A track-sprayer combined with a high-speed camera were used to visualize and identify droplet impaction outcomes for three formulations (water, 0.1% LI 700® (lecithin, a mixture of soya oils, propionic acid and surfactants) in water and 0.1% Pulse® (non-ionic surfactant, trisiloxane ethoxylate) in water) on four plant species (bean (Vicia faba L.), avocado (Persea americana L.), barnyard grass (Echinochloa crus-galli L. P. Beauv.) and cabbage (Brassica oleracea L.)) selected to represent a wide range of leaf surface characters. Droplet sizes and velocities were measured by image analysis and a multiple hypothesis tracking algorithm. Impaction outcomes were categorized into adhesion, bounce, or shatter. The probability of each outcome was estimated from logistic regression models related to the dimensionless Weber number. This approach is in contrast to various deterministic threshold criteria for droplet bounce or shatter that have been used to model droplet impaction events on leaves. It also provides a simple visual and numerical presentation of the complexity of impaction processes, and the relative influence of leaf surface character versus formulation for droplets with different impaction energies.
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