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© 2026 IJSREM – International Journal of Scientific Research in Engineering and Management. This is an open-access journal. Articles are published under the Creative Commons Attribution (CC BY 4.0) License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

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ArticlePeer ReviewedOpen AccessPlagiarism Passed
Paper ID:10.55041/IJSREM58017

An AI-Driven Framework for Crop Disease Detection and Management Using Deep Learning and Leaf Image Analysis

Stream/Area:

-

Subject:

-

Paper ID:

10.55041/IJSREM58017

Volume:

10 |

3 |

Mar 2026

Pages:

Publication Frequency:

Monthly (12 issues per year)

DOI
Digital Object Identifier
10.55041/IJSREM58017

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

DADR

Dr. A. D. Raut

SS

Samiksha Solanke

SK

Samiksha Koagde

SN

Saloni Nakat

RB

Rutuja Bambal

RG

Renuka Gaud

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Abstract

Agriculture is a key sector that supports the economy and food supply. However, plant diseases reduce crop yield and quality, creating major challenges for farmers. Early detection of plant diseases is important to prevent large agricultural losses. This project presents an AI-Driven Crop Disease Prediction and Management System that uses machine learning and image processing techniques to detect diseases in crop leaves. The system analyzes leaf images to identify disease patterns and provide appropriate management suggestions. By using artificial intelligence, farmers can easily detect diseases without relying on manual inspection. The system is designed to be efficient, scalable, and accessible through mobile applications, making it a useful tool for modern smart farming.

KEYWORDS

Artificial Intelligence Deep Learning Crop Disease Detection Image Processing Convolutional Neural Networks (CNN) Plant Disease Classification Smart Agriculture Precision Farming.

Cite This Article

Dr. A. D. Raut, Samiksha Solanke, Samiksha Koagde, Saloni Nakat, Rutuja Bambal, Renuka Gaud, "An AI-Driven Framework for Crop Disease Detection and Management Using Deep Learning and Leaf Image Analysis," International Journal of Scientific Research in Engineering and Management, vol. 10, no. 3, Mar 2026. https://doi.org/10.55041/IJSREM58017

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Publication Date

3/22/2026

Peer Review Type

Double-Blind Peer Review

Review Rounds: 2

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1

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3

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5

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Conflict of Interest

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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