Computer simulation of pesticide deposition and drift by conventional and intelligent air-assisted sprayers in apple orchards

Abstract

To enhance pesticide sprayer performance, a laser guided variable-rate spraying system was developed to efficiently deliver spray outputs to a variety of plants across different growth stages. However, evaluating the performance of this system using field experiments is challenging and resource intensive. The Simulation of Air-Assisted Sprayers (SAAS), a cost-effective and user-friendly computational fluid dynamics (CFD) simulation program, was used to evaluate pesticide deposition and drift in apple orchards under varying spray and weather conditions. Results indicated that pesticide deposition efficiency was highest when very fine droplets were applied to apple trees under low wind speeds (< 1.79 m s⁻¹), low relative humidity (< 30 %), and high ambient air temperatures (> 20 °C). Ground deposition losses were highest when spray nozzles producing very coarse droplets were applied at low travel speeds (0.89 m s⁻¹), low wind speeds, and high ambient air temperatures. Airborne drift was highest when a sprayer discharged very fine droplets under low travel speeds, high wind speeds (> 3.58 m/s), high relative humidity (> 70 %), and low ambient air temperatures (10 °C). The simulation results showed the intelligent sprayer was expected to reduce pesticide usage by 38.4 % to 51.9 % and improve average spray efficiency by 1.6 to 3.3 times depending on the nozzle type compared to a conventional spray system. This research demonstrated the SAAS could be used to optimize pesticide applications, improve spray efficiency, and reduce environmental impact.