QUALITY SORTING OF GREEN COFFEE BEANS FROM WET PROCESSING BY USING THE PRINCIPLE OF MACHINE LEARNING

Authors

  • Thanapat Thongnop King Mongkut's University of Technology Thonburi Author
  • Tanayut Perpaman King Mongkut's University of Technology Thonburi Author
  • Panchanit Kansiri King Mongkut's University of Technology Thonburi Author
  • Warathep Nuchda King Mongkut's University of Technology Thonburi Author
  • Supachai Peungsungwan King Mongkut's University of Technology Thonburi Author

Keywords:

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

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.

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Author Biographies

  • Thanapat Thongnop, King Mongkut's University of Technology Thonburi

    Department of Electrical Technology Education, Faculty of Industrial Education and Technology

  • Tanayut Perpaman, King Mongkut's University of Technology Thonburi

    Department of Electrical Technology Education, Faculty of Industrial Education and Technology

  • Panchanit Kansiri, King Mongkut's University of Technology Thonburi

    Department of Electrical Technology Education, Faculty of Industrial Education and Technology

  • Warathep Nuchda, King Mongkut's University of Technology Thonburi

    Department of Electrical Technology Education, Faculty of Industrial Education and Technology

  • Supachai Peungsungwan, King Mongkut's University of Technology Thonburi

    Department of Electrical Technology Education, Faculty of Industrial Education and Technology

References

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Feria-Morales, A. M. (2002). Examining the case of green coffee to illustrate the limitations of grading systems/expert tasters in sensory evaluation for quality control. Food Quality and Preference, 13(6), 355-367.

Mediayani, M., Wibisono, Y., Riza, L. S., and Pérez, A. R. (2019). Determining trending topics in twitter with a data-streaming method in R. Indonesian Journal of Science and Technology, 4(1), 148-157.

Riza, L. S., Rosdiyana, R. A., Pérez, A. R., and Wahyudin, A. The K-Means Algorithm for Generating Sets of Items in Educational Assessment. Indonesian Journal of Science and Technology, 6(1), 93-100.

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Published

2024-02-06

How to Cite

QUALITY SORTING OF GREEN COFFEE BEANS FROM WET PROCESSING BY USING THE PRINCIPLE OF MACHINE LEARNING. (2024). ASEAN Journal of Science and Engineering, 1(2), 63-66. https://ejournal.kjpupi.id/index.php/ajse/article/view/258