Weather based plant diseases forecasting using fuzzy logic

Integrated Pest Management (IPM) is a comprehensive approach that integrates a variety of practices to minimize the loss of farm productions due to pests and pathogens with optimum use of pesticides. Early detection of pest and its control is one of the aspects of IPM. Weather based forecasting is well accepted method for this. Various meteorological data like-temperature, humidity, leaf wetness duration (LWD) plays the vital roles in the growth of microorganism responsible for disease. Effective forecasting of such diseases on the basis of climate data can help the farmers to take timely actions to restrain the diseases. This can also rationalize the use of pesticides, which are one of the causes behind land pollution. Weather based forecasting system can be considered as a part of the Agricultural Decision Support System (ADSS) which is Knowledge Based System (KBS). This paper proposes fuzzy logic based structure for the plant disease forecasting system. It has been demonstrated that the proposed method can be implemented with minimum weather data like-temperature and humidity.