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ArticlePeer ReviewedOpen AccessPlagiarism Passed
Paper ID:10.55041/IJSREM18896

Fruit Grading System

Stream/Area:

-

Subject:

-

Paper ID:

10.55041/IJSREM18896

Volume:

7 |

4 |

Apr 2023

Pages:

Publication Frequency:

Monthly (12 issues per year)

DOI
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Not assigned

License:International Journal of Scientific Research in Engineering and Management follows the Creative Commons Attribution 4.0 (CC BY 4.0) License, allowing free use and distribution with proper attribution.

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Authors

PSD

Prof. Swapnil Desai

SS

Sagar Sunka

AS

Anubhav Shukla

HN

Harsh Narula

KT

Karan Tak

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Abstract

Fruit grading systems are critical for ensuring the quality, consistency, and efficiency of fruit production and distribution. These systems utilize advanced technologies such as computer vision and automation to accurately identify and classify fruit based on various quality parameters such as size, colour, and blemishes. The use of automated grading systems reduces the need for manual labour, increases throughput, and improves accuracy by minimizing human error. This results in a faster and more efficient grading process that can handle large volumes of fruit quickly and consistently, reducing the time and cost of fruit grading. Additionally, fruit grading systems play a crucial role in reducing waste and promoting sustainability in the fruit industry. By accurately grading fruit, less high-quality fruit goes to waste, and resources are used more efficiently. Grading systems can also identify opportunities for optimization, such as reducing packaging waste or identifying areas for process improvement. Overall, fruit grading systems are essential for ensuring high-quality fruit that meets the demands of the industry while also promoting sustainability and efficient distribution.

KEYWORDS

Object Detection Computer Vision Machine Learning Deep Learning Fruit Grading TensorFlow.

Cite This Article

Prof. Swapnil Desai, Sagar Sunka, Anubhav Shukla, Harsh Narula, Karan Tak, "Fruit Grading System," International Journal of Scientific Research in Engineering and Management, vol. 7, no. 4, Apr 2023. https://doi.org/10.55041/IJSREM18896

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Publication Date

11/3/2023

Peer Review Type

Double-Blind Peer Review

Review Rounds: 2

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5

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The authors declare no conflict of interest related to this research work.

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No funding information available for this research.

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