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All Journal International Journal of Informatics and Communication Technology (IJ-ICT)
Komang Diah Devi Pramesty
Telkom University
Computer Science & IT

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Early detection of vascular streak dieback (VSD) disease in cocoa plants using deep learning Dewi Marini Umi Atmaja; Arif Rahman Hakim; Fadhil Rozi Hendrawan; Komang Diah Devi Pramesty; Naufal Fadhilah Fitrah; Faiz Rochmatullah Widhaputra
International Journal of Informatics and Communication Technology (IJ-ICT) Vol 15, No 3: September 2026
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijict.v15i3.pp1087-1096

Abstract

Vascular streak dieback (VSD), caused by Ceratobasidium theobromae, poses a significant threat to cocoa (Theobroma cacao) production, leading to substantial yield losses and plant mortality. Early detection is critical to mitigate disease spread and reduce economic impact. While convolutional neural network (CNN) architectures like VGG-16 and ResNet-50 excel in leaf disease detection, no prior studies address stem-based VSD symptomatology where the disease originates in vascular tissues. This study presents the first CNN specifically developed for cocoa stem VSD detection, achieving 99.16% test accuracy with a lightweight architecture that outperforms VGG16/ResNet50 in both accuracy and mobile inference speed. A novel dataset of 215 cocoa stem images was curated and augmented for robustness. Additional evaluation metrics, including precision, recall, specificity, and F1-score, further confirm the reliability of the model. The model was successfully converted into TensorFlow Lite (TFLite) format, enabling deployment on mobile devices for real-time disease detection. This study highlights the potential of integrating deep learning into mobile and drone-based agricultural systems to support precision farming and early intervention strategies.
Co-Authors Arif Rahman Hakim Dewi Marini Umi Atmaja Fadhil Rozi Hendrawan Faiz Rochmatullah Widhaputra Naufal Fadhilah Fitrah