Improving prediction of wheat response to climate change

Improving prediction of wheat response to climate change

Project summary

Wheat is our primary arable crop and one of the big three arable crops across the world. It is a temperate grass which is sensitive to temperature and day-length for the regulation of key developmental stages. Whilst some of the details of these regulation mechanisms are known, knowledge is limited. As a result, skill in prediction of wheat response to climate change is also limited.

This project will investigate the specific growth stages which are showing temperature sensitivity at the phenotypic and molecular level. A combination of field and controlled conditions analysis will enable the role of variable temperatures to be investigated without the compounding effect of day-length. The data from the phenotypic assessment will be used to guide genetic dissection of the traits as well as provide critical parameters to constrain crop models. The realistic data-driven development of these models will enable sound future climate predictions to be made, which in turn can inform breeding on how to maximise yield whilst developing sustainable farming practices.

Project description

Wheat is the major arable crop in the UK and one of the big three arable crops across the world. However, surprisingly little is known about how wheat responds to temperature and next to nothing is known about the role of variable temperatures, such as those experienced in the field, in regulating growth and development of the wheat plant. This project will start to address this knowledge gap with the aim of developing an understanding of temperature responses such that predictions regarding wheat growth in the field can be made for future climate scenarios.

The project will combine in-field phenotyping of wheat plants for developmental (establishment, key developmental stages, apex transitions etc) and environmental parameters (day-length, temperature, soil moisture, light intensity) with dissection of the observed responses via controlled cabinet experiments. This will include monitoring the growth responses under variable temperatures whilst maintaining constant photoperiods, defining the critical developmental responses and conducting RNA-seq to develop a transcriptional profile of the response. Using the transcriptional profile key gene responses will be identified and the allelic variation of these genes assessed in diverse wheat genotype panels, including the Watkins collection.

The environmental parameters will be used to constrain a wheat-specific mathematical model, developed in A. Challinor’s group, which will be tested against the measured phenotypes from the same field. With this newly constrained model growth predictions will be made for different environments within the UK, which will be assessed through collaboration with wheat breeders (L.Dixon already has projects with UK wheat breeders) and ultimately used to make predictions for future climate scenarios.


This project will provide training in the collection of environmental parameters from a wide range of instrumentation types along with excellent training in plant development and genetics. The field experiments will develop skills in experimental design, multi-parameter analysis and excellent team and individual working skills. The PhD student will have access to a range of training courses designed to facilitate skills development and will be expected to present the outcomes of this project at both national and international conferences.

Research context and partners

Dr Dixon’s research specialises understanding how environmental parameters regulate wheat growth and the interaction of these with the underlying genetic and molecular mechanisms. Her research focuses on identifying the key aspects of the crops biology to provide translation into agriculture to enhance the sustainability of arable farming.  Prof. Challinor’s group meet weekly to discuss and develop crop modelling approaches, and the student will be an integral part of this group.

Co-supervisory meetings will happen every 3 months. Through the DTP the student will be embedded into the NERC community at Leeds, and will link with the university-wide Global Food and Environment Institute.


  1. Dixon, Karsai, Kiss, Adamski, Liu, Yang, Allard, Boden, Griffiths (2019) VERNALIZATION1 controls developmental responses of winter wheat under high ambient temperaturesDevelopment 146, 3
  2. Arnell NW, Lowe JA, Challinor AJ, Osborn TJ. Global and regional impacts of climate change at different levels of global temperature increase. Climatic Change. 155(3), pp. 377-391
  3. Droutsas I, Challinor AJ, Swiderski M, Semenov MA. New modelling technique for improving crop model performance – Application to the GLAM model. Environmental Modelling and Software. 118, pp. 187-200
  4. Montesino-San Martin M, Wallach D, Olesen JE, Challinor AJ, Hoffman MP, Koehler AK, Roetter RP, Porter JR. Data requirements for crop modelling-Applying the learning curve approach to the simulation of winter wheat flowering time under climate change. European Journal of Agronomy. 95, pp. 33-44