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Session description
Pest management programs are based on several practices among which pest identification and population monitoring are very important ones. Even in recent years, developing new control methods has been the center of attention for many researchers and far less has been done to develop more effective detection and identification tools that are the first steps for any pest control program.
Like other organisms, cultivated plants produce many symptoms and signals in response to biotic stress (viz. pathogen infection or herbivore attack). Detecting these signals at an early stage could be a key factor for successful pest control. Plants emit a wide array of volatiles, some of which are novel, when infected with pathogens or attacked by pests. Emission of these volatiles is part of an indirect defense mechanism that can help the plant to attract predators and parasitoids that will attack pests. Pests themselves or their presence / feeding symptoms have been the center of attention for most current pest monitoring practices. However, in this project I suggest a novel approach to pest monitoring by shifting the attention from the pest to the plant. If interpreted correctly, plant driven volatile chemical signals can provide more accurate information about the health of the plant.
By using well-developed mechanical olfaction technology (known as the ‘electronic nose’), we can follow these chemical cues to locate crop problems before they become visible to the naked eye of human scouts. This could enable a grower to take early action, preventing pest or disease dispersion and further damage by controlling the problem right at the source. Electronic noses are special biosensors that are able to detect different types of volatile chemicals at various concentration
based on their sensitivity. These sensors are used mostly in food processing plants to measure the quality of meats and other food products. They also have many applications in military and antiterrorism practices (by detecting explosives).
The sensors can be programmed to detect specific volatiles and monitor changes in the concentration and quality of these volatiles. Electronic chemosensors are very sensitive and can detect chemicals in concentrations as low as parts per trillion. In order to use biosensors in pest control programs, we need to have a database of plant volatiles emitted in response to pests and diseases. First we should collect plant volatile chemicals, analyze them and select a set of compounds as indicators. After documenting the variability of indicator compounds emitted from clean and infested plants, we can select the best sensor(s) to detect these variations and report changes. Based on these reports and a database, initial pest problems can be localized and appropriate action taken.
It is a fact that plant driven volatiles might vary due to several biotic (pests, diseases) and abiotic (light,temperature, moisture, stress) factors. Therefore, the pest induced-plant volatile database will be designed in such a way that enables me to segregate pest induced signals from nonpest induced signals and also can provide a flexible and robust range of acceptable signals. Many techniques have been developed in recent years (i.e. Neural networks, fuzzy logic, discriminant analysis, data mining, pattern recognition, etc.) which allows creation of such intelligent databases.
