Minimising Environmental and Public Health Risk of Pesticide Application Through Understanding the Droplet-Canopy Interface

Accurate placement of pesticide droplets on to crop and weed surfaces is a key step in controlling pests and weeds in agricultural production systems. Droplets impact on plant surfaces, depositing pesticides that give protective coverage on crops and destructive coverage for insect or fungi pests and weeds. Coverage is complex and is determined by a multitude of interactions between factors such as size and density of spray droplets, relative humidity and turbulence of the air through which the droplets travel, and the physical characteristics of the target plant leaves, branches and stems that go to make up the architecture of their canopy. There are, however, concerns over the effect of pesticides on the environment and public health. This thesis combines three dimensional (3-D) computer modelling techniques, physical measurements of droplet movement and impact on a canopy in a wind tunnel and risk management techniques to maximise the effectiveness of pesticides and enable risks to public health and the environment from agricultural spraying activities to be minimised. L-studio, a Windows based software environment for creating simulation models of plant architecture was used in this study. A particle trajectory model, based on the combined ballistic and random-walk approach proposed by Mokeba et al. (1997) and Cox et al. (2000) was used to model spray droplet movement. Algorithms were included in the spray model to account for evaporation of droplets, entrained air and movement of air around the spray, collection efficiency, and droplet splash. Existing functional-structural plant models of cotton (Gossypium hirsutum L.) and sow thistle (Sonchus oleraceus L.) and a static empirical model of immature grass weeds have been combined with the spray model. An environmental program has been used to take the location of the leaves in 3-D space from the plant model and determine if spray droplets will impact on them. Wind tunnel measurements were made to determine initial droplet properties (droplet size, velocity, trajectory, density and fluid properties) and droplet impact characteristics (retention and splash). The results from these measurements were then used to define parameters within the spray model. Additional experiments to measure spray drift and spray deposition on various plant surfaces within the wind tunnel were used to evaluate the combined spray and plant architecture model. The combined spray and plant architectural model developed and evaluated in this thesis has provided a new method to study the influence of plant architecture on spray distribution. This work has shown that 3-D plant architecture can influence the amount of spray depositing on leaf surfaces. Deposition on plant surfaces was also found to increase with decreased wind speed and reduced release height. Droplet size did not have a significant influence on spray deposition onto broadleaf plants such as cotton or sow thistle. There was however, a tendency for fine sprays to give a higher deposit on small, narrow grass leaves. Spray drift was found to increase with decreasing droplet size, increasing the range of droplet sizes generated by a nozzle, decreasing sheet velocity (initial velocity of droplets), increasing wind speed, increasing (difference between dry and wet bulb temperature), decreasing liquid density and increasing release height. The combined spray and architectural model has also enabled the study of how effects such as droplet splash and retention can influence the distribution of the spray. In this study it was found that there was little difference in modelled spray drift, amount of spray on the ground or amount of spray on the cotton plant between situations where most droplets splash on impact and where no droplet splash on impact. Although the total amount of spray retained on the plant surface was similar for both situations, it was found that there were more droplets on the plant under the splash scenario leading to better coverage of the spray over the plant. These results indicate that the majority of the smaller splash droplets were re-distributed onto other parts of the plant rather than becoming lost as spray drift or ground deposit. Decision trees have been used in this thesis to characterise the benefits and risks from pesticide applications. Results from model simulations and/or physical measurements are used to estimate the relative proportion of the spray depositing on plant surfaces, depositing on the ground and drifting away from the treatment area. These deposition results give a measure of pesticide exposure that can be incorporated into the risk management framework to investigate the influence of various application scenarios. The applicability of this approach is shown by the example of endosulfan sprayed on cotton to control Helicoverpa spp. The decision tree model can be used to quickly compare different scenarios, such as deciding which application method should be used. It can be used to effectively aid spray decisions to maximise the effectiveness of pesticides and minimise risks to public health and the environment from agricultural spraying activities.