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Rule Based System for Safflower Disease Diagnosis and Treatment

Show simple item record Salman, Fatima M. Abu-Naser, Samy S. 8/28/2019 8/28/2019 2019-08-29T10:57:33Z 8/28/2019 2019-08-29T10:57:33Z 2019
dc.identifier.citation International Journal of Academic Engineering Research (IJAER),3(8), pp. 1-10 en_US
dc.description.abstract Background: Safflower is a highly branched, herbaceous, thistle-like annual plant. Any section of the safflower plant sections can suffering from a disease that weakens the ability to grow and eliminates its production. Therefore, in this paper will identify the pests and diseases present in safflower culture and detect the symptoms in each disease. Also images are showing the symptom form in this disease. Objectives: The main objective of this expert system is to obtain appropriate diagnosis of the disease. Methods: In this paper, the expert system is designed for the ability of agricultural engineers to detect and diagnose disease of safflower like as: alternaria blight, cercospora leaf spot, powdery mildew, head rot and wilt, mosaic, ramularia leaf spot, rust, wilt, and root rot. This system displays the disease symptoms, survival and spread, favorable conditions and image for each disease. Clips and Delphi expert system languages are used for designing and implementing the proposed expert system. Results: The expert system in the diagnosis of safflower diseases was evaluated by farmers and agricultural engineers and they were satisfied and accepted with its quality of performance. Conclusions: The expert system is easy for farmers and people have experience in the plant of safflower to detect and diagnosis the symptoms that may face this plant from several disease. en_US
dc.language.iso en_US en_US
dc.publisher IJARW en_US
dc.subject safflower diseases en_US
dc.subject Artificial Intelligence en_US
dc.subject Expert Systems en_US
dc.subject CLIPS language en_US
dc.subject Delphi en_US
dc.title Rule Based System for Safflower Disease Diagnosis and Treatment en_US
dc.type Article en_US

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