Optimization of Disease Detection System for Improved Arecanut Cultivation by Machine Learning

Karthikeyan M, Vijaychitra S

2025

Abstract

Agricultural growth is crucial for ensuring a consistent food supply for ordinary people. To optimize disease detection methods and improve crop quality, data from various published research works is collected and analysed. These efforts aim to protect plants from diseases, enhancing both agricultural productivity and the country's economic contributions. This review compares machine learning and deep learning techniques for identifying and categorizing plant diseases. Images of arecanut leaves, trunk, stem and root were used as input for the research. The study focuses on disease detection systems implemented using various algorithms and compares their accuracy based on findings from published research. The results indicate that Convolutional Neural Networks (CNNs) consistently achieve better accuracy than traditional machine learning methods. Future research can explore advanced deep learning techniques to achieve even higher accuracy in plant disease detection.

Paper Citation

in Harvard Style

M K. and S V. (2025). Optimization of Disease Detection System for Improved Arecanut Cultivation by Machine Learning. In Proceedings of the 3rd International Conference on Futuristic Technology - Volume 2: INCOFT; ISBN 978-989-758-763-4, SciTePress, pages 123-134. DOI: 10.5220/0013588100004664

in Bibtex Style

@conference{incoft25,
author={Karthikeyan M and Vijaychitra S},
title={Optimization of Disease Detection System for Improved Arecanut Cultivation by Machine Learning},
booktitle={Proceedings of the 3rd International Conference on Futuristic Technology - Volume 2: INCOFT},
year={2025},
pages={123-134},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0013588100004664},
isbn={978-989-758-763-4},
}

in EndNote Style

TY - CONF

JO - Proceedings of the 3rd International Conference on Futuristic Technology - Volume 2: INCOFT
TI - Optimization of Disease Detection System for Improved Arecanut Cultivation by Machine Learning
SN - 978-989-758-763-4
AU - M K.
AU - S V.
PY - 2025
SP - 123
EP - 134
DO - 10.5220/0013588100004664
PB - SciTePress