CHEMOMETRIC-BASED ELECTRONIC NOSE APPLICATION TO PORK OIL AND OLIVE OIL USING THE ODOR PATTERN CLASSIFICATIONS

Abstract

A chemometric-based electronic nose has designed for analyzing pork oil and olive oil  using the odor pattern classifications. The electronic nose (e-nose) built from a combination of several chemical sensors derived from a semiconductor. The data retrieval was done by vaporizing the sample, then being captured by the sensor and identified by the electronic nose (e-nose). The output data from the electronic nose is the voltage released by each sensor. The analyzed samples were 100% olive oil, 100% pork oil and a combination of olive oil and pork oil with a ratio of 50%: 50%. The result of pattern classification using linear discriminant analysis (LDA) method shows that each sample is clustered well with the percentage of first discriminant function value is 87,9% and second discriminant function is 12,1%.