Development and validation of a 3D CFD model of drift and its application to air-assisted orchard sprayers

Abstract

Pesticides play an important role in providing high crop yields by minimizing risks associated with the occurrence of pests. Some of the sprayed product may, however, move beyond the intended target and result in drift. Modelling approaches help to understand spray drift using computer simulations. However, modelling drift from orchard spraying presents particular challenges: (1) the moving spray interacts with the canopy before reaching the drift area; (2) the vertical wind profile changes from the orchard to the neighbouring field that has a different vegetation; (3) the moving air jet from the air assistance cannot be ignored because the magnitude of the air jet velocity is typically higher than the wind velocity. As a result the modelling becomes rather complex. This work presents a three-dimensional (3D) computational fluid dynamics (CFD) model of spray drift from orchard sprayers that considers the actual tree architecture, the canopy wind flow and the moving sprayer outlet to calculate sedimenting and airborne drift; thus tackling each of the above challenges. The CFD model was validated against drift measurements from an apple orchard with different nozzles arrangements. This model was then used to evaluate the effect of drift reducing nozzles and fan speed on drift. Drift reducing nozzles reduced the drifting distance by 50%, but increased near-tree ground deposition. The increase in ground deposition near the tree can be avoided (keeping the 50% reduction in the drifting distance) by combining the drift reducing nozzles with the standard ones. A reduced sprayer airflow resulted in further reduction of the percentage drift.

The computational fluid dynamic modeling of downwash flow field for a six-rotor UAV

“…For instance, Melese Endalew et al [12,13] used CFD to analyze the drift of pesticides in orchards for an air-assisted spraying system for different spray types. Duga et al [14] studied the verification and development of the drift and application of the CFD model. Dekeyser et al [15] evaluated an orchard spraying system based on CFD and laboratory experiments.…”

Automation and robotics in the cultivation of pome fruit: Where do we stand today?

“…To further decrease the used amount of plant protection products, research has been done on quantifying and modeling spraying flows and drift. Duga et al (2017) developed a 3D computational fluid dynamics (CFD) model to calculate the drift of different types of nozzles, with the overall conclusion that under all circumstances drift reducing nozzles reduced the drifting distance by 50%. Holterman et al (2017) captured 10 years of data to establish an empirical model for predicting the pesticide spray drift in pome fruit orchards.…”

“…in DeMoor et al (2000), or more advanced leaf wetness sensors, such as inFoqué et al (2018). To further decrease the used amount of plant protection products, research has been done on quantifying and modeling spraying flows and drift Duga et al (2017). developed a 3D computational fluid dynamics (CFD) model to calculate the drift of different types of nozzles, with the overall conclusion that under all circumstances drift reducing nozzles reduced the drifting distance by 50% Holterman et al (2017).…”

Influence of Droplet Size on Spray Deposition and Weed Control Using Glyphosate

“…2021 Coarse droplets cannot easily adhere to plant parts. They also provide a low coverage rate due to the tendency to ricochet (Balsari et al, 2017;Duga et al, 2017) or to fragment on impact with the leaf surface (Boukhalfa et al, 2014). This can lead to a decrease in the biological efficiency of the herbicides as the droplet size increases (Knoche, 1994;Smith et al, 2000;Creech et al, 2015), even for mobile herbicides such as glyphosate.…”