Investment

Sorghum and maize crops across Queensland Gulf, Tablelands and Burdekin regions in the 2019-20 season experienced injury and yield losses from FAW, a major pest new to Australia.

This project proposes, for the first time in Australia, to bring together the expertise of entomologists, agronomists, biometricians and modellers to develop a conceptual workflow to establish, evaluate, disseminate and reiterate FAW management guidelines for industry with reference to specific regional cropping systems. while there are overseas thresholds described for transgenic, Bt maize, these are inappropriate to extrapolate directly for use in Australian crops. Initially, existing crop models will be reviewed for their capacity to simulate yield losses from FAW injury across Australia. Experimental design will be guided by the model output with the goal of parameterising, verifying and evaluating models of FAW-sorghum/maize systems.

Controlled environment and field trials will be undertaken to characterise the impact of FAW population density on vegetative and reproductive stages of sorghum and maize in WA and Qld. Detailed on-station crop trials (treatments guided by initial modelling, FAW impact evaluation and previous overseas research) will statistically model yield impacts and validate the crop simulation models. A key site in the Lockyer Valley (Qld) will host a factorial experiment combining both artificial defoliation and FAW infestation. Additional sites in Qld and Kununurra, WA will address specific crop-loss components and validation of the crop loss model.

Over the life of the project, an iterative approach to the entomology, agronomy and crop modelling research will ensure that reliable methodologies are developed and the suite of economically important FAW-crop scenario combinations are evaluated. Ultimately, the validated APSIM crop model will be used to simulate a range of likely what if FAW infestation(s) injury for regionally specific cropping systems. A calculator that uses farmers own data and a database of crop simulations to dynamically predict economic control thresholds.