Hoverfly use for Pollination of Commercial Soft Fruit Crops

To apply for this project please visit the LIDo website: https://www.lido-dtp.ac.uk/apply

This PhD project is a collaboration between the Natural Resources Institute (NRI, https://www.nri.org/), a multi-disciplinary research institute within the University of Greenwich, and Olombria (https://www.flypollination.com/), an early-stage AgTech SME, and is focused on the utilisation of advanced computer technology to aid in the pollination of commercial soft fruit crops.

Pollination of crops is essential for production of seeds, fruits, vegetables, and plant oils, generating billions of dollars annually in agriculture. The UK berry market itself was valued at £1.27 billion and is growing. However, wild pollination of fruit is often inadequate, especially at certain times of year and in covered crop systems. Insufficient pollination results in lower quality, and misshapen fruit, which is a major industry constraint. For example, some farms experience 12%-17% fruit waste from misshapes.

Olombria are developing a commercial hoverfly pollination system using attractive odour lures under AI control. Aphidophagous hoverflies offer several advantages over bumblebees/honeybees as commercial crop pollinators:

           - Lower hazard risk (bee stings)

           - Biocontrol of pest species from larvae feeding

           - Increased crop yield

Using an interdisciplinary approach, it should be possible to amplify hoverfly efficacy significantly from base levels. Hoverflies are known to learn that certain flowers offer superior nectar rewards and are thus more attracted towards them and are also known to be attracted to areas of high pest infestation for ovipositioning purposes.

This project will use an interdisciplinary approach to explore the potential to optimise pollinator behaviour and would appeal to prospective students with an interest in:

1. Entomology and Chemical Ecology. Using volatile capture and chemical analysis techniques. (GC-MS, electroantennography (EAG), LC-MS etc.).

2. Working with Olombria’s existing AI, developing machine learning algorithms.

3. Running field and polytunnel pollination trials at Olombria’s testing sites.

4. Insect behaviour trials, working in wind tunnels and utilising NRI’s advanced 3D tracking facilities to assess hoverfly response to odour and visual cues.

Although desirable it is not expected that the student would have experience in all disciplines, training will be provided as appropriate, however they should have experience in at least one of the following:

- Chemical Analysis (GC, HPLC etc.).

- Entomology or general Ecology (preferably behavioural studies).

- Computer programming/machine learning

This unique opportunity allows for the experience of both academic and industry environments, with world class facilities available at both. The NRI hosts a DEFRA licensed insectary facility, quarantine glasshouses, a range of state-of-the-art chemical analytical suites in addition to dedicated facilities for insect behaviour and electrophysiology. Olombria has dedicated insect rearing and lab facilities as well as access to large-scale field sites for outdoor testing as well as machine learning and artificial intelligence experts to train and advise.

The wide scope and interdisciplinary nature of this project would allow the student to influence the direction of research, take part in international conferences and obtain a wide variety of transferable skills for their future careers. 

To apply for this project please visit the LIDo website: https://www.lido-dtp.ac.uk/apply