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


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.
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:/
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