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ArticlePeer ReviewedOpen AccessPlagiarism Passed
Paper ID:IJSREM54735

An AI Approach to Disease Detection and Agronomic Support in Gymnema Sylvestre

Stream/Area:

-

Subject:

-

Paper ID:

IJSREM54735

Volume:

9 |

11 |

Nov 2025

Pages:

Publication Frequency:

Monthly (12 issues per year)

DOI
Digital Object Identifier
10.55041/IJSREM54735

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

PNG

Prof. Nirmala Ganiger

2MAS

2 Mr. Ayman Shilledar

3MNP

3 Ms. Noorussaba Pakali

4MSH

4 Ms. Sadiya Hospetkazi

5MSK

5 Ms. Sayyedaafreen Khatib

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Abstract

This study presents an AI-based system for detecting leaf diseases in Gymnema sylvestre, including powdery mildew, aphid infestation, and leaf spot. The platform uses convolutional neural networks (CNN) on smartphone images and provides web-based diagnostic reports, cultivation guidance, product recommendations, and dosage instructions. Developed with TensorFlow and React, it supports sustainable cultivation and safe human consumption of Gymnema products.

KEYWORDS

Gymnema sylvestre disease detection leaf disease classification CNN powdery mildew aphid infestation leaf spot agronomic support dosage guidance web application medicinal plant management plant health monitoring.

Cite This Article

Prof. Nirmala Ganiger, 2 Mr. Ayman Shilledar, 3 Ms. Noorussaba Pakali, 4 Ms. Sadiya Hospetkazi, 5 Ms. Sayyedaafreen Khatib, "An AI Approach to Disease Detection and Agronomic Support in Gymnema Sylvestre," International Journal of Scientific Research in Engineering and Management, vol. 9, no. 11, Nov 2025. https://doi.org/10.55041/IJSREM54735

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Publication Date

1/11/2025

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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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