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Sensors 2010, 10(5), 4675-4685; doi:10.3390/s100504675

Classification of Agarwood Oil Using an Electronic Nose

Sensor Technology and Applications Research Cluster, Universiti Malaysia Perlis (UniMAP), 01000 Kangar, Perlis, Malaysia
Author to whom correspondence should be addressed.
Received: 1 March 2010 / Revised: 14 April 2010 / Accepted: 19 April 2010 / Published: 6 May 2010
(This article belongs to the Section Chemical Sensors)
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Presently, the quality assurance of agarwood oil is performed by sensory panels which has significant drawbacks in terms of objectivity and repeatability. In this paper, it is shown how an electronic nose (e-nose) may be successfully utilised for the classification of agarwood oil. Hierarchical Cluster Analysis (HCA) and Principal Component Analysis (PCA), were used to classify different types of oil. The HCA produced a dendrogram showing the separation of e-nose data into three different groups of oils. The PCA scatter plot revealed a distinct separation between the three groups. An Artificial Neural Network (ANN) was used for a better prediction of unknown samples.
Keywords: agarwood oil; e-nose; HCA; PCA; ANN; dimensionality reduction agarwood oil; e-nose; HCA; PCA; ANN; dimensionality reduction
This is an open access article distributed under the Creative Commons Attribution License (CC BY 3.0).

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MDPI and ACS Style

Hidayat, W.; Shakaff, A.Y.M.; Ahmad, M.N.; Adom, A.H. Classification of Agarwood Oil Using an Electronic Nose. Sensors 2010, 10, 4675-4685.

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