Unmanned aerial vehicle image detection of maize-YOLOv8n seedling leakage
The results confirm the ability of the model to accurately detect maize seedling gaps. This study can evaluate the quality of seeding operations and provide accurate information on the number of missing seedlings for timely replacement work in areas with high rates of missing seedlings. This study advances precision agriculture by enhancing the efficiency and accuracy of maize planting management.
Authors
- Jiapeng Cui
- Jiaxin Gao (ORCID: https://orcid.org/0009-0001-2530-8808)
- Feng Tan
- Zhaoyuan Hou
Institutions
- Heilongjiang Bayi Agricultural University (CN)
- Chongqing Three Gorges University (CN)
Publication Details
- Journal
- Frontiers in Plant Science
- Published
- 2025-05-23
- DOI
- https://doi.org/10.3389/fpls.2025.1569229
- Citations
- 3
- Primary Topic
- Smart Agriculture and AI
- Type
- article
- Field-Weighted Citation Impact
- 5.25
Funders
- Heilongjiang Bayi Agricultural University