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Automated durian grading machine using raspberry pi / Sheila, G. Hermina, Fritz Bryan E. Buno, and Myka Sydney S. Rojas

By:

Hermina, Sheila G

Contributor(s):

Material type: Text

TextPublication details: Digos City : UMDC, ©December 2023.Description: ix, 32 pages : illustration (some colors) ; 29 cmDDC classification:

2023 UT

Summary: Durian has become a important high-value crop in the Philippines, not only due to local demand but also because it has a high market potential. The Bureau of Agriculture and Fisheries Product Standard(BAFPS) introduced a standardized grading system for fresh durian fruit. However, the current practice of manual grading post-harvest often results in inconsistent classification and inaccurate judgments due to variations among humans. This study aims to design and develop an automated durian-grading machine based on its weight and external characteristics to enhance efficiency and consistency in the grading process compared to the traditional manual approach. The researchers utilized Roboflow as an image processing tool where datasets undergo several processes. The researcher used a confusion matrix to analyze the data gathered. The overall results showed 83.5% accuracy in determining its grade.

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Holdings
Item type	Current library	Call number	Status	Date due	Barcode
Undergraduate Thesis	UM Digos College - LIC	UT (Browse shelf(Opens below))	Not for loan

Includes references and appendices.

Durian has become a important high-value crop in the Philippines, not only due to local demand but also because it has a high market potential. The Bureau of Agriculture and Fisheries Product Standard(BAFPS) introduced a standardized grading system for fresh durian fruit. However, the current practice of manual grading post-harvest often results in inconsistent classification and inaccurate judgments due to variations among humans. This study aims to design and develop an automated durian-grading machine based on its weight and external characteristics to enhance efficiency and consistency in the grading process compared to the traditional manual approach. The researchers utilized Roboflow as an image processing tool where datasets undergo several processes. The researcher used a confusion matrix to analyze the data gathered. The overall results showed 83.5% accuracy in determining its grade.

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