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Field Asymmetric Ion Mobility Spectrometry Based Plant Disease Detection: Intelligent Systems Approach
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Author(s): F. Zhang (School of Engineering, University of Warwick, UK), R. Ghaffari (School of Engineering, University of Warwick, UK), D. Iliescu (School of Engineering, University of Warwick, UK), E. Hines (School of Engineering, University of Warwick, UK), M. Leeson (School of Engineering, University of Warwick, UK)and R. Napier (Warwick HRI, University of Warwick, UK)
Copyright: 2011
Pages: 13
Source title:
Applied Signal and Image Processing: Multidisciplinary Advancements
Source Author(s)/Editor(s): Rami Qahwaji (University of Bradford, UK), Roger Green (University of Warwick, UK)and Evor L. Hines (University of Warwick, UK)
DOI: 10.4018/978-1-60960-477-6.ch006
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Abstract
This chapter presents the initial studies on the detection of two common diseases and pests, the powdery mildew and spider mites, on greenhouse tomato plants by measuring the chemical volatiles emitted from the tomato plants as the disease develops using a Field Asymmetric Ion Mobility Spectrometry (FAIMS) device. The processing on the collected FAIMS measurements using PCA shows that clear increment patterns can be observed on all the experimental plants representing the gradual development of the diseases. Optimisation on the number of dispersion voltages to be used in the FAIMS device shows that reducing the number of dispersion voltages by a factor up to 10, preserves the key development patterns perfectly, though the amplitudes of the new patterns are reduced significantly.
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