Ripening

Grading (engineering)

Ripeness

Mathematics

RGB color model

Biology

Categorization

Civil engineering

Engineering

Horticulture

Artificial intelligence

Computer science

Fuzzy logic

Researchers World – Journal of Arts Science & Commerce

Currently, the mango ripeness classification is determined manually by human graders according to a particular procedure. This method is inconsistent and subjective in nature because each grader has different techniques. Thus, it affects the quantity and quality of the mango fruit that can be marketed. In this project, a new model for classifying mango fruit is developed using the fuzzy logic RGB sensor colour model build in the MATLAB software. The grading system was programmed with a colour sensor to analyze the mango fruit ripening index. The decision making process uses fuzzy logic to train the data and also to classify or categorize the mango fruit. The model developed is able to distinguish or separate the three different classes of mango fruit. The proposed model is able to distinguish the three different classes of mango fruit automatically with more than 85% accuracy.

FUZZY RIPENING MANGO INDEX USING RGB COLOUR SENSOR MODEL