An Electronic Nose system for aromatic rice classification

A. H. Abdullah, A. H. Adorn, A. Y Md Shakaff, M. N. Ahmad, A. Zakaria, N. A. Fikri, O. Omar

Research output: Contribution to journalArticle

8 Citations (Scopus)

Abstract

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.

Original languageEnglish
Pages (from-to)850-855
Number of pages6
JournalSensor Letters
Volume9
Issue number2
DOIs
Publication statusPublished - Apr 2011
Externally publishedYes

Fingerprint

rice
electronics
Mass spectrometry
Inductively coupled plasma mass spectrometry
Flavors
Cooking
Cluster analysis
mass spectroscopy
Gas chromatography
Principal component analysis
Isotopes
cluster analysis
DNA
inductively coupled plasma mass spectrometry
isotope ratios
Fatigue of materials
gas chromatography
principal components analysis
Infrared radiation
Neural networks

Keywords

  • ANN
  • Aromatic rice classification
  • Electronic nose
  • Embedded system
  • HCA
  • PCA

ASJC Scopus subject areas

  • Electrical and Electronic Engineering
  • Atomic and Molecular Physics, and Optics

Cite this

Abdullah, A. H., Adorn, A. H., Shakaff, A. Y. M., Ahmad, M. N., Zakaria, A., Fikri, N. A., & Omar, O. (2011). An Electronic Nose system for aromatic rice classification. Sensor Letters, 9(2), 850-855. https://doi.org/10.1166/sl.2011.1629

An Electronic Nose system for aromatic rice classification. / Abdullah, A. H.; Adorn, A. H.; Shakaff, A. Y Md; Ahmad, M. N.; Zakaria, A.; Fikri, N. A.; Omar, O.

In: Sensor Letters, Vol. 9, No. 2, 04.2011, p. 850-855.

Research output: Contribution to journalArticle

Abdullah, AH, Adorn, AH, Shakaff, AYM, Ahmad, MN, Zakaria, A, Fikri, NA & Omar, O 2011, 'An Electronic Nose system for aromatic rice classification', Sensor Letters, vol. 9, no. 2, pp. 850-855. https://doi.org/10.1166/sl.2011.1629
Abdullah AH, Adorn AH, Shakaff AYM, Ahmad MN, Zakaria A, Fikri NA et al. An Electronic Nose system for aromatic rice classification. Sensor Letters. 2011 Apr;9(2):850-855. https://doi.org/10.1166/sl.2011.1629
Abdullah, A. H. ; Adorn, A. H. ; Shakaff, A. Y Md ; Ahmad, M. N. ; Zakaria, A. ; Fikri, N. A. ; Omar, O. / An Electronic Nose system for aromatic rice classification. In: Sensor Letters. 2011 ; Vol. 9, No. 2. pp. 850-855.
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