Ecophysiological and molecular mechanisms of weed seed bank persistence

Professor Gerhard Leubner, School for Life Sciences and the Environment, Royal Holloway University of London
Dr Kazumi Nakabayashi, School for Life Sciences and the Environment, Royal Holloway University of London
Dr Chun Liu and Anne Seville, Syngenta Weed Control Research, Jealott’s Hill International Research Centre (Bracknell, UK)

project details

Weeds are a major threat to modern agriculture. For example, blackgrass is considered the most destructive cereal weed in European agriculture. The overall aim of this project is to gain insight into fundamental mechanisms of weed adaptation to provide sustainable solutions for weed management. To address this challenge with an interdisciplinary approach, the supervisory team is from Royal Holloway University of London's Seed Science group (Prof Gerhard Leubner and Dr Kazumi Nakabayashi) and Syngenta's Weed Control Research unit (Dr Chun Liu and Anne Seville) at Syngenta's Jeallot's Hill International Research Centre (Bracknell, UK). Seed dormancy in agricultural weeds is the key factor regulating weed emergence patterns in the field. Together with seed viability and persistence, it affects the behaviour of the weed seed bank, which is of vital importance to designing effective weed control strategies.

This Industrial CASE PhD student project will combine comparative ecophysiological analysis of blackgrass seed lots using population-based hydrothermal-time modelling of dormancy, longevity responses to abiotic stresses and chemicals with the molecular analysis of the underpinning mechanisms by RT-qPCR, RNAseq, epigenetics and hormone quantification. For training and support the student will be integrated into the Seed Science group which will provide further expert support in multidisciplinary methods such as biomechanical engineering, 3D imaging, transcriptome, microscopy and biochemistry.

The student will spend at least 3 months at Syngenta. During the placement, the student will be introduced into the principles of mathematical modelling and model types as the project aims to transfer the investigated mechanisms for informing the development of more effective emergence models and control strategies.

eligibility and application

Applicants must hold, or be expected to achieve, a first or high upper second-class undergraduate honours degree or equivalent (for example BA, BSc, MSci) or a Masters degree in a relevant subject. This project is funded by a 4-year BBSRC studentship, applicants should ensure they have understood the funding eligibility criteria for these studentships. Unfortunately international students are not eligible for programme funding on this project.

For more information regarding the project, please contact Professor Gerhard Leubner

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