Decision Support System “Crop-9-DSS“ for Identified Crops
Commenced in January 2007
Frequency: Monthly
Edition: International
Paper Count: 32870
Decision Support System “Crop-9-DSS“ for Identified Crops

Authors: Ganesan V.


Application of Expert System in the area of agriculture would take the form of Integrated Crop Management decision aids and would encompass water management, fertilizer management, crop protection systems and identification of implements. In order to remain competitive, the modern farmer often relies on agricultural specialists and advisors to provide information for decision-making. An expert system normally composed of a knowledge base (information, heuristics, etc.), inference engine (analyzes knowledge base), and end user interface (accepting inputs, generating outputs). Software named 'CROP-9-DSS' incorporating all modern features like, graphics, photos, video clippings etc. has been developed. This package will aid as a decision support system for identification of pest and diseases with control measures, fertilizer recommendation system, water management system and identification of farm implements for leading crops of Kerala (India) namely Coconut, Rice, Cashew, Pepper, Banana, four vegetables like Amaranthus, Bhindi, Brinjal and Cucurbits. 'CROP-9-DSS' will act as an expert system to agricultural officers, scientists in the field of agriculture and extension workers for decision-making and help them in suggesting suitable recommendations.

Keywords: Diagnostic, inference engine, knowledge base and user interface.

Digital Object Identifier (DOI):

Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 3029


[1] D.A. Waterman. 1986. A guide to expert systems. Addison-Wesley, Reading, MA.
[2] N. Haie and R.W. Irwin. 1988. Diagnostic expert systems for land drainage decisions. Irrig. Drain. Syst. 2(2): 139-146.
[3] O. W. Morgan, , M.J. McGregor, M. Richards and K.E. Oskouri. 1989. SELECT: An expert system shell for selecting amongst decision or management alternatives. Agric. Syst., 31: 97-110.
[4] I. Broner, J.P. King and A. Nevo. 1990. Structured induction for agricultural expert systems knowledge acquisition. Comput. Electron. Agric. 5: 87-99.
[5] A. Nevo and I. Amir. 1991. CROPLOT : An expert system for determining the suitability of crops to plots. Agric. Syst., 37: 225-241.
[6] R.E. Plant, R.D. Horrocks, D.W. Grimes and L.J. Zelinski. 1992. CALEX / Cotton: An integrated expert system application for irrigation scheduling. American Society of Agricultural Engineers. 35(6): 1833 - 1838.
[7] R. Srinivasan, B.A. Engel and G. N. Pandyal 1991. Expert system for irrigation management (ESIM). Agric. Syst., 36: 297-314.
[8] K. Elango, R. Honert, C.N. Kumar, and V. Suresh, 1992. PC - based management game for irrigated farming. Micro Comp. Civil Engg. 7: 243-256.
[9] R.M. Crassweller, J.W. Travis, P.H. Heinsmann and E.G. Rajotte. 1993. The future use and development of expert system technology in Horticulture. Hort. Technology. 3: 203-204.
[10] S. Mohan and N. Arumugam 1997. Expert system applications in irrigation management: an overview. 17: 263-280.
[11] V. Ganesan. 2004. Agricultural expert system for the diagnosis of pests and diseases, 15th International Workshop on Artificial Intelligence in Agriculture AIA-2004, IFAC, Cairo, Egypt, March 8-10, pp. 107-110.