An electronic nose based on an array of six coated Piezoelectric Quartz crystal (PZQ) sensors has been used for classification of fresh edible oils. The electronic nose was presented with 346 samples of fresh edible oil headspace volatiles, generated at 45ºC. Extra virgin olive (EVO), olive oil (OI) and sunflower oil (SFO), were used over a period of 30 days. The sensor responses were analysed using Principle Component Analysis (PCA), Simplified Fuzzy Adaptive Resonance Theory Mapping (SFAM), and fuzzy logistic classification (FLC). Results for SFAM and FLC were similar, both giving classifications above 95% for the test samples.
|Title of host publication||Electronic noses and olfaction 2000: Proceedings of the seventh international symposium on olfaction and electronic noses|
|Editors||J W Gardner, K C Persaud|
|Publisher||Institute of Physics Publishing|
|Publication status||Published - 2000|
Ali, Z., O'Hare, W. T. L., Rowell, F. J., Sarkodie-Gyan, T., Scott, S. M., & Theaker, B. J. (2000). Classification of fresh edible oils with piezoelectric quartz crystal based electronic nose. In J. W. Gardner, & K. C. Persaud (Eds.), Electronic noses and olfaction 2000: Proceedings of the seventh international symposium on olfaction and electronic noses (pp. 229-234). Institute of Physics Publishing.