An Electronic Nose system for aromatic rice classification
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2011
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my.unimap-140702011-10-08T04:50:48Z An Electronic Nose system for aromatic rice classification Abu Hassan, Abdullah Abdul Hamid, Adom, Prof. Madya Dr. Ali Yeon, Md. Shakaff, Prof. Dr. Mansur N, Ahmad Ammar, Zakaria Nazifah, Ahmad Fikri Othman, Omar abdhamid@unimap.edu.my abuhassan@unimap.edu.my Artificial Neural Network (ANN) Aromatic rice classification Electronic nose Embedded system Hierarchical Cluster Analysis (HCA) Principal Component Analysis (PCA) Link to publisher's homepage at http://www.aspbs.com/ Aromatic rice is a variety of rice with good cooking qualities such as nice aroma and flavour. It is pricier because it is only suitable to be cultivated in regions with specific climatic and soil conditions. Presently, the aromatic rice quality classification uses either Isotope Ratio Mass Spectrometry (IRMS), Inductively Coupled Plasma Mass Spectrometry (ICP-MS), Near Infrared (NIR) or Deoxyribonucleic Acid (DNA). The rice aroma can also be classified using Gas Chromatography Mass Spectrometry (GC-MS), human panels or Electronic Nose (e-nose). The training for the human pan-els is lengthy, but the results are comparable to those using the said instrument analysis. However, the use of human panels has significant drawbacks such as fatigue, inconsistent and time consuming. This paper presents the development of a new cost-effective, portable, e-nose prototype with embedded data processing capabilities for aromatic rice classification. This system is intended to be used to assist the human panels. The e-nose utilises Hierarchical Cluster Analysis (HCA) and Principal Component Analysis (PCA) for data analysis. An Artificial Neural Network (ANN) was used to classify the unknown samples. The results show that the e-nose is able to successfully classify the aromatic rice with high accuracy. 2011-10-08T04:50:48Z 2011-10-08T04:50:48Z 2011-04 Article Sensor Letters, vol. 9 (2), 2011, pages 850-855 1546-198X http://www.ingentaconnect.com/content/asp/senlet/2011/00000009/00000002/art00082?token=00531897fb646b0e6720297d76347070237b60246c6a432c6b6d3f6a4b4b6e6e42576b6427388e7fc67 http://hdl.handle.net/123456789/14070 en American Scientific Publishers |
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English |
| topic |
Artificial Neural Network (ANN) Aromatic rice classification Electronic nose Embedded system Hierarchical Cluster Analysis (HCA) Principal Component Analysis (PCA) |
| spellingShingle |
Artificial Neural Network (ANN) Aromatic rice classification Electronic nose Embedded system Hierarchical Cluster Analysis (HCA) Principal Component Analysis (PCA) Abu Hassan, Abdullah Abdul Hamid, Adom, Prof. Madya Dr. Ali Yeon, Md. Shakaff, Prof. Dr. Mansur N, Ahmad Ammar, Zakaria Nazifah, Ahmad Fikri Othman, Omar An Electronic Nose system for aromatic rice classification |
| description |
Link to publisher's homepage at http://www.aspbs.com/ |
| author2 |
abdhamid@unimap.edu.my |
| author_facet |
abdhamid@unimap.edu.my Abu Hassan, Abdullah Abdul Hamid, Adom, Prof. Madya Dr. Ali Yeon, Md. Shakaff, Prof. Dr. Mansur N, Ahmad Ammar, Zakaria Nazifah, Ahmad Fikri Othman, Omar |
| format |
Article |
| author |
Abu Hassan, Abdullah Abdul Hamid, Adom, Prof. Madya Dr. Ali Yeon, Md. Shakaff, Prof. Dr. Mansur N, Ahmad Ammar, Zakaria Nazifah, Ahmad Fikri Othman, Omar |
| author_sort |
Abu Hassan, Abdullah |
| title |
An Electronic Nose system for aromatic rice classification |
| title_short |
An Electronic Nose system for aromatic rice classification |
| title_full |
An Electronic Nose system for aromatic rice classification |
| title_fullStr |
An Electronic Nose system for aromatic rice classification |
| title_full_unstemmed |
An Electronic Nose system for aromatic rice classification |
| title_sort |
electronic nose system for aromatic rice classification |
| publisher |
American Scientific Publishers |
| publishDate |
2011 |
| url |
http://dspace.unimap.edu.my/xmlui/handle/123456789/14070 |
| _version_ |
1643791133139009536 |
| score |
13.214268 |