Award details

Systems approaches to crop improvement

Reference	BBS/E/C/00005205
Principal Investigator / Supervisor	Dr Mikhail Semenov
Co-Investigators / Co-Supervisors
Institution	Rothamsted Research
Department	Rothamsted Research Department
Funding type	Research
Value (£)	707,771
Status	Completed
Type	Institute Project
Start date	01/04/2012
End date	31/03/2017
Duration	59 months

Abstract

Crop growth is a complex process, which includes many components interacting with the environment in a non-linear way. The effect of changes in a single trait on crop performance can be determined empirically in a field experiment assuming that suitable plant material is available. However, crop responses will also depend on environmental conditions due to large and variable G(cultivars) xE (envioronment) interactions. Determining experimentally how new plant characteristics, either individually or in combination, will affect crop performance under a wide range of target environments is an intractable practical task. Recent advances in crop modelling have demonstrated that process-based crop models, based on physiological and environmental parameters, can be used to explore GxE relationships, to deconvolute complex wheat traits, such as traits for resource-use efficiency, and explore wheat performance under climate change. The overall aim of the project is to develop a modelling framework to predict performance of wheat ideotypes in target environments including climate change and to identify key traits for crop genetic improvement. Direct Objectives and Deliverables: 1. Develop a framework for a rational design of wheat ideotypes for target environments. i. Sirius wheat simulation model refined, incorporating effects of extreme weather events on wheat, in particular, the effect of high temperature on wheat yield around anthesis and the latest data from the Free-Air CO2 Enrichment (FACE) experiments. ii. Methodology developed for probabilistic assessment of climate change impacts on wheat based on ensembles of climate predictions. 2. Identify key wheat traits for improvement and estimate the yield potential under climate change i. Identified target traits for improvement in resource-use efficiency and wheat resilience under climate change ii. Ultra-high yielding wheat ideotypes optimized in silico for future climate change

Summary

unavailable

Committee	Not funded via Committee
Research Topics	Crop Science, Plant Science, Systems Biology
Research Priority	X – Research Priority information not available
Research Initiative	X - not in an Initiative
Funding Scheme	X – not Funded via a specific Funding Scheme

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