Classification of Agarwood Oil Using an Electronic Nose

Sensors

Wahyu Hidayat¹  Ali Yeon Md. Shakaff²  Mohd Noor Ahmad² 

[1] Sensor Technology and Applications Research Cluster, Universiti Malaysia Perlis (UniMAP), 01000 Kangar, Perlis, Malaysia;

关键词: agarwood oil;    e-nose;    HCA;    PCA;    ANN;    dimensionality reduction;   

DOI  :  10.3390/s100504675

来源: mdpi

【 摘 要 】

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.

【 授权许可】

CC BY   
© 2010 by the authors; licensee MDPI, Basel, Switzerland.