Automated Mango Fruit Grading System Using Fuzzy Logic

Yeong Kin Teoh, Suzanawati Abu Hasan, Suraiya Sauddin@Sa’duddin


This paper concentrates on the size of mango fruit. Mangoes grading by humans in current agricultural industry are subjective, inconsistent and inefficient because there is an individual difference in visual inspecting which is affected by environment, physical and psychological conditions. In this paper, fuzzy logic is used to create a novel grading method. A membership function and fuzzy rules are generated from training instances based on minimum entropy formulas. Computer and Red Green and Blue (RGB) fiber optic sensor are used to examine and clarify data corresponding to human judgment and intelligence. A total of 77.78% of accuracy is achevied under the proposed method which capable of differentiating three different grades of mango. This paper offers a competent practice and capable to be applied to improve and standardize the current mango fruit grading system.

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Journal of Agricultural Science   ISSN 1916-9752 (Print)   ISSN 1916-9760 (Online)  E-mail:

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