Sensing the gap: Expressions of crop stress from molecular to landscape scales

Lead Research Organisation: University of Sheffield
Department Name: School of Biosciences

Abstract

Food security is one of the most pressing challenges that humans will face this century. A growing population, shifting dietary habits and a changing climate are placing unprecedented pressure on crop production. Future crops must therefore be resilient to climate change and (a)biotic stresses. Whilst modern crop varieties have been bred for high yields, this has led to a reliance on a diminished number of crop species and varieties, resulting in a vulnerability to pests and disease and a changing climate. Leveraging the genetic diversity that exists across different crop cultivars and landraces offers an opportunity to sustainably increase food production and close yield gaps by ensuring that crops are optimised to current and future environments.

However, identifying the molecular mechanisms that underpin crop physiological responses to environmental stress is complex. Crops express phenotypic traits according to interactions between their genomes, the environment and how they are managed. Identifying how a given crop cultivar will respond to different environmental conditions is key to guiding breeding programmes. Phenotyping studies are underpinned by testing how crop genomes respond to environmental conditions, and how these conditions affects overall yields and the resilience of the crops to stress. However, this is resource intensive and limited in scope by the time and environment that the crops are grown under.

There is a critical need to harness novel remote sensing techniques and state-of-the-art modelling approaches to model how genetically-regulated crop biochemical, structural and physiological traits affect yields, under different environmental scenarios. Closing this genotype to field-scale gap requires robust scaling methodologies that can be deployed at high throughputs. Leveraging our understanding of genetic controls on physiological traits and fluxes will enhance our ability to predict how crop genomes will respond under different environmental conditions.

Publications

10 25 50
 
Description EPSRC DTP Studentship - A combined remote sensing and machine learning approach to monitoring crop stress and predicting crop yield
Amount £0 (GBP)
Organisation Engineering and Physical Sciences Research Council (EPSRC) 
Sector Public
Country United Kingdom
Start 09/2023 
End 10/2026
 
Description PV4PLANTS - AgriPV system with climate, water and light spectrum control for safe, healthier and improved crops production
Amount £742,789 (GBP)
Funding ID 10049073 
Organisation European Commission 
Sector Public
Country Belgium
Start 01/2023 
End 12/2026
 
Description COST Action CA22136 - PANGEOS 
Organisation University of Barcelona
Country Spain 
Sector Academic/University 
PI Contribution I lead Working Group 3 within the PANGEOS COST Action. The COST Action is a networking collaboration which brings together researchers from all over Europe. I recently organised a workshop in Lisbon which was attended by 20 people to discuss research on remote sensing and vegetation modelling.
Collaborator Contribution Other members of the COST Action come together to share knowledge and research with the objective of writing publications.
Impact One training school, a workshop and a small conference
Start Year 2024