AROMA DISCRIMINATION BY PATTERN RECOGNITION ANALYSIS OF RESPONSES FROM SEMICONDUCTOR GAS SENSOR ARRAY

The method was applied to discriminating coffee aromas, essential oils, and volatile compounds with different functional groups. To standardise sample introduction and to remove excess ethanol from volatile mixtures, headspace concentration utilizing a porous polymer trap was incorporated into the sensing system. Pattern recognition techniques such as discriminant analysis and cluster analysis were applied to the normalized response pattern. Two ground coffees, Coffea arabica and C.robusta, and freeze-dried and spray-dried commercial instant coffees were clearly separated by cluster analysis and linear discriminant analysis.