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ArticlePeer ReviewedOpen AccessPlagiarism Passed
Paper ID:10.55041/IJSREM29056

FruitScan Pro : Fruit Disease and Quality Detection Application

Stream/Area:

-

Subject:

-

Paper ID:

10.55041/IJSREM29056

Volume:

8 |

3 |

Mar 2024

Pages:

Publication Frequency:

Monthly (12 issues per year)

DOI
Digital Object Identifier
10.55041/IJSREM29056

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

MSHS

Mr. S. H. Sangale

SN

Shiwani Nanaware

RM

Rituja Malode

SM

Shraddha More

MP

Madhura Patil

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Abstract

This research paper proposes a revolutionary approach to agriculture by combining the latest image processing technologies with machine learning. The agricultural industry, which is vital for India’s economy, needs efficient methods for monitoring fruit health. Manual monitoring is time consuming and often inadequate. In this paper, we propose a smart farming approach using image processing techniques. This approach improves image quality, segmenting images, extracting features, and classifying diseases and their cures. Fruit diseases are a major economic challenge around the world. Therefore, it is necessary to identify them quickly. Our proposed system offers fast and automatic disease detection. Preprocessing, extracting features, classifying, training/testing. The results prove its effectiveness for accurate disease detection and solutions. As the demand for agricultural productivity increases, this method will be a valuable tool for increasing fruit production with minimum human intervention. Image processing for effective implementation.

KEYWORDS

Fruit Disease Solution Image Preprocessing Feature Extraction Classification.

Cite This Article

Mr. S. H. Sangale, Shiwani Nanaware, Rituja Malode, Shraddha More, Madhura Patil, "FruitScan Pro : Fruit Disease and Quality Detection Application," International Journal of Scientific Research in Engineering and Management, vol. 8, no. 3, Mar 2024. https://doi.org/10.55041/IJSREM29056

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Publication Date

12/31/45355

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Double-Blind Peer Review

Review Rounds: 2

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

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