Đăng nhập
 
Tìm kiếm nâng cao
 
Tên bài báo
Tác giả
Năm xuất bản
Tóm tắt
Lĩnh vực
Phân loại
Số tạp chí
 

Bản tin định kỳ
Báo cáo thường niên
Tạp chí khoa học ĐHCT
Tạp chí tiếng anh ĐHCT
Tạp chí trong nước
Tạp chí quốc tế
Kỷ yếu HN trong nước
Kỷ yếu HN quốc tế
Book chapter
Tạp chí quốc tế 2023
Số tạp chí 2014(2023) Trang:
Tạp chí: Mesurement

The advancement of unmanned aerial vehicles (UAVs) offers precise and accurate spectral and spatial information about crops and plays a pivotal role in precision agriculture. This study used UAVs, geographic information systems (GIS), and deep learning technology to monitor corn growth performance across different management practices. Two experimental corn fields were divided into four plots to evaluate the effects of varying corn management practices (i.e., seeding schedule, planting depth, and fertilization method) on corn growth performance. RGB and MicaSense multispectral cameras were mounted on UAVs to collect corn field images. YOLOv5 was investigated for counting corn plants. Plant height, Normalized Difference Vegetation Index (NDVI), Normalized Difference Red-Edge Index (NDRE), plant density, and plant volume were mapped based on UAV images. Additionally, the Otsu thresholding method was evaluated as an automatic method for separating plant height, NDVI, and NDRE values from the background. YOLOv5 and Otsu thresholding were efficient and accurate for automatically counting corn plants and extracting corn plant heights as well as VIs, respectively. The emergence rates of corn seeds were 40%, 33%, 41%, and 62% in plots A, B, C, and D, respectively. Variations in corn field management practices significantly affected the emergence rate, with fertilizer application close to seeds emerging as the optimal practice for achieving higher emergence rates across experimental plots. This study used deep learning and UAV to provide precise information and valuable insights into corn field practices, which can help farmers optimize corn cultivation. The techniques applied in this study could be extrapolated to improve cultivation processes for other crops.

Các bài báo khác
Số tạp chí 13(2023) Trang: 295-301
Tạp chí: Online Journal of Animal and Feed Research
Số tạp chí 17(2023) Trang: 479-500
Tạp chí: International Journal of Management in Education
Số tạp chí 10(2023) Trang: 769-779
Tạp chí: International Journal of Membrane Science and Technology
Số tạp chí 12(2023) Trang:
Tạp chí: International Journal of Veterinary Science


Vietnamese | English






 
 
Vui lòng chờ...