Author
Hunt Jr, Earle | |
HORNECK, D - Oregon State University | |
GADLER, D - Collaborator | |
BRUCE, A - Collaborator | |
TURNER, R - Collaborator | |
SPINELLI, C - Collaborator | |
BRUNGARDT, J - Collaborator | |
HAMM, P - Oregon State University |
Submitted to: Meeting Abstract
Publication Type: Abstract Only Publication Acceptance Date: 2/1/2014 Publication Date: 6/14/2014 Citation: Hunt Jr, E.R., Horneck, D., Gadler, D., Bruce, A., Turner, R., Spinelli, C., Brungardt, J., Hamm, P. 2014. Detection of nitrogen deficiency in potatoes using small unmanned aircraft systems [abstract]. 12th International Conference on Precision Agriculture. Paper No. 16. Interpretive Summary: Technical Abstract: Small Unmanned Aircraft Systems (sUAS) are recognized as potentially important remote-sensing platforms for precision agriculture. However, research is required to determine which sensors and data processing methods are required to use sUAS in an efficient and cost-effective manner. We set up a nitrogen rate experiment in potatoes with four rates of nitrogen fertilizer (112, 224, 337, and 449 kg N/ha) using a randomized block design with 3 replicates. With an FAA Certificate of Authorization, overflights with a Tetracam Hawkeye parafoil and Agricultural Digital Camera sensor were used to collect color-infrared imagery with pixel sizes from 1.5 to 3.0 cm, depending on altitude above ground level. Vegetation indices such as NDVI and Green NDVI were correlated to chlorophyll content, plant cover fraction, and leaf area index. In mid-June (during tuber initialization), plots with 112 kg/ha of applied nitrogen were clearly distinguishable from the other treatments. In early August, plots with 224 kg/ha of applied nitrogen were also distinguishable from the other N rates. Color and color-infrared images acquired 2-m above the canopy indicated that very small pixel sizes may be better to separate effects of nitrogen deficiency on leaf chlorophyll content and leaf area index. If these preliminary results are confirmed with additional data, then imagery with very small pixel sizes (< 0.5 cm) acquired from low-flying sUAS may be important for nitrogen management. |