Improving <scp>UASS</scp> pesticide application: optimizing and validating drift and deposition simulations
This study optimized UASS simulation parameters, balancing computational efficiency with accuracy. The validated model enhances our ability to design more effective UASS for pest management, potentially leading to more precise and targeted pesticide applications. These advancements contribute to the development of sustainable pest control strategies, aiming to reduce pesticide usage and environmental impact while maintaining crop protection efficacy. © 2024 Society of Chemical Industry.
Authors
- Qing Tang (ORCID: https://orcid.org/0000-0001-7322-6455)
- Andrew Hewitt (ORCID: https://orcid.org/0000-0001-9210-7013)
- Tongchuan Yi
- Gang Xu (ORCID: https://orcid.org/0000-0002-1391-9919)
- Pan Zhang (ORCID: https://orcid.org/0000-0002-5486-7537)
- Liping Chen (ORCID: https://orcid.org/0000-0003-4873-8533)
- Ruirui Zhang (ORCID: https://orcid.org/0000-0001-8928-4238)
- Longlong Li (ORCID: https://orcid.org/0000-0001-6411-4603)
Institutions
- The University of Queensland (AU)
- National Engineering Research Center for Information Technology in Agriculture (CN)
Publication Details
- Journal
- Pest Management Science
- Published
- 2024-09-17
- DOI
- https://doi.org/10.1002/ps.8412
- Citations
- 5
- Primary Topic
- Lattice Boltzmann Simulation Studies
- Type
- article
- Field-Weighted Citation Impact
- 1.87
Funders
- National Natural Science Foundation of China