Tomato Plant Health Monitoring: An Electronic Nose Approach

Tomato Plant Health Monitoring: An Electronic Nose Approach

Fu Zhang (University of Warwick, UK), D. D. Iliescu (University of Warwick, UK), Evor L. Hines (University of Warwick, UK) and Mark S. Leeson (University of Warwick, UK)
Copyright: © 2011 |Pages: 18
DOI: 10.4018/978-1-61520-915-6.ch009
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Electric noses (e-noses), taking their inspiration from the human olfactory system, have been extensively used in food quality control and human disease monitoring. This chapter presents the e-nose as a potential candidate for health monitoring and disease and pest detection on tomato plants. Two common problems in greenhouse tomatoes, namely powdery mildew and spider mites, are considered. An experimental arrangement is described based on a commercial 13-sensor e-nose where tomato plants are grown in an isolated, controlled environment inside a greenhouse. Attention is paid to the preliminary results of data post-processing using two different techniques. First, Principal Component Analysis is employed and demonstrates clear evolution of the components as the plants develop disease or infestation. Subsequently, Grey System Theory enables the identification of clear groupings in the sensor responses and thus the reduction of the model, producing stronger trend differences in the Principal Component between healthy and unhealthy plants. The results, although preliminary, show that the e-nose with appropriate data post-processing is a promising approach to monitoring the development of tomato plant diseases and infestations.
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The prediction of crop yields and the detection of plant damage or infestation need methods to collect data regarding plant health in addition to diagnosis and analysis tools. The detection and recognition of chemical substances produced by plants thus form suitable approaches for greenhouse use. Volatile organic compounds (VOCs) are emitted by plants when they are attacked by pests or disease and VOC emission has been investigated from many plant species (Kesselmeier & Staudt, 2004). Plants emit VOCs that are specific to the type of attack to combat the threat (Frost et al., 2008) and VOCs are major players in the interactions exchanges between plants and both herbivores and pathogens. The composition of VOCs emitted by plants depends on the mode of damage and they are produced by a wide range of physiological processes (Maffei, 2010).

There are two well known artificial technologies mimicking the human olfaction system, namely, chemical analysis and e-noses. Each of these technologies has its own advantages and disadvantages. Chemical analysis is able to identify and determine the accurate quantitative information of various chemical compounds. Gas chromatography – mass spectrometry (GC-MS) is one of the most important chemical analysis tools in odor analysis. GC-MS can separate many chemical components from a complex mixture of volatiles. The major problems of GC-MS are time and costs. GC-MS devices are expensive and the analysis process of a sample may take up to several hours. Thus, GC-MS cannot be used in real-time applications. E-noses, also known as gas sensors arrays, overcome the processing shortage of GC-MS, they are rapid, simple and inexpensive compared to GC-MS (Zhang et al., 2007). This chapter presents work on the development of powdery mildew infection and spider mite infestation on tomato plants, monitored using an e-nose. It is shown that an e-nose can be used to examine disease progression in tomatoes and detect the occurrence of diseases at an early stage.

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