Development of Multimedia Fuzzy Based Diagnostic Expert System for Integrated Disease Management in Chickpea
Sonal Dubey1, R. K. Pandey2, S. S. Gautam3
1Smt. Sonal Dubey, Research Scholar, Faculty of Science & Environment Mahatma Gandhi Gramodaya Vishwa Vidyalaya Chitrakoot Satna, India.
2Dr.R.K. Pandey, Reader, University Institute of Computer Science and Applications (UICSA) Rani Durgavati Vishwa Vidyalaya, Jabalpur (M. P.), India.
3Dr.S.S. Gautam Reader, Faculty of Science & Environment Mahatma Gandhi Gramodaya Vishwa Vidyalaya Chitrakoot Satna., India.

Manuscript received on January 05, 2014. | Revised Manuscript received on January  11, 2014. | Manuscript published on January 15, 2014. | PP: 16-20 | Volume-2 Issue-2, January 2014. | Retrieval Number: B0572012214/2014©BEIESP
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Abstract: One of the most important branches of Artificial Intelligence are the expert systems. Expert systems are application oriented. . An expert system is a computer application that solves complicated problems that would otherwise require extensive human expertise. It can be operated by a less educated person or a layman in a particular field of knowledge. It uses the knowledge of the domain expert to form rules to assist in decision making depending on the inputs given by the user. Chickpea (Cicer arietinum L) is the second most important cool season legume crop. It is mainly grown in tropical, sub-tropical and temperate regions, as rainfed in semi arid regions. there is a tremendous scope for increasing the productivity of chickpea by reducing the production losses thereof caused by serious insect pests and diseases causing up to 100 % losses during epidemic years. . For better management of the pest, effective integrated disease and insect management techniques have to be followed for increasing crop production. Expert systems play an important role in supporting farmers to practice effective integrated disease and insect management techniques and taking decisions on crop protection where the experts are not available. Since Fuzzy logic can effectively handle vagueness and inperfect data, it is widely used in diagnosis of diseases in agriculture. This paper describes the fuzzy expert system for integrated disease management in chickpea taking into account the environmental factors like soil moisture, temperature, soil pH, relative humidity in the first step. In the second step identification based on symptoms and photos are taken into consideration and a conclusion is drawn about the diseases attacking the crop.
Keywords: Chickpea , environmental factors fuzzy expert system, integrated disease management.