Identification of traits and genetic markers to reduce the nitrogen requirement and improve the grain protein concentration of winter wheat
Lead Research Organisation:
University of Nottingham
Department Name: Sch of Biosciences
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.
People |
ORCID iD |
| Michael Foulkes (Principal Investigator) |
Publications
Moreau D
(2012)
Acclimation of leaf nitrogen to vertical light gradient at anthesis in wheat is a whole-plant process that scales with the size of the canopy.
in Plant physiology
He J
(2012)
Simulation of environmental and genotypic variations of final leaf number and anthesis date for wheat
in European Journal of Agronomy
Gaju O
(2011)
Identification of traits to improve the nitrogen-use efficiency of wheat genotypes
in Field Crops Research
Gaju O
(2014)
Nitrogen partitioning and remobilization in relation to leaf senescence, grain yield and grain nitrogen concentration in wheat cultivars
in Field Crops Research
Bogard M
(2011)
Anthesis date mainly explained correlations between post-anthesis leaf senescence, grain yield, and grain protein concentration in a winter wheat population segregating for flowering time QTLs.
in Journal of experimental botany
Bogard M
(2012)
Identifying wheat genomic regions for improving grain protein concentration independently of grain yield using multiple inter-related populations
in Molecular Breeding
Atkinson JA
(2015)
Phenotyping pipeline reveals major seedling root growth QTL in hexaploid wheat.
in Journal of experimental botany
| Description | For Nottingham Univ., 3 major achievements were: 1. Explaining genetic variation in NUE via senescence kinetics: An analysis of grain yield (GY), N-use efficiency parameters and senescence kinetics for 16 UK and French cultivars under contrasting N supply in field experiments in 2 years/4 sites (Nottingham, JIC, INRA Mons and Clermont Ferrand) showed timing of onset of post-anthesis senescence explained 32-70% of genetic variation in NutE (GY/N uptake; NUtE) across sites under low N, and was itself associated with the efficiency of post-anthesis N remobilization (Gaju et al accepted in FCR). 2. Understanding effects of crop N status on N allocation parameters: Analysis of N partitioning in the same experiments showed genetic variability in N distribution in leaf layers is due to differences mediated by crop N status. The adjustment of the leaf N gradient to the light gradient differed significantly among genotypes. But, when the impact of crop N status on leaf N distribution was considered, the remaining variability was only weakly explained by a genotypic effect. (Moreau et al draft ms uploaded with report). 3. A novel framework for predicting post-anthesis senescence in wheat: Analysis of canopy N dynamics and senescence profiles in the 16 cvs and a Savannah x Rialto DH population demonstrated the stay green trait is determined by an increase in N accumulation at the start of grain filling and/or decreased N remobilization from the lamina and/or stem during grain filling. |
| Exploitation Route | The project produced an extended genetic map of the Savannah x Rialto DH mapping population and provided stocks of this important population to other projects. The project required refinement of field phenotyping methodologies which included advanced protocols for scoring progression of field senescence and the development of calibration protocols for determination of stem, leaf, and ear Nitrogen content by Near Infra Red Reflectance (NIR). These high throughput and low cost screens allowed very large scale field screens. One output of this was the identification of 'stay green' mutants from 7000 Paragon EMS mutant lines (the DEFRA WGIN EMS population). Within the BBSRC-INRA NUE project some of these senescence mutants were shown to confer a yield advantage at low N levels. Coordination of data collection, phenotyping methodologies, and standardised trait naming (trait ontology) required the development of common standard operating procedures for University of Nottingham, JIC, RRes and INRA. Phenotyping data were collated at Nottingham and genotyping at JIC in relational data bases. This resulted in a high level of quality assurance for statistical analysis, QTL discovery, and meta-analysis. These datasets were all uploaded on the password controlled project database available at Rothamsted Research (http:/www.rothamsted.bbsrc.uk/bab/masprojects/ NUE.html). These bioanalytical resources have generic value for any large data set physiology/genetics project. A major output of the project is the development of Near Isogenic Lines (NILs) for QTL identified for QTL identified in Savannah x Rialto and Beaver x Soissons populations. QTL for senescence were prioritised quite early in the project and advanced backcross material is now available for QTL on 2D and 3A from Beaver x Soissons and 3D and 7D for Savannah x Rialto. These NILs are essential resources for the specific study of these genes. In the project a new model for the N vertical distribution in canopy leaf layers has been developed and incorporated in SiriusQuality2. Crop N uptake is driven by canopy expansion. The vertical distribution of leaf N follows the light distribution and the ratio of nitrogen to light extinction coefficients is determined by the crop N status. In addition, a new methodology for calibration of cultivar parameters with evolutionary algorithms has been developed and applied in SiriusQuality2. Calibration of cultivar parameters of a crop simulation model represents a considerable challenge when observed data for a single cultivar is available for a complex G x E x M experiment. The algorithm with self-adaptation (EA-SA) has been developed and applied to calibrate parameters of SiriusQuality2 for the experimental datasets, generated in the project for 16 wheat cultivars in two years at four field sites (Nottingham University, John Innes Centre, INRA Estree-Mons and INRA Clermont Ferrand) and for two N treatments. |
| Sectors | Agriculture, Food and Drink,Environment |
| Description | The British Wheat Breeders (BWB) Group (RAGT Ltd, KWS UK Ltd and Limagrain UK Ltd) have been represented by Dr Peter Jack of RAGT Ltd on the steering group throughout the project. All project publications, experimental datasets and models have been made immediately available to the BWB breeders to ensure that opportunities were not wasted in exploiting the deliverables of the project. The results of the research therefore provide a route by which the UK wheat breeding industry can directly exploit novel traits and markers for improved N-use efficiency generated from the project. Additionally, calibrations for estimation of plant dry matter N% using a scanning monochromator NIRSystem to measure NIR diffuse reflectance spectra developed in the project were provided to the wheat breeding company KWS UK Ltd and used directly by the company for estimating the N content of plant dry matter samples in their breeding trials aimed at enhancing NUE. |
| First Year Of Impact | 2011 |
| Sector | Agriculture, Food and Drink,Energy,Environment |
| Impact Types | Societal,Economic,Policy & public services |
| Description | Root Phenotyping Partnership with Prof Jonathan Lynch |
| Organisation | Penn State University |
| Department | Department of Plant Science |
| Country | United States |
| Sector | Academic/University |
| PI Contribution | Joint supervision of post doctoral and post graduate staff, and development of high-throughput methodologies for studying root anatomical traits. |
| Collaborator Contribution | Expertise in high throughput field based root phenotyping and root anatomics. |
| Impact | Protocols for root anatomics in wheat. |
| Start Year | 2014 |