Ghaffari, Reza, Zhang, Fu, Ph.D., Iliescu, Daciana, Hines, Evor L., Leeson, Mark S. and Napier, Richard M. (2011) The analysis of plant’s organic volatiles compounds with electronic nose and pattern recognition techniques. In: Qahwaji, Rami and Green, Roger J. and Hines, Evor L., (eds.) Applied Signal and Image Processing: Multidisciplinary Advancements. Hershey, PA, U.S.A: IGI Global, pp. 115-126. ISBN 978-1-6096-0477-6

Abstract

In this chapter, the authors introduce the principles of some of the most widely used supervised and unsupervised Pattern Recognition (PR) techniques and assess behaviour and performances. A dataset acquired from a set of experiments conducted at University of Warwick is employed to construct a case study in which the techniques will be applied. The chapter will also evaluate the integration of PR methods with an Electronic Nose (EN) device to develop and implement a plant diagnosis tool based on discriminating the Organic Volatile Compounds (VOC) released by plants when attacked by pest. The chapter concludes with a performance comparison and a brief discussion of how an appropriate PR technique can be coupled with an EN to produce a greenhouse plant pest and disease diagnosis system for day-to-day utilisation. Some consideration of further work is also presented.

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