DNA Computing for Early Detection of Crop Disorders in Bangladesh
Students & Supervisors
Student Authors
Supervisors
Abstract
"Background Crop diseases in Bangladesh cause major yield losses every year. Traditional detection methods are often slow and inaccurate, delaying effective action. DNA computing offers precise, early pathogen detection through molecular analysis. This study explores its application in managing diseases in rice, potato, and jute. Methodology Using secondary data, the study assessed yield losses from bakanae (rice), late blight (potato), and CoGMV (jute), and evaluated three DNA computing methods—HCR for amplification, TMSD for targeted detection, and DNAzymes for catalytic sensing. These cost-effective techniques showed 75%–93% potential loss reduction, visualized through a comparative bar chart. Findings Current disease-related yield losses are about 25% for rice, 27% for potato, and 20% for jute. With DNA computing, these losses could drop to 5%, 2%, and 5%, respectively—showing potential reductions of 80% (rice), 93% (potato), and 75% (jute). This shows molecular diagnostics can boost crop health and productivity. Conclusion DNA computing shows strong potential in reducing crop losses in Bangladesh through early disease detection. Techniques like HCR, TMSD, and DNAzymes offer practical, efficient solutions. Successful implementation, however, requires infrastructure support, farmer training, and further pilot studies. References [1] Husna et al. (2024). Egyptian J. of Crop Protection, 19(2), 19–28. [2] Dey et al. (2010). Potato Journal, 37(3–4), 99–102. [3] Ghosh et al. (2011). Microbiology Journal, 67(4), 1–15."
Keywords
Publication Details
- Type of Publication: Conference
- Conference Name: IEEE Computer Society Bangladesh Chapter Summer Symposium 2025
- Date of Conference: 18/07/2025 - 18/07/2025
- Venue: Hajee Mohammad Danesh Science and Technology University (HSTU)
- Organizer: IEEE Computer Society Bangladesh Chapter