An expert system for identification of nutrients deficiency/disorder and their management advisories in Mango (Mangifera indica, L.)

Abstract

When a nutrient deficiency/disorder symptom starts to become visible in a commercial crop, an accurate identification is necessary to support its scientific management/control. In some cases diagnosis is easy and orchardist can easily identify however in others, it needs expert opinion. Diagnosing nutrients disorder and deficiency symptoms in mango requires substantial expertise. The expertise of an expert in a particular domain is not generally available on demand. It is also difficult to retain expertise. Therefore, to make expertise more easily accessible to the mango orchardists and retain it, expert system software on nutrients disorder/deficiency in mango has been developed. Out of several nutrients viz., potassium, boron, manganese, zinc and copper, etc., are reported to be in short supply for optimum plant growth and productivity of mango in India. The expert system is developed by using forward chaining method of reasoning to reach the conclusion. The system is developed using programming language instead of using costly expert system shell software. After diagnosing the deficiency or disorder symptoms, the system advises the scientific management options. Therefore, this expert system will compliment the human expert in advisory on management aspect of nutrients deficiency/disorder. This expert system is menu based user friendly software that starts diagnosis from a question-answer based session and reconfirmation of symptoms based on visual symptoms of affected images. This reconfirmation session based on visual symptoms of affected part of plant ensures high level of diagnosis accuracy