Grey oyster mushroom grading system (GO-MUSH)

Nik Mohd Zarifie, Hashim and Mohd Hariz, - and ANUAR, JAAFAR and Ranjit Singh, Sarban Singh and MOHD SYUKOR, AHMAD (2022) Grey oyster mushroom grading system (GO-MUSH). In: International Borneo Innovation Exhibition & Competition (IBIEC 2022), 19-20 October 2022, Politeknik kota kinabalu.

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Abstract

In Malaysia, the grey oyster mushroom is a typical crop and supplemental food. Grading comprises looking over and selecting different mushrooms according to quality, freshness, legal compliance, and market worth to guarantee that this grey oyster mushroom is of high quality when it reaches the buyer. Typically, the mushroom is evaluated and sorted by hand as part of the grading process. Freshness, maturity, damage, defects, and uniform size are the five essential characteristics that can be used to grade mushrooms. Without a sophisticated grading system, the machinery is insufficient. Industrial Revolution 4.0's effects encourage using current, bright computer vision in various industrial applications. This study uses Raspberry Pi to simulate a straightforward grading system for a grey oyster mushroom that will work for the Malaysian agricultural sector. The suggested effort also aims to create a grading system using a GUI-based categorization assignment for grey oyster mushrooms. According to the FAMA's requirements, the proposed work delivered a good performance with an analysis with a 94% grading accuracy and hardware ready for the grey oyster mushroom grading system. The grading method allows the farmer to choose whether a grade of grey oyster mushrooms can be sold or not.

Item Type: Conference or Workshop Item (Paper)
Uncontrolled Keywords: Classification, Convolution neural network, Graphical user interface, Grey oyster mushroom, Raspberry Pi
Divisions: Faculty of Electronics and Computer Engineering
Depositing User: WIZANA ABD JALIL
Date Deposited: 07 Apr 2023 11:23
Last Modified: 19 Dec 2023 07:52
URI: http://eprints.utem.edu.my/id/eprint/26810
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