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Development of electronic nose for classification of aromatic herbs using Artificial Intelligent techniques

In normal practice, herbs identification is done mainly by botanists. However, it is difficult for a botanist to recognize herbs based on aroma measurement for species under the same family because they may have almost the same aromas. Moreover, several factors might influence the accuracy of the hu...

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Main Authors: Che Soh, Azura, Mohamad Radzi, Nur Fadzilah, Mohamad Yusof, Umi Kalsom, Ishak, Asnor Juraiza, Hassan, Mohd Khair
Format: Article
Language:English
Published: Taylor's University 2018
Online Access:http://psasir.upm.edu.my/id/eprint/72258/1/Development%20of%20electronic%20nose%20.pdf
http://psasir.upm.edu.my/id/eprint/72258/
http://jestec.taylors.edu.my/V13Issue10.htm
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spelling my.upm.eprints.722582020-04-26T16:01:19Z http://psasir.upm.edu.my/id/eprint/72258/ Development of electronic nose for classification of aromatic herbs using Artificial Intelligent techniques Che Soh, Azura Mohamad Radzi, Nur Fadzilah Mohamad Yusof, Umi Kalsom Ishak, Asnor Juraiza Hassan, Mohd Khair In normal practice, herbs identification is done mainly by botanists. However, it is difficult for a botanist to recognize herbs based on aroma measurement for species under the same family because they may have almost the same aromas. Moreover, several factors might influence the accuracy of the human olfactory system as a sensory panel such as physical and mental conditions. Meanwhile, non-human factors might involve various experimental exercises that are timeconsuming, less efficient and costly. Therefore, a small portable electronic nose that is easy to operate is proposed in this research. The herb leaves were blended as a mechanism in sample preparation was found as a preeminent procedure to overcome the drawback of the existing system. The emphasis on the ability of proposed electronic nose enhance with herbs recognition algorithm in this project was to distinctive odour pattern of the herbs leaves from three families group. Two classification methods, Artificial Neural Network (ANN) and Adaptive Neuro-Fuzzy Inference System (ANFIS) were used in order to investigate the performance of classification accuracy for this E-nose system. From the results, the developed E-Nose with both Artificial Intelligence (AI) techniques had performed well in distinguishing twelves herbs species. However, E-nose with ANFIS gives 94.8% percentage of accuracy higher than E-nose with ANN as 91.7% of accuracy. As a conclusion, the proposed E-nose system with AI technique application can classify the aromatic herbs species successfully. Taylor's University 2018-10 Article PeerReviewed text en http://psasir.upm.edu.my/id/eprint/72258/1/Development%20of%20electronic%20nose%20.pdf Che Soh, Azura and Mohamad Radzi, Nur Fadzilah and Mohamad Yusof, Umi Kalsom and Ishak, Asnor Juraiza and Hassan, Mohd Khair (2018) Development of electronic nose for classification of aromatic herbs using Artificial Intelligent techniques. Journal of Engineering Science and Technology, 13 (10). 3043 - 3057. ISSN 1823-4690 http://jestec.taylors.edu.my/V13Issue10.htm
institution Universiti Putra Malaysia
building UPM Library
collection Institutional Repository
continent Asia
country Malaysia
content_provider Universiti Putra Malaysia
content_source UPM Institutional Repository
url_provider http://psasir.upm.edu.my/
language English
description In normal practice, herbs identification is done mainly by botanists. However, it is difficult for a botanist to recognize herbs based on aroma measurement for species under the same family because they may have almost the same aromas. Moreover, several factors might influence the accuracy of the human olfactory system as a sensory panel such as physical and mental conditions. Meanwhile, non-human factors might involve various experimental exercises that are timeconsuming, less efficient and costly. Therefore, a small portable electronic nose that is easy to operate is proposed in this research. The herb leaves were blended as a mechanism in sample preparation was found as a preeminent procedure to overcome the drawback of the existing system. The emphasis on the ability of proposed electronic nose enhance with herbs recognition algorithm in this project was to distinctive odour pattern of the herbs leaves from three families group. Two classification methods, Artificial Neural Network (ANN) and Adaptive Neuro-Fuzzy Inference System (ANFIS) were used in order to investigate the performance of classification accuracy for this E-nose system. From the results, the developed E-Nose with both Artificial Intelligence (AI) techniques had performed well in distinguishing twelves herbs species. However, E-nose with ANFIS gives 94.8% percentage of accuracy higher than E-nose with ANN as 91.7% of accuracy. As a conclusion, the proposed E-nose system with AI technique application can classify the aromatic herbs species successfully.
format Article
author Che Soh, Azura
Mohamad Radzi, Nur Fadzilah
Mohamad Yusof, Umi Kalsom
Ishak, Asnor Juraiza
Hassan, Mohd Khair
spellingShingle Che Soh, Azura
Mohamad Radzi, Nur Fadzilah
Mohamad Yusof, Umi Kalsom
Ishak, Asnor Juraiza
Hassan, Mohd Khair
Development of electronic nose for classification of aromatic herbs using Artificial Intelligent techniques
author_facet Che Soh, Azura
Mohamad Radzi, Nur Fadzilah
Mohamad Yusof, Umi Kalsom
Ishak, Asnor Juraiza
Hassan, Mohd Khair
author_sort Che Soh, Azura
title Development of electronic nose for classification of aromatic herbs using Artificial Intelligent techniques
title_short Development of electronic nose for classification of aromatic herbs using Artificial Intelligent techniques
title_full Development of electronic nose for classification of aromatic herbs using Artificial Intelligent techniques
title_fullStr Development of electronic nose for classification of aromatic herbs using Artificial Intelligent techniques
title_full_unstemmed Development of electronic nose for classification of aromatic herbs using Artificial Intelligent techniques
title_sort development of electronic nose for classification of aromatic herbs using artificial intelligent techniques
publisher Taylor's University
publishDate 2018
url http://psasir.upm.edu.my/id/eprint/72258/1/Development%20of%20electronic%20nose%20.pdf
http://psasir.upm.edu.my/id/eprint/72258/
http://jestec.taylors.edu.my/V13Issue10.htm
_version_ 1665895994498220032
score 13.211869

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