AMRAPALIKA: An expert system for the diagnosis of pests, diseases, and disorders in Indian mango

This paper emphasizes application of expert system in Indian fruiticulture and describes development of a rule-based expert system, using Expert System Shell for Text Animation (ESTA), for the diagnosis of the most common diseases occurring in Indian mango. The objective is to provide computer-based support for agricultural specialists or farmers. The proposed expert system makes diagnosis on the basis of response/responses of the user made against queries related to particular disease symptoms. The knowledge base of the system contains knowledge about symptoms and remedies of 14 diseases of Indian mango tree appearing during fruiting season and non-fruiting season. The picture base of the system contains pictures related to disease symptoms and are displayed along with the query of the system. The result given by the system has been found to be sound and consistent. und and consistent.

[1]  Jennifer Widom,et al.  An overview of production rules in database systems , 1993, The Knowledge Engineering Review.

[2]  Frank G. Zalom,et al.  CALEX/peaches, an expert system for the diagnosis of peach and nectarine disorders , 1989 .

[3]  James J. Ferguson,et al.  CITPATH: Diagnostic and Hypertext Software for Fungal Diseases of Citrus Foliage and Fruit , 1995 .

[4]  P. H. Heinemann,et al.  The Future Use and Development of Expert System Technology in Horticulture , 1993 .

[5]  Peter J. F. Lucas,et al.  Analysis of Notions of Diagnosis , 1998, Artif. Intell..

[6]  George Luger,et al.  Artificial Intelligence: Structures and Strategies for Complex Problem Solving (5th Edition) , 2004 .

[7]  M. Mahmoud,et al.  LIMEX: An Integrated Expert System for Lime Crop Management , 1995 .

[8]  Anna Hart,et al.  Knowledge acquisition for expert systems , 1988 .

[9]  A. A. Rafea.  Agricultural expert systems development in Egypt , 1994, Proceedings of International Conference on Expert Systems for Development.

[10]  R. Ploetz,et al.  Compendium of tropical fruit diseases , 1994 .

[11]  Bruce G. Buchanan,et al.  Understanding Artificial Intelligence , 1985 .

[12]  Peter Lucas,et al.  Symbolic diagnosis and its formalisation , 1997, The Knowledge Engineering Review.

[13]  P. H. Heinemann,et al.  PENN STATE APPLE ORCHARD CONSULTANT: DESIGN AND FUNCTION OF THE PEST MANAGEMENT MODULE , 1992 .

[14]  Raymond Reiter,et al.  A Theory of Diagnosis from First Principles , 1986, Artif. Intell..

[15]  Glenn H. Sullivan,et al.  An Expert System for Integrated Production Management in Muskmelon , 1992 .

[16]  Stephen R. Ruth,et al.  Expert Systems In Developing Countries: Practice And Promise , 1992 .

[17]  Raymond Reiter,et al.  Characterizing Diagnoses and Systems , 1992, Artif. Intell..

[18]  Dimitrios Sklavakis,et al.  Integrating Problem-Solving Methods into CYC , 1999, IJCAI.

[19]  Raymond J. Mooney,et al.  Inductive Learning For Abductive Diagnosis , 1994, AAAI.

[20]  Pietro Torasso,et al.  On the Relationship between Abduction and Deduction , 1991, J. Log. Comput..

[21]  Bruce G. Buchanan,et al.  The MYCIN Experiments of the Stanford Heuristic Programming Project , 1985 .

[22]  Edward H. Shortliffe,et al.  Rule Based Expert Systems: The Mycin Experiments of the Stanford Heuristic Programming Project (The Addison-Wesley series in artificial intelligence) , 1984 .

[23]  Richard E. Plant,et al.  Knowledge Based Systems in Agriculture , 1991 .