Next Article in Journal
Diode Laser Detection of Greenhouse Gases in the Near-Infrared Region by Wavelength Modulation Spectroscopy: Pressure Dependence of the Detection Sensitivity
Previous Article in Journal
State-of-the-Art Sensor Technology in Spain: Invasive and Non-Invasive Techniques for Monitoring Respiratory Variables
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 Physical Sensors)
View Full-Text   |   Download PDF [303 KB, uploaded 21 June 2014]   |   Browse Figures


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 which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

Share & Cite This Article

Further Mendeley | CiteULike
Export to BibTeX |
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.

View more citation formats

Related Articles

Article Metrics

For more information on the journal, click here


Cited By

[Return to top]
Sensors EISSN 1424-8220 Published by MDPI AG, Basel, Switzerland RSS E-Mail Table of Contents Alert