EventsThe 12th International Electronic Conference on Sensors and Applications
Published
This submission belongs to the session S5. Smart Agriculture Sensors of the event The 12th International Electronic Conference on Sensors and Applications
Published date
07 Nov, 2025
Academic Editor
author-avatarStefano Mariani
Citation
Amila Dhanushka Karunanayaka, Nipun Shantha Kahatapitiya, Nisala Damith, Jeehyun Kim, Mansik Jeon, Bhagya Nathali Silva, Udaya Wijenayake, Ruchire Eranga Wijesinghe, Non-Invasive Disease Stage Classification of Bitter Rot in Fruits Using Optical Coherence Tomography and Intensity-Based Image Analysis, in Proceedings of The 12th International Electronic Conference on Sensors and Applications, 12 November–14 November 2025, MDPI: Basel, Switzerland, doi: 10.3390/ECSA-12-26540
Share
Email
Facebook
Twitter
LinkedIn

Non-Invasive Disease Stage Classification of Bitter Rot in Fruits Using Optical Coherence Tomography and Intensity-Based Image Analysis

image
image
image
image
image
image
1. Department of Electrical and Electronic Engineering, Faculty of Engineering, Sri Lanka Institute of Information Technology, Malabe 10115, Sri Lanka, Sri Lanka
2. School of Electronic and Electrical Engineering, College of IT Engineering, Kyungpook National University, Daegu 41566, Republic of Korea, South Korea
3. Department of Computer Engineering, Faculty of Engineering, University of Sri Jayewardenepura, Nugegoda 10250, Sri Lanka, Sri Lanka
4. Department of Information Technology, Faculty of Computing, Sri Lanka Institute of Information Technology, Malabe 10115, Sri Lanka, Sri Lanka
5. Center for Excellence in Informatics, Electronics and Transmission (CIET), Sri Lanka Institute of Information Technology, Malabe 10115, Sri Lanka
Abstract

Plant disease has a tremendous impact on global food security, and Colletotrichum spp. caused bitter rot is a greater challenge to post-harvest quality. Conventional diagnosis is precise but invasive and therefore inappropriate for real-time purposes. This study investigates optical coherence tomography (OCT) as a high-resolution, non-invasive imaging method to detect internal structural changes from disease progression. The developed OCT-based image analysis framework stages diseases by assessing morphological degradation. The discovery of unique oval-shaped internal features, invisible to other non-invasive methods, demonstrates OCT’s potential for early detection, accurate monitoring, and real-time application in precision agriculture.

Keywords
Optical Coherence Tomography (OCT)
Bitter Rot
Non-invasive Detection
Swept-Source OCT (SS-OCT)
Fruit Disease Monitoring
Structural Biomarkers
Post-harvest Diagnostics
Manuscript
Wireless Soil Health Beacons: An Intelligent Sensor-Based System for Real-Time Monitoring in Precision Agriculture
Exploring the Application of UAV-Multispectral Sensors for Proximal Imaging of Agricultural Crops