Optimising sticky traps for Western Flower Thrips and Whitefly using visual modelling.

This project tackles the major agricultural pests Wester flower thrips (WFT, Frankliniella occiidentalis) and Greenhouse Whitefly (GW, Trialeurodes vaporariorum) by developing optimised sticky traps for improved monitoring and mass trapping. We will apply a design process that measures a pest's-eye-view of trap appearance to identify the most attractive and stimulating trap design. We will develop designs that use colour and pattern to target multiple pests simultaneously. Proposed designs will be evaluated in lab and field trials in crops of strawberries, tomatoes, and peppers. Finally we will identify biodegradable papers, inks and glues to develop a low-cost low-waste solution. Optimised designs and carefully selected controls will be tested in experimental field trials.

This project tackles the major agricultural pests Wester flower thrips (WFT, Frankliniella occiidentalis) and Greenhouse Whitefly (GW, Trialeurodes vaporariorum) by developing optimised sticky traps for improved monitoring and mass trapping. We will apply a design process that uses visual modelling of trap appearance from the pests' perspective to optimise the attractiveness of traps. Specifically, we will develop designs that use colour and pattern to target multiple pests and identify biodegradable materials to develop a low-cost low-waste solution. Optimised designs and carefully selected controls will be tested in experimental field trials in crops of strawberries, tomatoes, and peppers.

Through more accurate monitoring of pest populations, the project improves pest detection and forecasting. By trapping target pests at a higher rate than current sticky traps, the product developed could also be used for environmentally friendly mass trapping control using sustainable low-impact materials. There is future potential too for a highly efficient multi-pest trap becoming a key component of an integrated pest management solution that provides automated monitoring for prediction and targeted control.