Proceedings of the International Conference on Recent Advancements and Modernisations in Sustainable Intelligent Technologies and Applications (RAMSITA 2025)

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Automated COCOA Disease Detection Using Convolutional Neural Networks: A Case Study of VSD and Other Pathogens

Authors
Sachin Kumar1, *, Avadhesh Kumar Sharma2, Saurabh Srivastava3, Vivek Tiwari1, Praveen Kumar Patidar1, Sangeeta Rai4
1Department of CSE, Parul University, Vadodara, Gujarat, India
2Department of ECE, GL Bajaj Institute of Technology & Management, Greater Noida, UP, India
3Department of CSE, United University, Rawatpur, Prayagraj, UP, India
4School of CSE, Lovely Professional University, Phagwara, Panjab, India
*Corresponding author. Email: jaiswalsachin009@gmail.com
Corresponding Author
Sachin Kumar
Available Online 26 May 2025.
DOI
10.2991/978-94-6463-716-8_29How to use a DOI?
Keywords
Cocoa leaf disease; Vascular streak dieback; Convolutional neural network
Abstract

Theobroma cacao L., commonly known as cocoa, is a plantation crop of significant economic value, renowned for its dried fruits. The high market demand for cocoa is not negatively correlated with its low production output. The high prevalence and quick spread of illness is the main problem in cocoa farms. A majority Vascular Streak Dieback (VSD) is a prevalent illness. To maintain productivity, appropriate treatment must be administered promptly. The diagnosis of cocoa leaf disease diseases can be sped up and made simpler by utilizing a “Convolutional Neural Network (CNN)” to identify diseases based on leaf images. The main objective of this research article is to distinguish VSD-infected cocoa plants, we have used total 1200 image for classification of VSD disease. DenseNet-19 shows the best result with accuracy of 99.1% in 7.48 minutes only.

Copyright
© 2025 The Author(s)
Open Access
Open Access This chapter is licensed under the terms of the Creative Commons Attribution-NonCommercial 4.0 International License (http://creativecommons.org/licenses/by-nc/4.0/), which permits any noncommercial use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license and indicate if changes were made.

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Volume Title
Proceedings of the International Conference on Recent Advancements and Modernisations in Sustainable Intelligent Technologies and Applications (RAMSITA 2025)
Series
Advances in Intelligent Systems Research
Publication Date
26 May 2025
ISBN
978-94-6463-716-8
ISSN
1951-6851
DOI
10.2991/978-94-6463-716-8_29How to use a DOI?
Copyright
© 2025 The Author(s)
Open Access
Open Access This chapter is licensed under the terms of the Creative Commons Attribution-NonCommercial 4.0 International License (http://creativecommons.org/licenses/by-nc/4.0/), which permits any noncommercial use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license and indicate if changes were made.

Cite this article

risenwbib
TY  - CONF
AU  - Sachin Kumar
AU  - Avadhesh Kumar Sharma
AU  - Saurabh Srivastava
AU  - Vivek Tiwari
AU  - Praveen Kumar Patidar
AU  - Sangeeta Rai
PY  - 2025
DA  - 2025/05/26
TI  - Automated COCOA Disease Detection Using Convolutional Neural Networks: A Case Study of VSD and Other Pathogens
BT  - Proceedings of the International Conference on Recent Advancements and Modernisations in Sustainable Intelligent Technologies and Applications (RAMSITA 2025)
PB  - Atlantis Press
SP  - 361
EP  - 372
SN  - 1951-6851
UR  - https://doi.org/10.2991/978-94-6463-716-8_29
DO  - 10.2991/978-94-6463-716-8_29
ID  - Kumar2025
ER  -