Ghaffari, Reza, Zhang, Fu, Iliescu, Daciana, Hines, Evor, Leeson, Mark S., Napier, R. and Clarkson, John P. (2010) Early detection of diseases in tomato crops : an electronic nose and intelligent systems approach. In: 2010 International Joint Conference on Neural Networks IJCNN 2010, Barcelona , 18-23 July 2010. Published in: IEEE International Conference on Neural Networks. Proceedings pp. 1-6. doi:10.1109/IJCNN.2010.5596535 ISSN 1098-7576.

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Abstract

Sensor arrays also known as Electronic Noses (ENs) have been used to analyse the Volatile Organic Compounds (VOCs) of both healthy and infected tomato (Solanum lycopersicum) crops. Statistical and intelligent systems techniques were employed to process the data collected by an EN. Principal Component Analysis (PCA), K-Means clustering and Fuzzy C-Mean (FCM) clustering were applied to visualise any clusters within the dataset. Furthermore, Multi-Layer Perceptron (MLP), Learning Vector Quantization (LVQ) and Radial Basis Function (RBF) based Artificial Neural Network (ANNs) were used to learn to classify and hence categorise the datasets. Using the RBF, MLP and LVQ techniques we achieved 94, 96 and 98% classification accuracy for the healthy, powdery mildew (Oidium lycopersicum) and spider mite infected plants respectively. From these results it is evident that EN is capable of discriminating between the healthy and artificially infected tomato plants and hence may be deployed as a potential early disease detection tool for tomato crops in commercial greenhouses.

Item Type:	Conference Item (Paper)
Subjects:	S Agriculture > SB Plant culture T Technology > TP Chemical technology
Divisions:	Faculty of Science, Engineering and Medicine > Engineering > Engineering Faculty of Science, Engineering and Medicine > Science > Life Sciences (2010- )
Library of Congress Subject Headings (LCSH):	Electrochemical sensors, Plant diseases -- Diagnosis, Tomatoes -- Diseases and pests, Intelligent control systems, Volatile organic compounds
Journal or Publication Title:	IEEE International Conference on Neural Networks. Proceedings
Publisher:	IEEE
ISSN:	1098-7576
Book Title:	The 2010 International Joint Conference on Neural Networks (IJCNN)
Official Date:	2010
Dates:	Date Event 2010 Published
Page Range:	pp. 1-6
DOI:	10.1109/IJCNN.2010.5596535
Status:	Peer Reviewed
Publication Status:	Published
Access rights to Published version:	Restricted or Subscription Access
Conference Paper Type:	Paper
Title of Event:	2010 International Joint Conference on Neural Networks IJCNN 2010
Type of Event:	Conference
Location of Event:	Barcelona
Date(s) of Event:	18-23 July 2010

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