Nugraha, Rafi Dwi (2025) Classification of the Severity of Bacterial Leaf Blight (Xanthomonas sp.) in Rice Plants (Oryza Sativa L.) Based on Image Processing VARI Drone Images. Undergraduate thesis, UPN Veteran Jawa Timur.
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Abstract
Rice (Oryza sativa L.) is a strategic food commodity in Indonesia that is vulnerable to bacterial leaf blight (Xanthomonas oryzae). Early detection of disease severity is crucial to prevent yield loss. This study aims to classify the severity levels of bacterial leaf blight in rice using drone imagery and an image processing approach based on the Visible Atmospherically Resistant Index (VARI) and a Convolutional Neural Network (CNN) model. The research stages included aerial image acquisition, preprocessing, Tiling, vegetation index calculation, and disease classification. The results showed that the CNN model achieved an average classification accuracy of 78.8–87.5%, while the agreement between CNN classification and VARI reference maps reached 38%. These findings indicate that although CNN performs reasonably well in distinguishing disease severity levels, there is a significant difference compared to the VARI method, suggesting the need for further optimization. This study contributes to the development of automated plant disease detection methods using aerial imagery to support precision agriculture management.
| Item Type: | Thesis (Undergraduate) | ||||||||||||
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| Subjects: | S Agriculture > SB Plant culture > SB950-989 Pest Control and Treatment of Diseases, Plant Protection S Agriculture > S Agriculture (General) S Agriculture > SB Plant culture > SB599-990.5 Pests and Diseases S Agriculture > SH Aquaculture. Fisheries. Angling T Technology > T Technology (General) > T58.6-58.62 Management Information Systems |
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| Divisions: | Faculty of Agriculture > Departement of Agritechnology | ||||||||||||
| Depositing User: | Rafi Dwi Nugraha | ||||||||||||
| Date Deposited: | 15 Aug 2025 02:59 | ||||||||||||
| Last Modified: | 15 Aug 2025 02:59 | ||||||||||||
| URI: | https://repository.upnjatim.ac.id/id/eprint/41709 |
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