Quality tests of electronic noses: the influence of sample dilution and sensor drifts on the pattern recognition for selected case studies

Arrays of chemical sensors have a broad spectrum of applications, e.g., in the field of process control and quality analysis. Especially for the fast and objective evaluation of food quality and off-flavour contents in plastic materials, such sensor systems, often called “Electronic Noses”, have an increasing demand. In this context, the performance and reproducibility of an array analysis is usually not checked systematically. The present paper therefore deals with the influence of sample dilution (external effect) and of changed sensor parameters with time (internal effect) on the subsequent results of pattern recognition.