4.7 Article

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

Journal

BIOSYSTEMS ENGINEERING
Volume 154, Issue -, Pages 62-75

Publisher

ACADEMIC PRESS INC ELSEVIER SCIENCE
DOI: 10.1016/j.biosystemseng.2016.10.010

Keywords

Drift reduction; Nozzle; Tree model; Lagrangian model; Fan speed; Plant protection product

Funding

  1. Institute for the Promotion of Innovation by Science and Technology in Flanders [IWT 080528]

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Pesticides play an important role in providing high crop yields, by minimising the risks associated with pests but some of the sprayed product may move beyond the intended target and result in drift. Modelling approaches can help understand the behaviour of spray drift using computer simulations. However, modelling drift from orchard spraying presents particular challenges: (1) the moving spray interacts with the canopy before drifting outside the target area; (2) the vertical wind profile in the orchard is different to neighbouring fields where there is different vegetation; (3) the moving air jet from the air assistance cannot be ignored because the airspeed of the fan is usually higher than the wind speed. This work presents a three-dimensional (3D) computational fluid dynamics (CFD) model of spray drift from orchard sprayers that considers tree architecture, canopy wind flow and the movement of the sprayer to calculate sedimenting and airborne drift; thus tackling the challenges listed above. The model was validated against drift measurements from an apple orchard with different nozzles arrangements. The model was then used to evaluate the effect of drift reducing nozzles and fan airspeed on drift. The model predicted that drift reducing nozzles reduced the drifting distance by 50%, but increased near-tree ground deposition. This increase in ground deposition can be avoided whilst retaining the reduction in the drifting distance, by using a combination of drift reducing and standard nozzles. A reduced sprayer airflow can further reduce drift. (C) 2016 IAgrE. Published by Elsevier Ltd. All rights reserved.

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