Development of a pest threshold decision support system for minimising damage to winter wheat from wheat bulb fly, Delia coarctata

In this article we describe two predictive models that can be used for the integrated management of wheat bulb fly. Our first model is a pest level prediction model and our second model predicts the number of shoots a winter wheat crop will achieve by the terminal spikelet developmental stage. We revise and update current wheat bulb fly damage thresholds and combine this with our two models to devise a tolerance-based decision support system that can be used to minimise the risk of crop damage by wheat bulb fly. ![Figure][1] Summary Wheat bulb fly, Delia coarctata, is an important pest of winter wheat in the UK, causing significant damage of up to 4 t ha-1. Accepted population thresholds for D. coarctata are 250 eggs m-2 for crops sown up to the end of October and 100 eggs m-2 for crops sown from November. Fields with populations of D. coarctata that exceed the thresholds are at higher risk of experiencing economically damaging pest infestations. In the UK, recent withdrawal of insecticides means that only a seed treatment is available for chemical control of D. coarctata, however this is only effective for late-sown crops (November onwards) and accurate estimations of annual population levels are required to ensure a seed treatment is applied if needed. As a result of the lack of post-drilling control strategies, the management of D. coarctata is becoming increasingly reliant on non-chemical methods of control. Control strategies that are effective in managing similar stem-boring pests of wheat include sowing earlier and using higher seed rates to produce crops with more shoots and greater tolerance to shoot damage. In this study we develop two predictive models that can be used for integrated D. coarctata management. The first is an updated pest level prediction model that predicts D. coarctata populations from meteorological parameters with a predictive accuracy of 70%, which represents a significant improvement on the previous D. coarctata population prediction model. Our second model predicts the maximum number of shoots for a winter wheat crop that would be expected at the terminal spikelet development stage. This shoot number model uses information about the thermal time from plant emergence to terminal spikelet, leaf phyllochron length, plant population, and sowing date to predict the degree of tolerance a crop will have against D. coarctata. The shoot number model was calibrated against data collected from five field experiments and tested against data from four experiments. Model testing demonstrated that the shoot number model has a predictive accuracy of 70%. A decision support system using these two models for the sustainable management of D. coarcata risk is described. ### Competing Interest Statement The authors have declared no competing interest. [1]: pending:yes