Drift from field crop sprayers using an integrated approach

General introduction

This project studies the phenomenon of spray drift from field crop sprayers using an integrated approach. Which are the most important factors affecting drift? Can we quantify these factors to develop an accurate drift prediction model? The aim of this project is to deliver drift reducing measures and advice to the stakeholders involved.

Spray drift is the quantity of plant protection product that is carried out of the sprayed area by the action of air currents during the application process. Spray drift from agricultural pesticides can cause crop protection chemicals to be deposited in undesirable areas. This can cause serious consequences such as damage to sensitive adjoining crops and susceptible off-target areas, environmental contamination, illegal pesticide residues, and health risks to animals and people. For these reasons, spray drift and risks connected with application of pesticides in agriculture are attracting increased attention from the general public as well as the scientific community.

Research approach

We perform indirect (spray quality and wind tunnel measurements) and direct drift experiments  (field drift experiments). We then develop drift prediction models (using 'Computational Fluid Dynamics') to study the effect of spray application technique, droplet characteristics, buffer zones, meteorological conditions, spray liquid properties, border structures and crop characteristics on drift from field crop sprayers. These models make it possible for us to independently adjust and study all of the parameters that affect drift. A spray drift risk assessment is performed to evaluate the effect of pesticide spray drift on the environment and humans.

Relevance/Valorisation

This project results in drift measuring protocols and advanced measuring techniques, a unique drift database useful for spray drift risk assessments, and spray drift models. A validated 3-D Computational Fluid Dynamics (CFD) mechanistic drift model is developed which can be used for a systemic study of different drift influencing factors. This model is reduced to a fast 2-D diffusion advection model useful as a hands-on drift prediction tool. We develop measures to minimize the negative effects of spray applications on the environment. The broad communication of these results through national and international channels increases awareness of good agricultural practices and encourages the use of these practices.