In the food, beverage and cosmetic industry and so on, odor sensing systems instead of human sensory test are demanded. We have developed odor sensing systems using QCM (quartz crystal microbalance) sensor array and pattern recognition method. Since the properties of the sensors depend on the gas sorption characteristics of the sensing films coated on them, the optimum films according to target odors should be selected. In this study, we tried to select sensing films appropriate for discrimination of slightly different apple flavors. The examples of typical apple flavors were prepared blending 9 compounds. The sensing films were extracted from various kinds of materials such as lipid, stationary phase material of GC (gas chromatography) and cellulose. The selection method under the condition of the small number of measurements was studied. We analyzed the data of steady-state sensor responses in terms of the Euclidean distance, and the films appropriate for apple flavor discrimination were successfully selected.

A systematic method is proposed to generate a random image with a known correlation function and the modified Laplace distribution; the modified Laplace distribution includes the one-side exponential distribution and the Laplace distribution as a special case. Several random images with an isotropic correlation and the modified Laplace distribution are generated and displayed in figures.