Identification of traits and genetic markers to reduce the nitrogen requirement and improve the grain protein concentration of winter wheat
Lead Research Organisation:
Rothamsted Research
Department Name: Computational & Systems Biology
Abstract
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Organisations
People |
ORCID iD |
| Mikhail Semenov (Principal Investigator) |
| Description | Modelling predicted that yield potential of wheat ideotypes can be substantially increased by 2050. Optimal phenology, increase in light use efficiency and extended grain filling are the key traits. To achieve the high yield potential in Southern Europe, tolerance to heat stress will be needed. |
| Exploitation Route | Models and tools developed in this project are available to academic community. |
| Sectors | Agriculture, Food and Drink,Environment |
| URL | http://www.rothamsted.ac.uk/mas-models/sirius |
| 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 |