Quality Sorting of Green Coffee Beans from Wet Processing by Using The Principle of Machine Learning

Thanapat Thongnop, Tanayut Perpaman, Panchanit Kansiri, Warathep Nuchda, Supachai Peungsungwan

Abstract


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.

Keywords


Coffee beans dataset; Coffee beans; Coffee dataset; Green coffee beans; Machine Learning; Quality sorting

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References


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DOI: https://doi.org/10.17509/ajse.v1i2.41078

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