensors. The devices have been used to analyze a variety of food stuffs (Winquist, F., Hörnsten, E. G., Sundgren, H. and Lundström, I., Performance of an electronic nose for quality estimation of ground meat, Meas. Sci. Technol. 4, 1493-1500, 1993.; Winquist, F., Hörnsten, G., Holmberg, M., Nilsson, L. And Lundström, I. Classification of bacteria using a simplified sensor array and neural nets”, submitted).