Graduate Thesis Or Dissertation
 

Development of an expert system for irrigation and fertilization management in the Pacific Northwest

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https://ir.library.oregonstate.edu/concern/graduate_thesis_or_dissertations/d791sk658

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  • Recent advances in computer technology have made possible the development of expert systems. Expert systems are computer programs that perform at the level of a human expert. Expert systems can help integrate and apply diverse sources of information and expertise to problems of integrated crop management. A prototype Crop Management eXpert (CMX) system has been developed. The primary goal of CMX is to provide recommendations on optimal irrigation and fertilization scheduling for wheat production in the Pacific Northwest. This system can be used by farmers and/or extension agents. OUS II Shell has been used as a implementation tool. To build this rule - based expert system, a development strategy, commonly used in the construction of expert systems, consisting of 1 ) identification; 2) conceptualization; 3) formalization; 4) implementation; and 5) testing was applied. CMX is composed of modules for irrigation and fertilization management. For irrigation management, CMX is mainly involved in the irrigation scheduling which is the major part of irrigation management. Irrigation strategies have been applied in irrigation decision making. For each strategy, timing criteria which generally consist of management allowed depletion, soil water potential, leaf water potential, and water stress indices have been used. The system provides farmers with irrigation scenarios which determine when and how much water to apply. CMX represents an integration of conventional computing and expert systems technology designed to provide expert recommendations enabling farmers to obtain the best return on their water and fertilizer investment. For fertilization management, a variety of variables have been taken into considered. Crop growth stages, soil moisture, nutrient analysis, protein requirement, and application methods are important factors for the fertilizer decision making. Several constraints have been used in optimal fertilizer advice. CMX can focus only on relevant information, thus reducing the problem space to a manageable size and significantly, improving the efficiency of the system. The facility of the expert system to explain the decision-making process enables users to better understand the underlying assumptions, facts, and reasoning used to generate recommendations. The CMX prototype demonstrates the feasibility of employing expert systems technology in agricultural applications. CMX has been validated and evaluated. The survey results showed that this prototype was successful in capturing domain experts' knowledge as rules and providing advice on the irrigation and fertilization management for wheat.
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file details CaoWeidong1993.pdf 2017-08-20 Pubblico Scaricare