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Intelligent electronic nose system for basal stem rot disease detection

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Main Authors: Marni Azira Markom, Ali Yeon, Md Shakaff, Abdul Hamid, Adom, Mohd Noor, Ahmad, Wahyu, Hidayat, Abu Hassan, Abdullah, N., Ahmad Fikrib
Format: Article
Language:English
Published: Elsevier 2009
Subjects:
Commercial electronic nose
ANN
Basal stem rot disease
Ganoderma boninense
Detectors > Design and construction
e-nose
Disease detectors
Online Access:http://dspace.unimap.edu.my/xmlui/handle/123456789/6338
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spelling my.unimap-63382009-08-14T04:16:00Z Intelligent electronic nose system for basal stem rot disease detection Marni Azira Markom Ali Yeon, Md Shakaff Abdul Hamid, Adom Mohd Noor, Ahmad Wahyu, Hidayat Abu Hassan, Abdullah N., Ahmad Fikrib Commercial electronic nose ANN Basal stem rot disease Ganoderma boninense Detectors -- Design and construction e-nose Disease detectors Link to publisher's homepage at www.elsevier.com The agricultural industry has been, for a long time, dependent upon human expertise in using odour for classification, grading, differentiating and discriminating different types of produce. Odour as a parameter of differentiation can also be used to determine the state of health of crops, although this is not favourable when dealing with detecting plant disease that may pose health threats to human beings. In addition to these, human experts may take years of training and can be inconsistent, as well as prone to fatigue. This paper presents a work conducted on utilising an electronic nose incorporating artificial intelligence to detect plant disease, specifically basal stem rot (BSR) disease that is caused by Ganoderma boninense fungus affecting oil palm plantations in South East Asia. This study used a commercially available electronic nose, Cyranose 320, as the front end sensors and artificial neural networks for pattern recognition. The odour samples were captured on site at Besout oil palm plantation, Perak, Malaysia, and the classification performed on a PC. The results showed that the system was able to differentiate healthy and infected oil palm tree using different odour parameters with a high rate of accuracy. 2009-07-07T04:17:32Z 2009-07-07T04:17:32Z 2009-05 Article Computers and Electronics in Agriculture, vol.66 (2), 2009, pages 140-146. 0168-1699 http://hdl.handle.net/123456789/6338 http://www.sciencedirect.com/science/journal/01681699 en Elsevier
institution Universiti Malaysia Perlis
building UniMAP Library
collection Institutional Repository
continent Asia
country Malaysia
content_provider Universiti Malaysia Perlis
content_source UniMAP Library Digital Repository
url_provider http://dspace.unimap.edu.my/
language English
topic Commercial electronic nose
ANN
Basal stem rot disease
Ganoderma boninense
Detectors -- Design and construction
e-nose
Disease detectors
spellingShingle Commercial electronic nose
ANN
Basal stem rot disease
Ganoderma boninense
Detectors -- Design and construction
e-nose
Disease detectors
Marni Azira Markom
Ali Yeon, Md Shakaff
Abdul Hamid, Adom
Mohd Noor, Ahmad
Wahyu, Hidayat
Abu Hassan, Abdullah
N., Ahmad Fikrib
Intelligent electronic nose system for basal stem rot disease detection
description Link to publisher's homepage at www.elsevier.com
format Article
author Marni Azira Markom
Ali Yeon, Md Shakaff
Abdul Hamid, Adom
Mohd Noor, Ahmad
Wahyu, Hidayat
Abu Hassan, Abdullah
N., Ahmad Fikrib
author_facet Marni Azira Markom
Ali Yeon, Md Shakaff
Abdul Hamid, Adom
Mohd Noor, Ahmad
Wahyu, Hidayat
Abu Hassan, Abdullah
N., Ahmad Fikrib
author_sort Marni Azira Markom
title Intelligent electronic nose system for basal stem rot disease detection
title_short Intelligent electronic nose system for basal stem rot disease detection
title_full Intelligent electronic nose system for basal stem rot disease detection
title_fullStr Intelligent electronic nose system for basal stem rot disease detection
title_full_unstemmed Intelligent electronic nose system for basal stem rot disease detection
title_sort intelligent electronic nose system for basal stem rot disease detection
publisher Elsevier
publishDate 2009
url http://dspace.unimap.edu.my/xmlui/handle/123456789/6338
_version_ 1643788556975472640
score 13.222552

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