Open AccessQuality Sorting of Green Coffee Beans from Wet Processing by Using The Principle of Machine Learning
Author(s) -
Thanapat Thongnop,
Tanayut Perpaman,
Panchanit Kansiri,
Warathep Nuchda,
Supachai Peungsungwan
Publication year - 2021
Publication title -
asean journal of science and engineering
Language(s) - English
Resource type - Journals
eISSN - 2776-5938
pISSN - 2776-6098
DOI - 10.17509/ajse.v1i2.41078
Subject(s) - green coffee , sorting , sort , agricultural engineering , coffee bean , food processing , quality (philosophy) , mathematics , machine vision , computer science , artificial intelligence , food science , machine learning , engineering , arithmetic , algorithm , chemistry , philosophy , epistemology
Coffee beans are processed in a variety of ways such as beverages, foods, sweets, etc. Technology to sort coffee beans is still automated. We, therefore, proposed the concept of machine learning to be applied in coffee bean sorting. We consider the moisture content, size, colour, and characteristics of the coffee bean using image processing. Finally, we sorted the green coffee beans by the Thai coffee grading standards. There are three grades: A, X, and Y. Our machine has an accuracy of 85%. To improve the quality of our machines, the datasets used to train machines must be increased.