Abstract
Unmanned agricultural aircraft system (UAAS) has been widely employed as a low-cost and reliable method to apply agrochemicals to small agricultural fields in China. The performance of battery-powered multirotor UAAS has attracted considerable attention from manufacturers and researchers. The objective of this research was to design a UAAS equipping with a data acquisition system, to characterize its chemical application performance based on droplet deposition data and optimize the operating parameters. Each test was repeated three times to assess the reliability of the spraying system. Various flight parameters were also evaluated. The optimal spray pressure for the XR8001 and XR8002 (TeeJet, Wheaton, IL, USA) nozzles was found to be 300 kPa, and the latter nozzle had a higher droplet deposition rate and spray volume. Spray volume was not significantly affected by the flight speed or droplet density and was negatively correlated with the nozzle pressure. The results of this study provide a basis for improving the efficiency of UAAS chemical application systems in terms of large-scale application.
Recommended Citation
H. Zhu et al., "Performance Evaluation of a Multi-Rotor Unmanned Agricultural Aircraft System for Chemical Application," International Journal of Agricultural and Biological Engineering, vol. 14, no. 4, pp. 43 - 52, International Journal of Agricultural and Biological Engineering (IJABE), Jul 2021.
The definitive version is available at https://doi.org/10.25165/j.ijabe.20211404.6194
Department(s)
Civil, Architectural and Environmental Engineering
Keywords and Phrases
Aerial Sprayer; Chemical Application; Effective Swath Width; Flight Parameters; Onboard Data Acquisition System; Performance Evaluation; Spray Characterization; Unmanned Agricultural Aircraft System
International Standard Serial Number (ISSN)
1934-6352; 1934-6344
Document Type
Article - Journal
Document Version
Final Version
File Type
text
Language(s)
English
Rights
© 2021 The Authors, All rights reserved.
Creative Commons Licensing
This work is licensed under a Creative Commons Attribution 4.0 License.
Publication Date
01 Jul 2021
Comments
This work was partially financially supported by the National Key Research and Development Program of China (Grant No. 2016YFD0200701).