Systems approaches to crop improvement
Lead Research Organisation:
Rothamsted Research
Department Name: UNLISTED
Abstract
Abstracts are not currently available in GtR for all funded research. This is normally because the abstract was not required at the time of proposal submission, but may be because it included sensitive information such as personal details.
Technical Summary
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
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
Planned Impact
unavailable
Organisations
People |
ORCID iD |
| Mikhail Semenov (Principal Investigator) |
Publications
Barber H
(2017)
Temporally and Genetically Discrete Periods of Wheat Sensitivity to High Temperature
in Frontiers in Plant Science
Bo V
(2014)
Discovering study-specific gene regulatory networks.
in PloS one
Cammarano D
(2016)
Uncertainty of wheat water use: Simulated patterns and sensitivity to temperature and CO2
in Field Crops Research
Clare FC
(2016)
Climate forcing of an emerging pathogenic fungus across a montane multi-host community.
in Philosophical transactions of the Royal Society of London. Series B, Biological sciences
Kauserud H
(2013)
Reply to Gange et al.: Climate-driven changes in the fungal fruiting season in the United Kingdom.
in Proceedings of the National Academy of Sciences of the United States of America
Kauserud H
(2012)
Warming-induced shift in European mushroom fruiting phenology.
in Proceedings of the National Academy of Sciences of the United States of America
Lake I
(2017)
Climate Change and Future Pollen Allergy in Europe
in Environmental Health Perspectives
Liu B
(2016)
Similar estimates of temperature impacts on global wheat yield by three independent methods
in Nature Climate Change
Maiorano A
(2017)
Crop model improvement reduces the uncertainty of the response to temperature of multi-model ensembles
in Field Crops Research
| Description | RRes developed and refined the Sirius wheat simulation model to understand impact of climate change on wheat yield and identify traits for wheat improvement in target environments. RRes actively participated in international model inter-comparison and improvement. The following are illustrations of research output in Systems Approaches to Crop Improvement. ADAPTING WHEAT IN EUROPE FOR CLIMATE CHANGE. Increasing cereal yield is needed to meet the projected increased demand for world food supply of about 70% by 2050. Sirius, a process-based model for wheat, was used to estimate yield potential for wheat ideotypes optimized for future climatic projections for wheat growing areas of Europe. It was predicted that the detrimental effect of drought stress on yield would be decreased due to enhanced tailoring of phenology to future weather patterns, and due to genetic improvements in the response of photosynthesis and green leaf duration to water shortage. Yield advances could be made through extending maturation and thereby improve resource capture and partitioning. However, the model predicted an increase in frequency of heat stress at meiosis and anthesis. Controlled environment experiments quantify the effects of heat and drought at booting and flowering on grain numbers and potential grain size. A current adaptation of wheat to areas of Europe with hotter and drier summers is a quicker maturation which helps to escape from excessive stress, but results in lower yields. To increase yield potential and to respond to climate change, increased tolerance to heat and drought stress should remain priorities for the genetic improvement of wheat. ADVERSE WEATHER CONDITIONS FOR EUROPEAN WHEAT WILL BECOME MORE FREQUENT. Europe is the largest producer of wheat, the second most widely grown cereal crop after rice. The increased occurrence and magnitude of adverse and extreme agroclimatic events are considered a major threat for wheat production. We present an analysis that accounts for a range of adverse weather events that might significantly affect wheat yield in Europe. For this purpose, we analysed changes in the frequency of 11 adverse weather events. Using climate scenarios based on the most recent ensemble of climate models and greenhouse gases emission estimates, we assessed the probability of single and multiple adverse events occurring within one season. We showed that the occurrence of adverse conditions for the main European wheat-growing areas might substantially increase by 2060 compared to the present (1981-2010). This is likely to result in more frequent crop failure across Europe. RISING TEMPERATURES REDUCE GLOBAL WHEAT PRODUCTION. Crop models are essential tools for assessing the threat of climate change to local and global food production. Present models used to predict wheat grain yield are highly uncertain when simulating how crops respond to temperature. Here we systematically tested 30 different wheat crop models of the AgMIP Project against field experiments in which growing season mean temperatures ranged from 15C to 32C, including experiments with artificial heating. Many models simulated yields well, but were less accurate at higher temperatures. The model ensemble median was consistently more accurate in simulating the crop temperature response than any single model, regardless of the input information used. Extrapolating the model ensemble temperature response indicates that warming is already slowing yield gains at a majority of wheat-growing locations. Global wheat production is estimated to fall by 6% for each 1C of further temperature increase and become more variable over space and time. |
| Exploitation Route | Sirius wheat model is available to academics community for research. |
| Sectors | Agriculture Food and Drink Environment |
| Description | The results of this project contributed to preparation of the EU Report on Climate change, impacts and vulnerability in Europe 2016 |
| First Year Of Impact | 2016 |
| Sector | Agriculture, Food and Drink,Environment |
| Title | ELPIS |
| Description | ELPIS is a dataset of site parameters for the LARS-WG weather generator for Europe. |
| Type Of Material | Database/Collection of data |
| Year Produced | 2012 |
| Provided To Others? | Yes |
| Impact | ELPIS has been used to generate local-scale climate scenarios for Europe using LARS-WG and climate projections from the CMIP5 ensemble. These scenarios have been used in many projects including MACSUR. |
| URL | http://www.rothamsted.ac.uk/mas-models/larswg |
| Title | LARS-WG stochastic weather generator |
| Description | LARS-WG 6.0, a stochastic weather generator, is a computationally inexpensive downscaling tool to generate local scale climate scenarios based on global or regional climate models for impact assessments of climate change. LARS-WG has been used in more than 75 countries for research and education. The current version of LARS-WG incorporates climate projections from the CMIP5 ensemble used in the IPCC Fifth Assessment Report. LARS-WG has been well validated in diverse climates around the world. |
| Type Of Technology | Software |
| Year Produced | 2021 |
| Impact | LARS-WG 6.0, a stochastic weather generator, is a computationally inexpensive downscaling tool to generate local scale climate scenarios based on global or regional climate models for impact assessments of climate change. LARS-WG has been used in more than 75 countries for research and education. |
| URL | https://zenodo.org/record/4572752 |
| Title | LARS-WG stochastic weather generator |
| Description | LARS-WG is a model simulating time-series of daily weather at a single site. It can be used: 1. to generate long time-series suitable for the assessment of agricultural and hydrological risk; 2. to provide the means of extending the simulation of weather to unobserved locations; 3. to serve as a computationally inexpensive tool to produce daily site-specific climate scenarios for impact assessments of climate change. LARS-WG version 5.0 includes climate scenarios based on 15 Global Climate Models (GCMs) which have been used in the IPCC 4AR (2007). This large dataset of future climate projections was produced by leading modelling groups worldwide who performed a set of coordinated climate experiments in which GCMs have been run for a common set of experiments and emission scenarios. Multi-model ensembles allow to explore the uncertainty in climate predictions resulting from structural differences in the global climate model design as well as uncertainty in variations of initial conditions or model parameters. The new version also improves simulation of extreme weather events, such as extreme daily precipitation, long dry spells and heat waves. LARS-WG has been well validated in diverse climates around the world. |
| Type Of Technology | Software |
| Year Produced | 2015 |
| Impact | LARS-WG has been used in more than 65 countries for research and in several Universities as an educational tool. Climate scenarios generated by LARS-WG have been used in the impact assessments of climate change for the IPCC Assessment Report 5. |
| URL | http://www.rothamsted.ac.uk/mas-models/larswg |
| Title | SIRIUS wheat simulation model |
| Description | Sirius is a wheat simulation model that calculates biomass from intercepted photosynthetically active radiation and grain growth from simple partitioning rules. Leaf area index (LAI) is developed from a simple thermal time sub-model. Phenological development is calculated from the mainstem leaf appearance rate and final leaf number, with the latter determined by responses to daylength and vernalisation. Effects of water and N deficits are calculated through their influences on LAI development and radiation-use efficiency. Sirius has been calibrated for several modern wheat cultivars and was able to simulate crop growth accurately in a wide range of conditions, including Europe, NZ/Australia and USA and under climate change |
| Type Of Technology | Software |
| Year Produced | 2015 |
| Impact | Sirius is used in research by many scientists to understand crop responses to environmental variations, and in practice by farmers to optimize water and N management. |
| URL | http://www.rothamsted.ac.uk/mas-models/sirius |
| Title | Sirius crop model |
| Description | Sirius is a process-based crop simulation model. Initially developed for wheat, Sirius has been extended to model inter-plant competition and other species. Sirius is a well validated model and was able to simulate accurately crop growth in a wide range of environments, including Europe, USA, New Zealand and Australia, and for experiments of climate change, e.g. Free-Air Carbon Dioxide Enrichment (FACE) experiments. |
| Type Of Technology | Software |
| Year Produced | 2021 |
| Impact | Sirius wheat model is used as a research tool by scientists, and in practice by farmers to optimize crop management |
| URL | https://zenodo.org/record/4572624 |