Feasibility study of utilising electronic nose to detect BSR disease in oil palm plantation

The agricultural industry has been, for a long time, dependent upon human expertise to detect plant disease. However, human experts may take years of training and can be inconsistent, as well as prone to fatigue. Presented in this thesis is the work conducted on utilising electronic nose incorpo...

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Main Author:	Marni Azira, Markom
Format:	Thesis
Language:	English
Subjects:	Basal stem rot (BSR) Electronic nose Odour Plant disease Oil palm industry Artificial neural networks (ANN) Ganoderma boninense
Online Access:	http://dspace.unimap.edu.my:80/xmlui/bitstream/123456789/9876/1/Page%201-24.pdf http://dspace.unimap.edu.my:80/xmlui/bitstream/123456789/9876/2/Full%20Text.pdf
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id	my-unimap-9876
record_format	uketd_dc
spelling	my-unimap-98762010-10-18T12:27:42Z Feasibility study of utilising electronic nose to detect BSR disease in oil palm plantation Marni Azira, Markom The agricultural industry has been, for a long time, dependent upon human expertise to detect plant disease. However, human experts may take years of training and can be inconsistent, as well as prone to fatigue. Presented in this thesis is the work conducted on utilising electronic nose incorporating artificial intelligence to detect plant malaise, specifically, basal stem rot (BSR) disease that is caused by Ganoderma boninense, a type of fungi affecting oil palm plantations in South East Asia. A commercial electronic nose, Cyranose 320, was used as the front-end sensors with artificial neural networks trained using Levenberg-Marquardt algorithm employed for decision making. For the first stage, a study on Cyranose 320 embedded pattern recognitions and artificial neural networks (ANNs) was conducted using a few types of essences. This stage confirmed that the ANNs is better than the embedded pattern recognitions in terms of accuracy and hence should be used for the next experiments. The second stage involved the Ganoderma boninense fruiting bodies detection in laboratory and oil palm plantation. This stage proved that the fungi odour can be detected after being tested using a few types of odour parameter. The next stage is to discriminate the healthy and non-healthy oil palm trunk in the plantation. The conducted work indicates that the combination of the electronic nose and ANNs has the ability to discriminate the infected trunk. The findings of the work were also used to develop an in-house low cost electronic nose to support further fundamental study and implementations. As a conclusion, this work confirms that it is feasible to utilise the electronic nose and ANNs to detect and discriminate the BSR disease both in the laboratory and in the plantation. Universiti Malaysia Perlis 2009 Thesis en http://dspace.unimap.edu.my/123456789/9876 http://dspace.unimap.edu.my:80/xmlui/bitstream/123456789/9876/3/license.txt 8a4206bd6f1c81d185902b99e5b7f053 http://dspace.unimap.edu.my:80/xmlui/bitstream/123456789/9876/1/Page%201-24.pdf 67f15ae66b56419c2bdbe699c28d63e3 http://dspace.unimap.edu.my:80/xmlui/bitstream/123456789/9876/2/Full%20Text.pdf a1b0cc839c89c45d013279ff85197420 Basal stem rot (BSR) Electronic nose Odour Plant disease Oil palm industry Artificial neural networks (ANN) Ganoderma boninense School of Computer and Communication Engineering
institution	Universiti Malaysia Perlis
collection	UniMAP Institutional Repository
language	English
topic	Basal stem rot (BSR) Electronic nose Odour Plant disease Oil palm industry Artificial neural networks (ANN) Ganoderma boninense
spellingShingle	Basal stem rot (BSR) Electronic nose Odour Plant disease Oil palm industry Artificial neural networks (ANN) Ganoderma boninense Marni Azira, Markom Feasibility study of utilising electronic nose to detect BSR disease in oil palm plantation
description	The agricultural industry has been, for a long time, dependent upon human expertise to detect plant disease. However, human experts may take years of training and can be inconsistent, as well as prone to fatigue. Presented in this thesis is the work conducted on utilising electronic nose incorporating artificial intelligence to detect plant malaise, specifically, basal stem rot (BSR) disease that is caused by Ganoderma boninense, a type of fungi affecting oil palm plantations in South East Asia. A commercial electronic nose, Cyranose 320, was used as the front-end sensors with artificial neural networks trained using Levenberg-Marquardt algorithm employed for decision making. For the first stage, a study on Cyranose 320 embedded pattern recognitions and artificial neural networks (ANNs) was conducted using a few types of essences. This stage confirmed that the ANNs is better than the embedded pattern recognitions in terms of accuracy and hence should be used for the next experiments. The second stage involved the Ganoderma boninense fruiting bodies detection in laboratory and oil palm plantation. This stage proved that the fungi odour can be detected after being tested using a few types of odour parameter. The next stage is to discriminate the healthy and non-healthy oil palm trunk in the plantation. The conducted work indicates that the combination of the electronic nose and ANNs has the ability to discriminate the infected trunk. The findings of the work were also used to develop an in-house low cost electronic nose to support further fundamental study and implementations. As a conclusion, this work confirms that it is feasible to utilise the electronic nose and ANNs to detect and discriminate the BSR disease both in the laboratory and in the plantation.
format	Thesis
author	Marni Azira, Markom
author_facet	Marni Azira, Markom
author_sort	Marni Azira, Markom
title	Feasibility study of utilising electronic nose to detect BSR disease in oil palm plantation
title_short	Feasibility study of utilising electronic nose to detect BSR disease in oil palm plantation
title_full	Feasibility study of utilising electronic nose to detect BSR disease in oil palm plantation
title_fullStr	Feasibility study of utilising electronic nose to detect BSR disease in oil palm plantation
title_full_unstemmed	Feasibility study of utilising electronic nose to detect BSR disease in oil palm plantation
title_sort	feasibility study of utilising electronic nose to detect bsr disease in oil palm plantation
granting_institution	Universiti Malaysia Perlis
granting_department	School of Computer and Communication Engineering
url	http://dspace.unimap.edu.my:80/xmlui/bitstream/123456789/9876/1/Page%201-24.pdf http://dspace.unimap.edu.my:80/xmlui/bitstream/123456789/9876/2/Full%20Text.pdf
_version_	1747836780532465664

Feasibility study of utilising electronic nose to detect BSR disease in oil palm plantation

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