World pesticide annual expenditures already exceeded more than $35 billion in 2007, and the United States is the second largest consumer of pesticides, accounting for more than 20% of the world pesticide consumption. To complicate matters, more than 98% of sprayed insecticides and 95% of herbicides can reach a destination other than their targets (Miller, 2004). The off-target chemicals result in significant waste of money as well as environmental degradation, particularly water and soil pollution, and human health risks.
During pesticide applications, of particular concern is the spray efficiency, defined as the percentage of spray droplet deposition in crop canopies, and spray drift, defined as the phenomena that pesticide droplets deflect out of the canopies and transport through the air to any places other than the targeted areas. Field measurement of spray drift is difficult and expensive because it is affected by many factors such as sampling time, air volume sampled, pesticide concentration in the air, and collection efficiency of samplers. As a complement to field tests, mathematical models and computer simulations, such as plume-based model and droplet trajectory model, have been developed and used to predict the spray drift and deposition according to various weather conditions and spray application conditions. For higher accuracy, many droplet trajectory models were combined with CFD simulations that provide calculation of detailed turbulent flows over a wide range of areas from sprayers to the field intended.
Numerical modeling integrated with user interfaces for inputs and outputs can improve both the efficiency and usability of the spray prediction for the purposes of regulation as well as better spray application practices. Several models are available for spray drift assessment, including AGDISPTM, AgDRIFT®, and DRIFTSIM. However, they are limited in considering spray drift for orchards and vineyard which occupy a major portion of ground pesticide applications. Furthermore, they cannot account for sprayer type, sprayer operation and efficiency affected by various crop species and growth stages.
The objective is to develop a software application, SAAS (Simulation of Air-Assisted Sprayers), for estimation of spray efficiency and drift from pesticide applications using orchard air-assisted sprayers.
The approach is using computational fluid dynamics (CFD) simulations to provide solutions to the fate and transport of pesticide spray droplets according to crop conditions, spray operating conditions, and weather conditions. The software tool SAAS provides the interpolated results based on a drift database generated by CFD simulations, data analysis programs, and condition inputs through graphic interfaces for users.
SAAS enables the users to estimate the spray mass balances, spray drift through airborne and ground deposition by distance, and pesticide drift setback distances to prevent potential risks of spray drift. It is expected to help farmers in making tactical decisions for pesticide applications to enhance the spray efficiency and reduce the risk of spray drift.
Relevant publications can be found here:
- Hong, S.W., L. Y. Zhao, and H. Zhu. 2018. SAAS, a computer program for estimating pesticide spray efficiency and drift of air-assisted pesticide applications. Computers and Electronics in Agriculture.155:58-68. https://doi.org/10.1016/j.compag.2018.09.031
- Hong, S.W., L. Y. Zhao, and H. Zhu. 2018. CFD simulation of pesticide spray from air-assisted sprayers in an apple orchard: Tree deposition and off-target losses. Atmospheric Environment. 175:109-119. https://doi.org/10.1016/j.atmosenv.2017.1001
- Hong, S.W., L. Y. Zhao, and H. Zhu. 2018. CFD simulation of airflow inside tree canopies discharged from air-assisted sprayers. Computers and Electronics in Agriculture. 149: 121-132. https://doi.org/10.1016/j.compag.2017.07.011
Please contact Dr. Lingying Zhao (firstname.lastname@example.org) for questions and comments.