Dr Daniel Leybourne

Research Fellow

Curriculum vitae

Evolution, Ecology and Behaviour. Institute of Infection, Veterinary and Ecological Sciences

The University of Liverpool

Updating a wheat bulb fly risk prediction model (Agriculture and Horticulture Development Board project; 2020; Contributor; ADAS)

Overview of the wheat bulb fly life-cycle; Leybourne, Storer et al., 2022. Image created in bioRender
Project Overview:
Wheat bulb fly, Delia coarctata, is a significant herbivorous insect pest of winter wheat in the UK and crop risk can fluctuate year-on-year. Wheat bulb fly larvae are a significant threat to  crops between January and April when the insect larvae burrow into developing shoots. There are no foliar insecticide sprays available for wheat bulb fly control, and a limited understanding of insect biology and ecology means that few tried and tested sustainable insect management practices are available. Therefore, control of wheat bulb fly is primarily reliant on the application of insecticide as a seed treatment. However, as this treatment must be applied before a crop is planted it is important that annual wheat bulb fly risk can be determined prior to planting so that growers are aware of the potential wheat bulb fly risk and can apply seed treatments if needed.

Currently, annual wheat bulb fly risk is determined through soil sampling and egg counts. These annual surveys generally occur between September and October each year. Although this information is important for providing growers with an idea of the annual wheat bulb fly risk, these surveys are often carried out during, or after, most winter wheat crops are planted. Predictive modelling was used in this project to develop an annual wheat bulb fly prediction model that can be run in August each year, producing a wheat bulb fly risk prediction tool that could be run prior to crop planting. The project report and associated publications are highlighted below.
Developing the foundations for a Decision Support System
The results of this project were combined with another predictive model, a model to estimate shoot number production in winter wheat, and a revision of the pest thresholds to develop the foundations for an eventual decision support system (DSS) that could be used to assist with wheat bulb fly management in the UK.

The image below provides an overview of this DSS, which would work by following the process below:
  1. Use the pest level prediction model developed in this project to estimate wheat bulb fly risk;
  2. Compare the predicted numbers with the updated thresholds and determine whether the estimated wheat bulb fly population represents a risk to the crop;
  3. Use the additional shoot number prediction model to estimate tiller production;
  4. Determine whether the wheat crop would produce sufficient tillers to be able to naturally tolerate the estimated wheat bulb fly numbers;
  5. If natural tolerance will likely not be achieved, consider a management intervention, such as:
    1. Adjust sowing conditions to increase natural tolerance,
    2. Apply a seed treatment to a late-sown crop,
    3. Adjust the crop in the rotation

Overview of the proposed DSS; Leybourne, Storer et al., 2022. Image created using bioRender


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

Daniel J. Leybourne, Kate E. Storer, Pete Berry, Steve Ellis

Annals of Applied Biology, vol. 180, 2022, pp. 118-131

Updating a wheat bulb fly risk prediction model

D Leybourne, K Storer, S Ellis, P Berry



Follow this website

You need to create an Owlstown account to follow this website.

Sign up

Already an Owlstown member?

Log in