Intelligent Classification of Cocoa Bean using E-nose

Authors

  • Nur Amanda Nazli Faculty of Manufacturing and Mechatronic Engineering Technology, Universiti Malaysia Pahang
  • Muhammad Sharfi Najib Faculty of Manufacturing and Mechatronic Engineering Technology, Universiti Malaysia Pahang
  • Suhaimi Mohd Daud Faculty of Electrical and Electronic Engineering Technology, Universiti Malaysia Pahang, 26600 Pahang, Malaysia.
  • Mujahid Mohammad Faculty of Electrical and Electronic Engineering Technology, Universiti Malaysia Pahang, 26600 Pahang, Malaysia.
  • Zainul Baharum Division of Biotechnology, Cocoa Innovation &Technology Centre, Malaysian Cocoa Board, NegeriSembilan, Malaysia
  • Mohamed Yusof Ishak Division of Regulatory and Quality Control, Cocoa Innovation &Technology Centre, Malaysian Cocoa Board, Negeri Sembilan, Malaysia

DOI:

https://doi.org/10.15282/mekatronika.v2i2.6747

Keywords:

Cocoa bean, Chocolate, E-nose, CBR

Abstract

Cocoa bean (Theobrama cacao) is an essential raw material in the manufacture of chocolate, and their classification is crucial for the synthesis of good chocolate flavour. Cocoa beans appear to be very similar to one another when visualised. Hence, an electronic device named the electronic nose (E-Nose) is used to classify the odor of cocoa beans to give the best cocoa bean quality. E-nose is a set of an array of chemical sensors used to sense the gas vapours produced by the cocoa bean and the raw data collected was kept in Microsoft Excel, and the classification took place in Octave. They then underwent normalisation technique to increase classification accuracy, and their features were extracted using mean calculation. The features were classified using CBR, and the similarity value is obtained. The results show that CBR's classification accuracy, specificity and sensitivity are all 100%.

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Published

2020-12-13 — Updated on 2021-11-19

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How to Cite

[1]
N. A. Nazli, M. S. Najib, S. Mohd Daud, M. . Mohammad, Z. Baharum, and M. Y. . Ishak, “Intelligent Classification of Cocoa Bean using E-nose”, Mekatronika: J. Intell. Manuf. Mechatron., vol. 2, no. 2, pp. 28–35, Nov. 2021.

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Original Article