Disease Identification & Classification in Millet Crops Using ML Techniques

Meena Kumari, Devansh Kulshreshtha, Anshul Agrawal, Aniket Sharma

2025

Abstract

Millets, including pearl, finger, and sorghum varieties, are essential crops known for their adaptability to harsh conditions and significant contribution to food security. However, their cultivation is frequently disrupted by plant diseases and weed infestations, which affect yield and quality. Traditional methods of addressing these issues often require manual effort and are limited in scalability, making them inefficient for large-scale farming. This project aims to provide a comprehensive solution through Machine Learning (ML) and Computer Vision technologies. Using the pre-trained VGG16 model, the system identifies and classifies diseases in millet crops, determining whether the plants are healthy or affected by specific conditions such as rust, mildew, or blast. Additionally, a weed detection feature is incorporated to facilitate effective management of weeds. The solution is deployed as a user-friendly application designed to deliver real-time insights, improving agricultural practices and promoting sustainable millet farming.

Paper Citation

in Harvard Style

Kumari M., Kulshreshtha D., Agrawal A. and Sharma A. (2025). Disease Identification & Classification in Millet Crops Using ML Techniques. In Proceedings of the 1st International Conference on Research and Development in Information, Communication, and Computing Technologies - ICRDICCT`25; ISBN 978-989-758-777-1, SciTePress, pages 328-334. DOI: 10.5220/0013897500004919

in Bibtex Style

@conference{icrdicct`2525,
author={Meena Kumari and Devansh Kulshreshtha and Anshul Agrawal and Aniket Sharma},
title={Disease Identification & Classification in Millet Crops Using ML Techniques},
booktitle={Proceedings of the 1st International Conference on Research and Development in Information, Communication, and Computing Technologies - ICRDICCT`25},
year={2025},
pages={328-334},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0013897500004919},
isbn={978-989-758-777-1},
}

in EndNote Style

TY - CONF

JO - Proceedings of the 1st International Conference on Research and Development in Information, Communication, and Computing Technologies - ICRDICCT`25
TI - Disease Identification & Classification in Millet Crops Using ML Techniques
SN - 978-989-758-777-1
AU - Kumari M.
AU - Kulshreshtha D.
AU - Agrawal A.
AU - Sharma A.
PY - 2025
SP - 328
EP - 334
DO - 10.5220/0013897500004919
PB - SciTePress