000			01559nam a22001817a 4500
005			20250821141203.0
008			250218b |||||||| |||| 00| 0 eng d
082			_22023 _aUT
100			_aHermina, Sheila G. _965428
245			_aAutomated durian grading machine using raspberry pi / _cSheila, G. Hermina, Fritz Bryan E. Buno, and Myka Sydney S. Rojas
260			_aDigos City : _bUMDC, _c©December 2023.
300			_aix, 32 pages : _billustration (some colors) ; _c29 cm.
500			_aIncludes references and appendices.
520			_aDurian 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.
700			_a Buno, Fritz Bryan E. _965429
700			_a Rojas, Myka Sydney S. _965430
942			_2ddc _cUT
999			_c23479 _d23479