Classification of pure and mixture Agarwood oils by Electronic Nose and Discriminant Factorial Analysis (DFA)

Abstract

This paper describes the performance of a commercial AlphaMOS 4000 Electronic Nose coupled with Discriminant Factorial Analysis (DFA) as statistical tool used in discriminating the differences between pure and mixture agarwood oils by their volatile properties. The proposed techniques in this paper for testing and evaluating the capability of E-Nose for classifying and testing two different groups pure and mixtures Agarwood oil is successfully conducted. E-Nose coupled with DFA as a statistical tool is capable to discriminate ten oils from two separate groups pure and mixtures by their different odor uniqueness with significant p-value <; 0.05 and both groups are recognized as different samples with 100% accuracy. Lastly, for selected unknown sample projection, the projection accuracy is 90%.