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

Plant disease has a tremendous impact on global food security, and bitter rot caused by Colletotrichum spp. 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.

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Published
2025-11-07
DOI
https://doi.org/10.3390/ecsa-12-26540
Primary Topic
Optical Coherence Tomography Applications
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article
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Non-Invasive Disease Stage Classification of Bitter Rot in Fruits Using Optical Coherence Tomography and Intensity-Based Image Analysis

Bhagya Nathali Silva, Jeehyun Kim, Nipun Shantha Kahatapitiya, Mansik Jeon et al.
Optical Coherence Tomography Applications
article

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

Bhagya Nathali Silva, Jeehyun Kim, Nipun Shantha Kahatapitiya, Mansik Jeon, Udaya Wijenayake, Nisala Damith, Ruchire Eranga Wijesinghe, Amila Dhanushka Karunanayaka
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Abstract

Plant disease has a tremendous impact on global food security, and bitter rot caused by Colletotrichum spp. 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.

University of Sri Jayewardenepura (LK), Sri Lanka Institute of Information Technology (LK), Kyungpook National University (KR)
Zero hunger
Openalex Percentile: Top 40%
Optical Coherence Tomography Applications
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