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SID 5 Research Project Final Report
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NoteIn line with the Freedom of Information Act 2000, Defra aims to place the results of its completed research projects in the public domain wherever possible. The SID 5 (Research Project Final Report) is designed to capture the information on the results and outputs of Defra-funded research in a format that is easily publishable through the Defra website. A SID 5 must be completed for all projects.
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Project identification
1. Defra Project code AR0714
2. Project title
A study of the scope for the application of crop genomics and breeding to improve the N economy within cereals and rapeseed food chains
3. Contractororganisation(s)
Division of Agricultural and Enviornmental Sciences
University of NottinghamSchool of BiosciencesLoughboroughLeicestershireLE12 5RD
54. Total Defra project costs £ 54,021
5. Project: start date................ 01 November 2003
end date................. 28 February 2005
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6. It is Defra’s intention to publish this form. Please confirm your agreement to do so...................................................................................YES NO (a) When preparing SID 5s contractors should bear in mind that Defra intends that they be made public. They
should be written in a clear and concise manner and represent a full account of the research project which someone not closely associated with the project can follow.Defra recognises that in a small minority of cases there may be information, such as intellectual property or commercially confidential data, used in or generated by the research project, which should not be disclosed. In these cases, such information should be detailed in a separate annex (not to be published) so that the SID 5 can be placed in the public domain. Where it is impossible to complete the Final Report without including references to any sensitive or confidential data, the information should be included and section (b) completed. NB: only in exceptional circumstances will Defra expect contractors to give a "No" answer.In all cases, reasons for withholding information must be fully in line with exemptions under the Environmental Information Regulations or the Freedom of Information Act 2000.
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Executive Summary7. The executive summary must not exceed 2 sides in total of A4 and should be understandable to the
intelligent non-scientist. It should cover the main objectives, methods and findings of the research, together with any other significant events and options for new work.
The overall objective of the project was to assess the scope for the application of crop genomics and breeding to increase N economy within cereal and rapeseed-based food-chains, and to inform DEFRA on the potential, feasibility and likelihood of success of further public investment in modifying N economy.
The potential for crop genomics and breeding research to improve nitrogen economy Cereal and rape-seed are the major UK arable crops. Of the total annual UK use of 1.2 Mt of nitrogen (N) fertiliser, about 0.7 Mt are applied to cereals and oilseed rape (OSR). These fertilisers represent a substantial cost to the grower and additionally have environmental impacts through N leaching and de-nitrification with associated N2O contributing to global warming. About 40% of UK cereals are used in livestock diets. They provide significant protein, but tend to cause high N excretion, with adverse environmental consequences. Minimising environmental impacts of N inputs requires N-efficient crops with lower fertiliser N requirements and with protein tailored to optimise utilization in feedstuffs.
The scope for applied crop genomics and breeding research to lower fertiliser N requirements was assessed through a review of genetic variation in N-use efficiency (yield/N available; NUE) and underlying traits (Annex 3) as well as available genomics platforms (Annex 4). In summary, for cereals and OSR, evidence suggested that genetic reductions of up to 20% in fertiliser N requirements may be feasible in the medium term (10-15 years). Phenotyping studies in winter wheat and results from UK variety evaluation trials in both winter wheat and winter OSR under contrasting N availability (Annex 2) demonstrate sufficient genetic variation in current UK commercial germplasm to underpin breeding for improvement. It will be necessary to develop new mapping populations for improvement of some traits, e.g. rooting traits, and there is a general requirement for the development of high-throughput phenotyping screens to underpin breeding. The available genomics technologies (marker technology, arrays, mutagenesis systems etc) are largely in place and there is a requirement now for their exploitation to develop markers to assist breeding to improve N economy in both the short-
An analysis of the annual UK net N fertiliser input into cereals and OSR land was carried out (Annex 1). The N surplus (N fertiliser input - grain N offtake) was first calculated, and then the net fertiliser N input into arable land was estimated by adding to the N surplus an amount of N
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to account for N returned to agricultural land in N manures resulting from grain fed to animals. The largest net fertiliser N input was from winter wheat, accounting for 57% of the annual total for cereals and OSR. The contribution of winter OSR (15%) and winter barley feed cultivars (13%) was also relatively high. The main reason for the large influence of winter wheat was the large area over which the crop is grown. In contrast, winter OSR contributed a relatively large net fertiliser N input from a relatively modest area grown, due a large N surplus at 112 kg N/ha compared to other crop species. In general, the net fertiliser N inputs were larger for feed cereals than for quality cereals, due to the extra N returned to the system in livestock manures.
The potential environmental impacts of lowering fertiliser N requirements through breeding were estimated in the current project (Annex 1). We have estimated the potential impacts of a 20% reduction in fertiliser N requirements on potential N leaching and global warming potential (GWP) at the national scale. For winter wheat the effect was to reduce annual N leaching from 65,565 to 55,643 t N (15%) per annum and for winter OSR from 19,152 to 10,403 t N (46%) per annum. Overall, for these two major arable crops species N leaching would be reduced by 18,671 t N (22%) per annum. With regard to effects on global warming potential (equivalent tonnes of CO2 ; GWP), i.e. via denitrification and burning of fossil fuels for N fertiliser manufacture, a 20% reduction of the N fertiliser requirement reduced GWP arising from winter wheat production on average by 0.24 eq. t CO2/ha (19%) and for winter OSR by 0.28 eq. t CO2/ha (31%). Overall, the environmental benefit from reduced GWP would be in the region of 2-3 times greater for winter wheat than for winter OSR, associated with the greater area of wheat cultivated. In summary, there is considerable scope for research underpinning breeding to increase the N economy of cereals and OSR; and to ameliorate the impacts of N fertilisers on UK water bodies and climate change. This would assist policy makers in implementing measures to comply with the EU Nitrates Directive (91/676/EEC) and to meet the EU nitrate limit of 50 mg l-1 as set out in the EU Water Framework Directive (2000/60/EC). Lowering fertiliser N requirements will additionally benefit farmers facing increasing economic pressures with high N fertiliser costs and cereal and OSR grain trading at historically low prices. The uptake of new N-efficient varieties by farmers would be widespread and rapid due to the low requirement for knowledge transfer (research, extension, adoption).
Contribution of project activities to the DEFRA Genetic Improvement NetworksThe present project has guided the activities of the existing DEFRA Genetic Improvement Networks and the development of two relevant DEFRA-LINK projects adressing improved N economy in cereals and OSR. A summary of the relevant information generated by this scoping study is provided below.
The crop species/end-uses of greatest influence on UK N emissions were identified as: (1) winter wheat (feed cultivars), (2) winter wheat (bread-making cultivars), (3) winter OSR (all end uses), and (4) winter barley (feed cultivars). Strategies for improving N economy were reviewed and prioritized. In summary, priorities were identified as research to underpin breeding to increase crop NUE and to optimize grain protein content/composition to lower N content in animal manures. The generic ‘road map’ for the delivery of new commercial cultivars with improved N economy for the UK science and breeding communities was outlined for each of the four key crop species/end uses, namely:
Characterisation of genetic variability (Assessment of variability in NUE (uptake, utilization) and physiological traits, and grain protein content/composition) Detection of QTL (QTLs for NUE (uptake, utilization) and physiological traits, and grain protein content/composition, at low and high N levels; fine mapping of some QTL using backcross lines) Identification of candidate genes (Identification of potential candidate genes through transcriptome, molecular mutational and bioinformatics studies; identification and mapping of genes involved in N metabolism) Plant breeding programme (Identification of potential parents; progeny selection using indirect selection (QTLs, phenotypic screens) at low N levels)
To maximize the use of resources in this report, we have carried out new empirical N x cultivar
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analyses (Annex 2) and trait prioritisation analyses (Annex 3) for winter wheat and winter OSR only. For winter barley, additional suggestions for future research activities are made on the assumption that there will be significant commonality between traits to improve N economy in feed wheats and feed barleys. Research requirements were identified where we consider investment is needed to fill in the gaps in the ‘road map’ to guide the activities of the Wheat Genetic Improvement Network (WGIN) and the Oilseed Rape Genetic Improvement Network (OREGIN). A synopsis of the recommendations for future research activities in each case is set out below.
Winter wheat (feed cultivars)Target traits for improved N economy include high root length density, high number of N transporters/unit root length, low stem N storage, high glutamine synthetase (GS) activity, low grain N content, high grain protein % essential amino acids (EAA) and low grain protein % rumen degradable N (RDN). DEFRA WGIN NUE trials have identified populations suitable for genetic analysis of traits underlying N-utilization efficiency (yield/N uptake), e.g. stem N storage and GS activity. It may be necessary to develop new mapping populations for analysis of traits underlying N-uptake efficiency (N uptake/N available), e.g. rooting traits. Studies bridging the respective genomics platforms and integrating physiological/development analysis as outlined in the generic road map are required. There is a requirement for the development of precise, high-throughput phenotyping screens, particularly for rooting and stem N storage traits. The available genomics technologies (marker technology, wheat arrays, mutagenesis systems etc) are largely in place to develop markers to assist breeding in a 5-10 year timeframe. For grain protein composition traits (%EAA and % RDN), preliminary phenotyping studies to characterise genetic variability are required to identify the most appropriate germplasm resources for genetic studies.
Winter wheat (bread-making cultivars)Target traits for N economy include high root length density, high number of N transporters/unit root length, high stem N storage (with optimised remobilization), high GS activity, high total grain N content and high grain protein % glutenins. Although the direction of desirable trait expression in the N economy crop ideotype is sometimes different to that for feed wheats (e.g. high stem N storage for bread-making wheats cf. low stem N storage for feed wheats), the road map is essentially as outlined under feed wheats. An Avalon x Cadenza mapping population, for which a high density map has been produced under the DEFRA WGIN project, should serve as a central mapping resource. For grain protein % glutenins, preliminary phenotyping studies to characterise genetic variability are required to identify the most appropriate germplasm resources for genetic studies.
Winter Oilseed Rape (all end-uses)The ideotype combining priority traits for winter OSR to improve N economy includes high root length density, high number of N transporters/unit length, low/delayed leaf shed, low stem N storage, high GS activity and low total grain N content. Germplasm resources have been put in place by the DEFRA OREGIN through the development of the Diversity Fixed Foundation Set (DFFS), and mapping populations with high density maps are available from the collections at Warwick HRI. In the event that the available mapping populations do not represent sufficient genetic variation for key traits, the DFFS could be used through association genetics studies to identify genetic loci associated with target traits. As for wheat, there is a requirement for the development of high-throughput phenotyping screens for rooting and stem N storage traits. Marker technologies (existing high density maps, SSR, SNps etc) are largely in place. Large-scale oligo-arrays are not currently available but are in the pipeline and should be available with a 1-2 year timeframe. As for wheat, studies bridging the respective genomics platforms and integrating physiological/development analysis as outlined in the generic road map are required. There is scope to identify markers for each of the priority traits, but this will require preliminary phenotyping trials to identify appropriate germplasm resources for genetic studies.
Winter Barley (feed cultivars)Target traits for feed winter barley will likely include high root length density, high number of N transporters/unit root length, low stem N storage, high GS activity, low total grain N, high grain protein % EAA and low grain protein %RDN. The genomics technologies (marker technology,
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barley arrays, mutagenesis systems etc) are again largely in place, and studies bridging the respective genomics platforms and integrating physiological/development analysis are again required. As for OSR, there is a requirement for preliminary phenotyping screens to identify appropriate germplasm resources for respective traits according to parental differences. There is scope to exploit activities of the large ongoing association genetics DEFRA LINK programme in elite cultivated barleys (acronym, AGOUEB). For example, the phenotypic information collated in this project will be exclusively on above-ground characteristics, so there is scope for new studies to supplement this phenotypic dataset with below-ground rooting characters.
Generic recommendations for future research activities Definition of useful mapping populations (information on NUE and grain protein content/composition and underlying traits for parental lines of well characterised mapping populations through phenotyping trials) CE ‘smart-screens’ for phenotyping genetic diversity (development of precise phenotyping methodologies, field screening and CE screening well correlated to field expression of traits.) Crop physiology: modelling (development of modelling frameworks to design virtual crop ideotypes with improved N economy, more information is required about inter-relationships between plant and crop NUE processes) Genomics (Transcriptome analysis should provide useful information on gene expression related to NUE and grain protein content/composition to highlight important genes. Mapping in association with marker development should provide information on genomic regions associated with NUE and grain protein content/composition). Informatics (There will be a likely requirement for the study of appropriate genotypes combining multi-disciplinary approaches, namely transcriptomics, proteomics and metabolomics with appropriate bioinformatics support.)
The project has also contributed information to DEFRA used in the commission of two DEFRA-LINK projects:
DEFRA-LINK: The genetic reduction of energy use and emissions of nitrogen through cereal production: Green Grain. (ADAS, SCRI, University of Nottingham, Syngenta Seeds, HGCA, Scotch Whisky Research Institute, Wessex grain Ltd., Grampian Country Food Group Ltd., FOSS UK Ltd) 2004 - 2009The project addresses lowering fertiliser N requirements and optimizing grain N composition in wheat for the feed and distilling end-use markets.
DEFRA-LINK: Breeding oilseed rape with a low requirement for nitrogen fertiliser. (ADAS, Warwick HRI, University of Nottingham, Elsoms Seeds, Saaton Union Uk Ltd, Nickerson UK Ltd, Syngenta Seeds Ltd, NE Biofuels & Terra N, BASF, HGCA, BP). 2006-2011.The project addresses improving the viability of UK oilseed rape for biodiesel and food production by reducing green house gas emissions, nitrate leaching and financial costs associated with growing the crop.
Project Report to Defra
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8. As a guide this report should be no longer than 20 sides of A4. This report is to provide Defra with details of the outputs of the research project for internal purposes; to meet the terms of the contract; and to allow Defra to publish details of the outputs to meet Environmental Information Regulation or Freedom of Information obligations. This short report to Defra does not preclude contractors from also seeking to publish a full, formal scientific report/paper in an appropriate scientific or other journal/publication. Indeed, Defra actively encourages such publications as part of the contract terms. The report to Defra should include: the scientific objectives as set out in the contract; the extent to which the objectives set out in the contract have been met; details of methods used and the results obtained, including statistical analysis (if appropriate); a discussion of the results and their reliability; the main implications of the findings; possible future work; and any action resulting from the research (e.g. IP, Knowledge Transfer).
1. INTRODUCTION
1.1. ObjectivesThe overall objective of the project was to assess the scope for the application of crop genomics and breeding to increase N economy within cereal and rapeseed-based food-chains, and to inform DEFRA on the potential, feasibility and likelihood of success of further public investment in modifying N economy. Nitrogen economy subsumes processes affecting N-use efficiency (yield/N available; NUE) and grain protein content/composition affecting livestock nutrition. Specific objectives were:
(1) A review of genetic variation in NUE and protein content/composition using available data sets and the literature, to identify priority traits and crop ideotypes.
(2) A review of genomics-based technologies in relation to their application for increasing N economy and the prospects for further advances.
(3) A consultation with the plant breeding industry to assess the critical factors influencing the feasibility of developing varieties with greater N economy.
(4) An environmental and economic potential-impact analysis to comment on the potential environmental and economic impacts of genetically improving N economy.
(5) Guidance to DEFRA on the potential for applied strategic crop genomics and breeding research to increase N economy within cereal and rapeseed-based food-chains.
These objectives were addressed by firstly identifying the key supply chains (crop species/end-uses) with most influence on N economy of UK cereals and oilseed rape and associated N emissions. For the key supply chains, areas of inefficiency were identified at the ‘crop production’ and at the ‘livestock nutrition’ stages, and the potential environmental and economic impacts of reducing inefficiencies assessed. The potential for the application of crops genomics and breeding to address these inefficiencies was then assessed and the timeframes involved estimated. Finally, road-maps for improving N economy through the application of crops genomics and breeding were outlined for the key supply chains.
1.2. Identifying the key supply chainsCereal and rape-seed crops are the major UK arable species (Fig 1a). Of the total annual UK use of 1.2 Mt of N fertiliser, about 0.65 Mt are applied to cereals and oilseed rape (Fig 1b). These fertilisers represent a cost to the grower and have environmental impacts through N leaching, use of fossil fuels for their manufacture and application, and de-nitrification and associated N2O contributing to global warming. Bread-making wheat and oilseed rape (OSR) crops are high-risk crops for N leaching. About 42% of UK cereals are used in livestock diets (Fig 2). They provide significant protein, but the low value proteins tend to cause high N excretion, with adverse environmental consequences. Minimising environmental impacts of applied N inputs requires N-efficient crops with lower fertiliser N requirements, and additionally lower protein content and optimised protein composition to reduce N content of manures for crops used in livestock diets.
An analysis of the annual UK net N input into cereals and OSR land was carried out (Table 1). It was assumed that 70% of N in feed grain is re-imported into UK arable land through livestock N excretion1. The total annual N surplus (N fertiliser input - grain N offtake) was calculated and this figure adjusted for re-imported grain N to calculate the annual net fertiliser N input into arable land. The greatest net N input was from winter wheat, accounting for 57% of the total net N input associated with cereals and
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OSR. Feed/export cultivars contributed about twice the net N input of bread-making cultivars for winter wheat. The contribution of OSR (15%) and winter barley feed/export cultivars (13%) was also relatively high. Spring cereals, winter oats and triticale were less significant. The main reason for the large influence of winter wheat was the larger area over which the crop is grown. In contrast, OSR contributed a relatively high net N input from a relatively modest area grown, due a large net N input per ha. This was mainly associated with a larger N surplus at 112 kg N/ha compared to other crop species. In general, net N inputs were significantly larger for feed cereals than for quality cereals, due to the extra N returned to the system in livestock manures.
The supply chains of greatest influence on N emissions were identified as: 1. Winter Wheat (feed/export cultivars), 2. Winter Wheat (bread-making cultivars), 3. WOSR (all end uses), and 4. Winter Barley (feed/export cultivars). These supply chains therefore provide the focus of the work presently reported. To maximimze the use of resources in this report, we have carried out new empirical N x cultivar analyses (Annex 2) and trait prioirisation analyses (Annex 3) for supply chains 1 - 3 only. For feed winter barley, additional suggestons for future research activities are made on the assumption that there will be signficant commanlity between traits to improve N economy in feed wheats and feed barleys.
Figure 1. UK areas, average fertiliser N application rate and total N applied for cereals and oilseed rape in 2002-3 (DEFRA June Census and British Survey of Fertiliser Practice). SW/WW = spring/winter wheat; SB/WB = spring/winter barley; SOSR/WOSR = spring/winter oilseed rape; BM = bread-making; M = malting.
Figure 2. Total grain DM production and end-use markets for UK cereals and oilseed rape (OSR) in 2002-3 (UK supply/demand statistics and certified seed production (http:\\data.hgca.com).Table 1. Annual N balances for cereals and oilseed rape crops in the UK. N surpluses and net fertiliser N inputs relate to all UK agriculture (after Sylvester-Bradley2, but updated).
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Area N input applied
Yield N content
N offtake at harvest
N surplus(input-offtake)
Net fertiliser N input
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'000 ha t/UK t/ha kg/t t/UK t/UK t/UKWinter wheat-feed/export 1,074 200,806 7.9 17.0 144,215 56,591 127,256Winter oilseed rape 366 75,824 3.2 30.0 35,165 40,659 50,505Winter wheat-milling 694 144,690 7.3 19.0 96,252 48,438 65,282Winter barley-feed/export 455 70,486 6.4 17.0 49,477 21,009 45,253Spring barley-feed 299 30,085 5.8 17.0 29,261 824 21,307Spring barley-malting 116 16,561 5.4 14.0 8,755 7,806 7,806Winter barley-malting 61 16,108 3.6 35.0 7,659 8,449 8,449Spring oilseed rape 41 5,454 2.2 33.0 2,955 2,499 3,326Winter oats 84 9,140 6.0 17.0 8,553 587 3,581Spring wheat-milling 55 7,217 5.8 20.0 6,287 930 930Spring oats 36 3,917 5.0 17.0 3,055 862 1,931Triticale 14 1,230 6.0 18.0 1,535 -305 232Rye 8 711 5.8 18.0 851 -140 158
Total 3,303 582,229 394,020 188,209 336,016
2. IDENTIFYING PRIORITY INTERVENTION POINTS IN THE SUPPLY CHAINS Until recently there has been little incentive to breed for improved N economy. The EU launched the Nitrates Directive in 1991 (91/676/EEC) in response to concerns about the excessive use of chemical fertilisers and environmental pollution. In England ‘Nitrate Vulnerable Zones’ (NVZs) were expanded in 2002 to cover 55% of the total land area which includes most arable farmland. Growers in NVZs must comply with NVZ Action Programme Measures and from January 2005 the NVZ regulations became a cross compliance requirement. Farmers are also facing increasing economic pressures with high costs of N fertiliser currently at around £480/t of N and cereal and OSR grain trading at historically low prices. Additionally, reducing N fertiliser application to cereals and OSR will assist policy makers in implementing measures to meet the EU nitrate limit of 50 mg l-1 as set out in the EU Water Framework Directive introduced in 2000 (2000/60/EC). Inefficiencies in N economy can occur associated with either the ‘crop production’ stage or the ‘livestock nutrition’ stage of the food-chain.
2.1. Crop production intervention strategiesN-use efficiency is a complex trait defined as grain DM yield/N available (from the soil and/or fertiliser). NUE can be partitioned into two components: (i) N-uptake efficiency (crop N uptake/N available, NupE) and (ii) N-utilization efficiency (grain DM yield/crop N uptake, NutE). An alternative approach to increasing NUE to encourage reduction in N inputs could be to tax N losses to the environment. However, diffuse pollution is difficult to monitor and control and any tax would be expensive to maintain. Similarly a N fertiliser tax has been suggested as a way to reduce N inputs, but economic models suggest that fertiliser taxes must be very high, > 100%, before they become effective1. We therefore presently assess the scope for agronomic and genetic intervention strategies to lower fertiliser N requirements.
2.1.1. Nitrogen-uptake efficiency Fertiliser-recovery efficiency (N offtake/N applied; FUE) is about 55% for winter wheat, 60% for WOSR and 50% for winter barley in the UK. Since in the region of 40-50% of the N applied is not recovered, N-uptake efficiency is a key point in the supply chain where improvements can potentially impact on diffuse pollution. There are two conceptual strategies for improving FUE: (1) alter fertiliser application techniques and (2) breed new crop cultivars with increased NupE.
2.1.1.1. Fertiliser application techniquesBest management practices can be prescribed including calculating fertiliser recommendations within a recommendation system, allowing for soil mineral N and manures applied, spreading fertilisers evenly with a properly calibrated spreader, and minimising pest and disease infestation1. In the UK, most of these practices are already generally adopted. Yield-mapping, by remote-sensing or direct measurement of the spatial variation in fields, offers the prospect of variable rate N applications. However, using yield maps, without measuring other transient yield-limiting factors, e.g. soil N, may be futile. Sylvester-Bradley et al.3 concluded that uptake of precision agriculture practices was most likely where prior knowledge identified large heterogeneity and predicted treatment zones, but that the main obstacle was the lack of appropriate sensors. Another significant factor affecting the success of yield mapping on N application and recovery in our maritime climate is the unpredictability of the weather. Nitrification inhibitors have often been suggested as a means of reducing N loss but they have not been extensively adopted. In summary, agronomic strategies offer several potential avenues for
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reducing diffuse N pollution, but their application may be limited due to the unpredictability of weather and a high requirement for knowledge transfer (research, extension, adoption). 2.1.1.2. Breeding for increased N-uptake efficiencyThere is evidence for genetic variation in NupE in winter wheat (Annex 3). In the present project analysis of National List (NL) and Recommended List (RL) trials (178 cultivars) in 1988-2003 showed variation in the range 0.68 - 0.88 at ‘optimum’ N levels (Annex 2, Table A2.2). This range was similar to those reported in spring wheats at the International Centre for Maize and Wheat Improvement (CIMMYT) in Mexico (0.60 - 0.76 under 150 kg fertiliser N/ha4) and in winter wheats in France (0.76 - 0.97 under 170 kg/ha fertiliser N5). A DEFRA Wheat Genetic Improvement Network (WGIN) NUE trial at Rothamsted Research in 2003/4 also demonstrated a range of 0.60 - 0.72 for 13 modern UK winter wheat cultivars out of a total of 32 UK and continental cultivars tested under 200 kg/ha fertiliser N. The corresponding range under nil N was 0.65 to 0.92. Therefore sufficient genetic variation exists to form the basis for breeding progress in NupE. For WOSR, a genetic range of 2.2 - 3.4 t/ha grain yield under nil fertiliser N has been reported in Germany potentially indicative of large differences in NupE6. In the present study, 88 NL and RL trial sites in 1995-2003 were classified into moderate N and optimal N backgrounds (Annex 2). This analysis identified statistically significant cultivar x N interactions amongst 149 cultivars examined, and showed that the yield of some cultivars could be the same at optimal N, but differ by as much as 1.4 t/ha (35%) at moderate N levels suggesting there is sufficient genetic variation to form the basis for breeding progress in NupE.
2.1.2. Nitrogen-utilization efficiency 2.1.2.1. Fertiliser application techniquesIt seems unlikely that altering fertiliser application techniques can play a significant role in improving NutE (grain yield/N offtake) in cereals and OSR.
2.1.2.2. Breeding for increased N-utilization efficiencyA key requirement is to identify genetic variation in NutE which is independent of variation in NupE. In winter wheat, genetic variation under moderate N supply (fertiliser + soil N < 270 kg N/ha) was reported in the present study amongst 178 NL/RL cultivars in the range 31.7 - 39.7 kg DM/kg N (Annex 2, Table A2.2). Other studies at CIMMYT and the French Institute of Agronomy Research (INRA) on the N budget of wheat show reasonable heritability and differences in NutE under low N4,5. Importantly the DEFRA WGIN NUE trial 2003/4 demonstrated a range of 48 - 68 kg DM/kg N under 50 kg/ha fertiliser N, and the regression of NutE on NupE was not significant. There is therefore sufficient genetic variation to form the basis for breeding for this trait. It should be noted that for bread-making cultivars, higher NutE may be associated with low grain protein content. So it may be necessary to increase N harvest index (ratio of grain N to crop N) and/or to improve grain quality alongside increases in NutE for quality wheats. With regard to WOSR, genetic variation under sub-optimal N supply has been demonstrated by Nyikako6 in Germany and Yau and Thurling7 in Australia. The variety x N interactions for yield in the UK NL and RL trials identified in this study (Annex 2, Table A2.6) are also indicative of significant differences in ability to maintain yield when crop N uptake is restricted. In summary, there appears to be sufficient genetic variation to form the basis for breeding progress for NutE in WOSR.
Turning to consider to the relative importance of the two NUE components (NupE and NutE) in contributing to genetic reductions in fertiliser N requirements, results in the literature (Annex 3) and from the present analysis of NL/RL data (Annex 2) generally indicate that under low N, NupE is the predominant component affecting genetic variation in NUE, and as the rate of fertiliser N increases, the relative importance of NupE decreases and that of NutE increases. Hence at high N NutE is the most important component. In the context of N economy in UK cereals and OSR the aim is probably to achieve good yields at low to moderate N fertiliser inputs, and therefore it seems that both NUE components are likely to be of high importance in improving NUE in UK cereals and OSR. 2.2. Livestock nutrition intervention strategiesStrategies for improving N economy within the food chain of cereals and OSR must also address tailoring grain protein content and composition to optimise utilization by animals in feedstuffs. Currently 20 to 30% of N consumed by ruminants is in the protein of the meat and milk produced and the remainder is excreted in faeces and urine. In non-ruminant production, where the protein needs of the animals can be more closely met, this efficiency may average 30 to 35%8. The maximum possible efficiency varies with animal species, age, stage of lactation, and so on, but this theoretical limit is about 50%. Two general strategies can be used to reduce N excretion. The first is to reduce the protein
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fed by improving the match between the protein quality fed and that required by the animal. The second is to improve animal productivity. Although improved animal productivity can increase the utilization efficiency, greater improvements are generally obtained through strategies that improve protein-feeding efficiency. These efficiency strategies relate to: (1) management techniques to alter feed formulations or (2) breeding new crop cultivars with altered grain protein content and/or composition. Considerations can be made with regard to non-ruminants and ruminants in each case.
2.2.1. Non-ruminants2.2.1.1. Management techniques to alter feed formulations There are 20 primary amino acids in proteins. Providing the precise amount of each amino acid required at any point in the animal’s life is essentially impossible, but improved feeding management can approach this goal. Amino acids are generally classified as either essential or non-essential. Essential amino acids (EAA) are those that must be obtained directly from the feed. Non-essential amino acids can be synthesised by the animal from other amino acids fed in excess in the diet. The emphasis in formulating diets must be given to the essential group. In poultry and pigs, the optimal dietary pattern among EAA corresponding to the needs of the animal is often referred to as the ideal protein9. Dietary crude protein (CP) can be reduced through the supplementation of synthetic amino acids to reduce N excretion. Reductions of 2-4 percentage units of dietary CP have been made without decreasing weight gain or feed conversion10. An average reduction in N excretion per unit of dietary CP reduction is about 8.5%. Phase-feeding provides another strategy for improving the match of the diet to the requirements of the animal. Multiphase feeding can be accomplished by mixing a diet high in N with a low-N diet in decreasing proportions each week through the growth period. Multiphase feeding may reduce urinary N excretion in pig production by up to 15%. Other feeding strategies include feed additives to inhibit urease activity or to bind ammonia. Thus far, experimental work on these additives has shown small and inconsistent effects on ammonia emission8.
2.2.1.2. Breeding for improved grain protein content and/or compositionThe storage tissue of the grain (endosperm) contains prolamins in protein bodies (about 50% of total grain N) forming part of the protein matrix surrounding the starch granules. In wheat the prolamins are comprised of gliadins which are present as monomers and glutenins which form polymers. The glutenins and gliadins have poor and very poor, respectively, EAA levels (lysine, threonine and tryptophan) relative to non-ruminant requirements. There may therefore be scope to reduce the CP content of feed grain by reducing the gliadin fraction without decreasing weight gain in poultry and pigs. Similarly in barley the prolamins are low in essential amino acids, and there may be scope to reduce the specific hordeins which have very poor EAA levels to reduce N excretion. However, there is relatively little information currently available on the variation amongst UK cultivars in the relationship between grain N content and percentage EEA level.
2.2.2. Ruminants2.2.2.1. Management techniques to alter feed formulations The digestive process in ruminants includes the extra step of rumen fermentation. Rumenally degraded protein (RDP) provides a mixture of peptides, free amino acids and ammonia for microbial growth and protein synthesis. Rumenally synthesized microbial protein typically supplies most of the amino acids passing into the small intestine. Rumenally undegraded protein (RUP) is the second most important source of amino acids that are absorbed within the intestinal tract. Most forage protein is highly degradable, so there is normally little problem in meeting the RDP requirement. Total protein can be overfed to meet the minimum RUP requirement, but this leads to the excretion of considerable excess N. Therefore, protein needs of cattle, particularly dairy cows, are normally best met by reducing the total protein in the diet through the supplementation of feeds high in RUP. However, less degradable protein feed is usually more expensive. Attempts to identify requirements and responses to supplementary synthetic amino acids in ruminants have been the subject of a number of reviews. Due to problems in predicting the extent to which dietary proteins are degraded in the rumen, it has been difficult to identify situations in which positive and cost-effective responses to supplementation with synthetic amino acids will be achieved. Even with industrially produced rumen-protected amino acids responses to supplementation have been variable. A number of studies have examined the effect of different supplements comparing fibre and starch-based energy sources on N excretion. These generally suggest that the type of supplement may influence the partitioning of excreted N between faeces and urine but has little effect on the overall amount of N excreted.
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2.2.2.2. Breeding for improved grain protein content and/or composition Total dietary N intake principally affects the efficiency with which N is utilized by ruminants. Generally, reducing dietary N content increases the efficiency of utilization. Increasing the RUP percentage of grain protein will contribute to improved utilization by facilitating the reduction in total dietary N intake. Grass and grass silage (the main forages fed to ruminants) contain large proportions of RDP that is rapidly released. The majority of this N is excreted in urine. Capturing excess RDP is an effective strategy for reducing N excretion and total N requirements of ruminants. Wheat and barely play a valuable role because they are a source of rapidly digested starch, which complements RDP. However, inclusion of cereal grain in ruminant diets has to be limited because its starch is digested too rapidly and can result in rapid decreases in rumen pH which inhibit microbial fermentation. In summary, to improve N utilization lower grain protein contents and higher percentage RUP may be desirable but also starch that is more slowly digested in the rumen. There is relatively little information on variation in UK cereal and OSR cultivars for RUP as a percentage of grain protein or rates of starch digestion in the rumen. Changes in the amino-acid profile of cereals and rapeseed are unlikely to have a major impact on N retention by ruminants because of the modifying effects of rumen fermentation.
2.3. Potential environmental and economic impacts of improving N economy 2.3.1. Environmental impactsImproved N economy offers the potential to decrease: (i) N leaching, (ii) use of fossil fuels for manufacture and application of fertiliser, and (iii) de-nitrification and associated N2O emissions. Decreasing N leaching will help meet EU standards for drinking water for nitrates of 50 mg NO3
-/l in designated NVZs. Decreasing the burning of fossil fuels will assist in lowering emissions of CO2, N2O and CH4, the so-called ‘greenhouse gases’ associated with global warming. Reducing N2O from denitrification of N fertilisers will contribute meaningfully to reducing global warming, because although the amount of N2O emitted is quite low its global warming potential is high, 310 times greater than CO2.
In the present study, nitrogen losses to leaching and de-nitrification at the crop production stage were derived from the SimUlation of Nitrogen Dynamics In Arable Land (SUNDIAL) model, developed at IACR-Rothamsted (Annex 1). Two crops, winter wheat and WOSR, grown on two soil types, deep clay (150 cm) and shallow sand (50 cm), were assessed. Reductions of the standard RB209 N fertiliser recommendations of 5%, 10%, 20% and 50% were made, assuming grain DM yield to be conserved (Annex 1, Table A1.1). Of the crop scenarios considered, a reduction in the N applied to WOSR grown on either shallow sand or deep clay offered the greatest potential to reduce N leaching losses per ha. For a 20% reduction in N fertiliser, N losses from leaching were reduced by 15-17 kg N/ha (Fig. 3; Annex 1, Table A1.6). Corresponding reductions for winter wheat were 0-11 kg N/ha. For a 20% reduction in N fertiliser, average losses for WOSR from de-nitrification were reduced by 17 kg N/ha on deep clays compared to 11 kg N/ha for winter wheat (Annex 1, Table A1.6).
Figure 3. The nitrogen leached and de-nitrified from winter wheat (WW) and winter oilseed rape (WOSR) on a deep clay and shallow sand according to long-term mean overwinter rainfall, with straw removed for 2 N rates (standard RB209 N fertiliser rate and 20% reduction). RB209 N rates: deep clay WW (220 kg N/ha); shallow sand WW (160 kg N/ha); deep clay WOSR (220 kg N/ha); shallow sand WOSR (250 kg N/ha): DEFRA (2000) Fertiliser recommendations for agricultural and horticultural crops (RB209), 7th Edition.The reduction in the potential N leaching at the UK national scale associated with a 20% reduction in fertiliser N input for winter wheat and WOSR was estimated from the results presented in Fig 3. We assumed the N leaching losses (per ha) on silts to be represented by those modelled on clays, on chalk/limestone N losses (per ha) by those on sands, and on medium soils to be intermediate between those on sands and clays. On this basis, the potential impact of a 20% reduction in fertiliser N inputs on
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0
10
20
30
40
50
60
Clay W
W
Sand WW
Clay W
OSR
Sand WO
SR
Clay W
W
Sand WW
Clay W
OSR
Sand WO
SR
Clay W
W
Sand WW
Clay W
OSR
Sand WO
SR
N le
ache
d (k
g/ha
)
Standard 'RB209' N rate
20% reduction of standard 'RB209' N rate
Current crop Subsequent crop Total
0
10
20
30
40
50
60
Clay W
W
Sand WW
Clay W
OSR
Sand WO
SR
Clay W
W
Sand WW
Clay W
OSR
Sand WO
SR
Clay W
W
Sand WW
Clay W
OSR
Sand WO
SR
N De
nitr
ified
(kg/
ha)
Standard 'RB209' N rate
20% reduction of standard 'RB209' N rate
Current crop Subsequent crop Total
UK N leaching is broadly similar for winter wheat and WOSR at around 9,000 tonnes N per year; reductions in leaching N losses per ha were greater for WOSR than winter wheat but this was counteracted by the smaller area grown (Table 2). With regard to potential impacts on global warming potential (equivalent tonnes of CO2 ,GWP), i.e. via denitrification and burning of fossil fuels for N fertiliser manufacture, a reduction of N fertiliser by 20% reduced GWP by up to 0.27 eq. t CO2/ha for winter wheat and 0.32 eq. t CO2/ha for WOSR (Fig. 4). These values are not greatly different, and it can be concluded that the environmental benefit from reduced UK GWP via a 20% reduction in N fertiliser input would be in the region of 2-3 times greater for winter wheat than for WOSR, associated with the greater area of wheat cultivated. In conclusion, the potential environmental impact at the national scale from developing N-efficient varieties is overall greater in winter wheat than in WOSR.
Table 2. Estimated UK N leaching losses for standard RB209 N fertiliser rate and 20% reduction (losses per ha as per Figure 3); distribution of UK crops according to soil type as described by DEFRA 11; total areas as in 2004 from FAOSTAT database).
Winter wheat Winter oilseed rapeSoil type UK area
HaN losses~ RB209 N
rate(tonnes)
N losses ~ 20% reduction
RB209 rate(tonnes)
UK area
ha
N losses ~ RB209
rate(tonnes)
N losses ~ 20% reduction
RB209 rate(tonnes)
SandyMedium
ClaySilts
Chalk/limestoneOthers
Total
31856049775065703017919023892099550
1991000
137941692416229
442610345
384865566
1369814684105122867
102743609
55644
55700133680228370445607798016710
557000
13934411936318271950209
19153
446225358691145624
6710404
0
0.2
0.4
0.6
0.8
1
1.2C
lay WW
Sand WW
Clay W
OSR
Sand WO
SR
Clay W
W
Sand WW
Clay W
OSR
Sand WO
SR
Clay W
W
Sand WW
Clay W
OSR
Sand WO
SR
Clay W
W
Sand WW
Clay W
OSR
Sand WO
SR
Glo
bal w
arm
ing
pote
ntia
l (eq
. CO 2
t/ha
)
Standard 'RB209' N rate
20% reduction of standard 'RB209' N rate
Energy fert. manufacure
Energy field operations
TotalDenitrification
Figure 4. Global Warming Potential (equivalent tonnes of CO2/ha) associated with N fertiliser use for winter wheat (WW) and winter oilseed rape (WOSR) with straw removed for 2 N rates (standard RB209 rate and 20% reduction). RB209 standard rates: Deep clay WW (220 kg N/ha); shallow sand WW (160 kg N/ha); deep clay WOSR (220 kg N/ha); shallow sand WOSR (250 kg N/ha).
The data in Table 1 also allow a comparison of the effects of improving N economy through interventions at the crop-production stage and the livestock-diet stage on the UK annual net N input into arable land. Effects of a 20% increase in the fertiliser-use efficiency (grain DM yield/fertiliser N applied) and of a 20% increase in the efficiency of N utilization of feed grain by livestock were compared (Table 3). The analysis illustrates that the potential impacts on UK N emissions are generally
SID 5 (2/05) Page 14 of 36
much larger for interventions acting at the crop-production stage (via reduction in fertiliser N requirements) than at the livestock-nutrition stage (Table 3). This is mainly because the benefits from improved fertilizer-use efficiency are realized across crops grown for all end-uses, whereas the benefits from improved utilization of N by livestock are realized over a much smaller area of cultivated land, relating to cultivars for specific end-use niches e.g. wheat fed to non-ruminants etc.
Table 3. Annual N surpluses and net fertiliser N inputs into arable land for cereals and oilseed rape crops in the UK (after Table 1; current baseline) and predicted values for Scenario 1 (a decrease of 20% in fertiliser N input whilst conserving yield) and Scenario 2 (an increase of 20% in the efficiency of N utilization of feed grain by livestock, i.e. from 30% of grain N fed retained in protein of meat and milk produced to 36% retained).
Area N input applied
Grain N offtake
at harvest
N surplus(input-offtake)
Net N input
'000 ha t/UK t/UK t/UK t/UKCurrent baseline
Winter wheat-feed/export 1,074 200,806 144,215 56,591 127,256Winter oilseed rape 366 75,824 35,165 40,659 50,505Winter wheat-milling 694 144,690 96,252 48,438 65,282Winter barley feed/export 455 49,472 49,472 21,009 45,253
Scenario 1. N fertiliser input reduced by 20%,Winter wheat-feed/export 1,074 160,670 144,215 16,430 87,095Winter oilseed rape 366 60,609 35,165 25,494 35,340Winter wheat-milling 694 116,037 96,252 19,500 36,344Winter barley feed/export 455 56,420 49,472 6,912 31,155
Scenario 2. N utilization efficiency by livestock increased by 20% Winter wheat-feed/export 1,074 200,806 144,215 56,591 121,199Winter oilseed rape 366 75,824 35,165 40,659 49,661Winter wheat-milling 694 144,690 96,252 48,438 63,838Winter barley feed/export 455 49,472 49,472 21,009 43,175
2.3.2. Economic impactsN fertiliser usage has a direct cost to growers. Fertilisers represent about 37% of the total variable cost of growing winter wheat and 40% with oilseed rape12. With wheat, about 40% of total fertiliser cost is for N and with winter oilseed rape it is about 50%. If NUE is improved by maintaining yield with a 10% reduction in N application, the economic benefit is relatively small as the ratio between the cost of N (per ha) and the value of the crop (per ha) is large (Annex 2, Table A2.4). However, if the NUE is improved by increasing yield by 10% with the same level of N then the economic benefits are much larger with a significant improvement in margin of income over N cost. To achieve the same level of economic benefit from a 10% reduction in N use would require, at 2005 crop prices, the cost of the N to be £1,750/t for winter wheat and £1,500/t for WOSR. It is therefore apparent that improvements in NUE mediated solely through reduced fertiliser N requirement will relate to relatively small improvements in margins. It should be noted that the above analysis in relation to wheat applies only to feed/export varieties as large reductions in N could have a serious impact on end-use quality and therefore price of wheats that require high protein levels for end use.
2.4. Summary of priority strategies to improve N economyBased on the information outlined above strategies for improving N economy to lower N emissions at the crop-production and livestock-nutrition stage are prioritized below according to high (1), moderate to high (2), low to moderate (3) and low (4) priorities.
Management strategies:- Fertiliser application techniques… N inputs calculated within a recommendation system (priority 3, already widely in use)… Precision agriculture practices (priority 2, high requirement for knowledge transfer)… Nitrification inhibitors (priority 4, responses variable)
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- Feed formulations for non-ruminants… Reduce dietary crude protein/supplement with synthetic EAA (priority 2, high potential, but
benefits restricted to relatively small end-use niche)… Phase feeding (priority 3, experimental work shows inconsistent effects)… Feed additives to inhibit urease activity (priority 4, responses variable)
- Feed formulations for ruminants… Supplementation of feeds high in RUP (priority 3, feed more expensive)… Supplementation with synthetic EAAs (priority 4, responses variable)
Genetic strategies: - Breeding to increase nitrogen-use efficiency… Increase N-uptake efficiency: (priority 1, high impact on fertiliser N requirement, sufficient
genetic variation in UK cereals and OSR to justify breeding, low requirement for knowledge transfer)
… Increase N-utilization efficiency: (priority 1, high impact on fertiliser N requirement, sufficient genetic variation in UK cereals and OSR to justify breeding, low requirement for knowledge transfer)
- Breeding to optimize grain protein content/composition (feed, non-ruminants)… Reduce grain protein content and % prolamins (low in EAA) (priority 2, high potential impact
on N emissions, low requirement for knowledge transfer, but genetic variation not well characterised and benefits restricted to relatively small end-use niche)
- Breeding to optimize protein content/composition (feed, ruminants)… Reduce grain protein content and % RDP (priority 2, high potential impact on N emissions, low
requirement for knowledge transfer, but genetic variation not well characterised and application restricted to relatively small end-use niche)
… Increase %starch more slowly digested in the rumen (priority 3, inconsistent effects in experimental data sets, genetic variation not well characterised, benefits restricted to relatively small end-use niche)
- Breeding to optimize protein content/composition (bread-making) … Increase fraction of grain protein as glutenins (priority 2, high potential impact on N emissions,
low requirement for knowledge transfer, but genetic variation not well characterised)
In summary, the potential impacts on UK N emissions through interventions at the crop production stage are probably larger those that may be achieved through modifying livestock-diets, as indicated by the analysis set out in Table 3. It seems unlikely that management strategies will be able to achieve the same scale of impacts as those achievable through breeding due to the unpredictability of weather and a high requirement for knowledge transfer. Additionally breeding offers the opportunity to combine efficiencies operating at the levels of crop production and livestock nutrition in the case of feed cultivars. On the other hand, the delivery timeframe for breeding interventions is in the range 5-10 years compared to 1-5 years for management interventions. In the following section of the report the scope for genomics and breeding to address the key genetic targets identified above for the four priority crop species/end-uses will be reviewed. We will then outline road maps by which the scientific and breeding communities may proceed to make most rapid and effective progress in delivering new cultivars with improved N economy in each case.
3. GENETIC ANALYSIS OF N ECONOMY IN CEREALS AND RAPESEED CROPS
3.1. Genomics and breeding approaches: current state3.1.1. Molecular marker approaches
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To our knowledge, there are no published reports of marker approaches being used to locate QTLs for NUE and underlying traits in wheat, barley or OSR. In wheat, work is currently ongoing in the Génoplante project at INRA, France on two DH populations (Recital x Arche and Apache x Ornicar). For the Recital x Arche population, 19 chromosomal locations have been identified (9 stable regions) through QTL detection for NUE (LeGouis, presentation at BBSRC-INRA workshop, Clermont Ferrand 21-22 April 2005). In maize, Hirel et al.13 at INRA reported co-incidental locations for QTLs for NUE and a structural gene for glutamine synthetase 1 (GS1). Similar marker approaches focusing on GS1 are currently being used in wheat at Rothamsted Research (Habash, personal communication, see Annex 3, section 5). With regard to underlying traits, there are reports in Brassica14 and barley15, where QTLs have been identified associated with N uptake, storage and remobilization in flag leaves. In the UK, the DEFRA-LINK projects: (i) ‘Genetic reduction of energy use and emissions of nitrogen through cereal production; acronym Green Grain’ and (ii) ‘Breeding oilseed rape with a low requirement for nitrogen fertiliser’ are currently using marker approaches to improve NUE and grain protein composition in feed/distilling wheat and OSR cultivars, respectively (see Annex 3, section 5).
3.1.2. Comparative genetics approachesThere is a substantial literature on physiological and metabolic N-related processes in model species (see Annex 3, sections 2.1.2 and 2.2.2), and in many studies genes related to N use have been isolated and characterised. The challenge is to use the molecular genetics in model species such as Arabidopsis and rice to define underlying genetic components in UK crop species. There are only a few direct instances of the analysis of the complex trait of NUE in Arabidoposis, e.g.16. To our knowledge, there are currently no published investigations where candidate genes identified in Arabidopsis or rice for traits associated with NUE have been used to define underlying genetic components in wheat, barley or OSR. However, this seems likely to change in the near future. For example, an Arabidopsis gene involved in root proliferation, AXR4, has recently been identified and cloned, opening up the possibility of examining effects of over-expression of the orthologues in cereals and OSR plants.
3.1.3. Transcriptome profilingTranscriptome profiling can integrate information on G x E interactions in specific developmental contexts, with changes in gene expression related to NUE. Following initial screening procedures, identified expressed sequence tags (ESTs) can be used for marker development. In wheat and barley, initial groundwork has been laid through the BBSRC-funded “Investigating Gene Function” (IGF) initiative. For wheat, two N stress-response libraries have been produced in the variety Mercia, and for barley N-stress response root cDNA libraries have been generated from hydroponic material at SCRI (http:\\clatto.scri.sari.ac.uk/barleyIGF/). At INRA, France, EST generation has been undertaken using the variety Recital in controlled conditions at the vegetative stage on root and leaf material at 2 N levels and 4 EST libraries will soon be available on public databases (LeGouis, presentation at BBSRC-INRA workshop, Clermont Ferrand 21-22 April 2005). Transciptomics analysis is currently ongoing at INRA on the variety Arche (deficiency induction and relief) at 4 N levels using Génoplante chips. Transcriptomics is being used to identify plant genes whose expression is regulated by N status in two current projects at Rothamsted Research, one investigating the wheat endosperm transcriptome (BBSRC-funded) and the other investigating smart plant technology for sensing crop nutritional status (DEFRA-funded) (see Annex 3, section 5).
3.1.4. Transformation approachesTwo alternative methods for introducing foreign genes into crop plants are available: biolistics (DNA-coated metal particles used to physically bombard plant tissues), or Agrobacterium tumifaciens (used as a biological agent to deliver specific genes in the T-DNA vector). A DEFRA-funded research programme, BRACT, jointly run by Rothamsted Research and the John Innes Centre (JIC) has optimised protocols and aims to develop a crop transformation service to the UK research community (see: http://www.bract.org). Transformation has been used to demonstrate the role of genes determining GS1 expression influencing nitrate assimilation17. More generally, there are examples of successful genetic manipulation of the amount of Rubisco through transformation in several crops species, e.g. tobacco18, but not to date in cereals or rapeseed crops.
3.1.5. Traditional breeding approachesThe evidence for genotypic variation for the complex traits of NupE and NutE in wheat, barley, oats and OSR was assessed in the current project (see sections 2.1.1.2. and 2.1.2.2 above; and Annexes 2 and 3). In summary, there appears to be sufficient genetic variation in currently commercial germplasm to support future UK breeding progress in NUE. However, to our knowledge no UK-based breeding
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company has a programme aimed at optimising ‘direct selection’ breeding strategies to improve N economy in cereals or OSR. Elsewhere in the world at CIMMYT, Mexico an initial strategy proposed was to select for grain yield in medium-to-high fertility conditions, since they found that at this fertility level, both NupE and NutE contributed to the variation in NUE. New lines developed under intermediate levels of N were more N efficient than older lines. More recently, it has been suggested by CIMMYT that this method of selection, though successful, may not be as efficient as selecting lines under alternating high-low N selection regimes19. Le Gouis et al.5 reported the results of a diallel analysis at 2 N levels to assess heterosis and combining ability at INRA, France. The INRA programme is currently comparing direct and indirect selection methods for low N input levels and identification of potential parents (Le Gouis, presentation at BBSRC-INRA workshop, Clermont Ferrand 21-22 April 2005).
3.1.6. NUE and modelling approachesA large number of crop models are currently available for integrating knowledge on N uptake and utilization, e.g., SIRIUS, CERES-Wheat, CERES-Rape, DAISY and AFRCWHEAT2. Although the models differ in complexity, they are all based on similar conceptual frameworks, in which N availability and crop N are compared. Major sub-models are normally: (i) quantification of crop N demand, (ii) N uptake and assimilation (these two processes are generally not separated in models, and no differentiation is made between NH4+ and NO3-) and (iii) effects of N deficiency on crop growth and development. Some recent advances have been made in the integration of new molecular and physiological knowledge into mechanical models, e.g.20. However, the currently available models often fail to account for variety-specific responses.
3.2. Prioritisation of target traits for improving N economy3.2.1. Candidate traitsThe likely metabolic and physiological processes for future improvement of N economy in cereals and oilseed rape were reviewed and discussed in Annex 3. A brief summary of this review is set out below. The main candidate traits/processes included:
Root traits to improve N-uptake efficiency:- Increase root/shoot partitioning and root axis numbers (affected by root signalling and
phenology)- Increase rooting depth (affected by root-penetration rate and phenology) - Decrease specific root weight (= root dry weight per unit root length) - Increase root longevity (for post-anthesis uptake) - Changes in efficiency of root uptake processes (per unit root surface area)
… Increase number of N transporters … Optimize types of N transporters (respective expression of nitrate,
ammonium and organic N transporters)
Nitrate assimilation to improve N-uptake and N-utilization efficiency: - Optimize N status signaling from roots to shoots - Increase nitrate reductase and nitrite reductase amount/activity in roots and shoots - Optimize GS/GOGAT system - Optimize C/N interactions during nitrate assimilation
Leaf photosynthesis to improve N-utilization efficiency: Ribulose Bisphosphate Carboxylase/Oxygenase (Rubisco) is the carboxylating enzyme for CO2 fixation in the Benson-Calvin cycle, and this enzyme also acts as an oxygenase, releasing CO2 from previously fixed carbon during photorespiration. It constitutes up to 30% of the total leaf N by weight. Ribulose bisphosphate (RuBP) is the substrate in both reactions. Changing the size, amount or catalytic properties of Rubsico are the most likely routes to improving photosynthetic efficiency hence NutE.
- Metabolic changes in Rubsico… Decrease oxygenase activity of Rubisco, including introduction of higher catalytic rate
foreign forms of Rubisco… Increase rate of recovery from photoprotection of photosynthesis
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… Increase capacity for regeneration of RuBP via over-expression of sedoheptulose-1,7-bisphosphatase
- Reduce amount of N per unit leaf area… Reduce the amount of Rubsico … Reduce the size of Rubisco molecule… Reduce the amount of other leaf proteins
- C4 photosynthesis engineered into C3 crops
- Canopy architecture to improve N-utilization efficiency … Optimize N distribution within canopy leaf layers … Optimize stem N storage.… Reduce pod canopy size (to optimize light distribution in pod canopy; WOSR only).
N remobilization processes to improve N economy:- Improve remobilization (re-use) of N between vegetative tissues
… Delay leaf shed (WOSR only)… Optimize stem N storage (see above) … Optimize GS/GOGAT system (see above)
- Optimize ‘stay green’ traits (to optimise senescence and N remobilization according to crop species/end-use).
Grain protein composition to improve N economy:- Changes in protein composition of feed varieties to improve NutE and lower N content of animal
manures… Low % rumen degradable protein (feed cereals for ruminants)… High % essential amino acids (feed cereals for non-ruminants)
- Changes in protein composition of quality varieties … High % glutenins (bread-making wheat)
3.2.2. Prioritisation of candidate traitsOf the candidate traits set out above, those considered of most value for breeding in the ‘short term’ (< 10 years) are summarized in Table 4. Other more intractable traits but nevertheless of high potential impact in the longer term (> 20 years) are also indicated. In classifying traits we have taken account of their potential impacts on N economy, the likely extent of available genetic diversity in currently commercial UK germplasm and their likely heritability (see Annexes 2 and 3). Using the ‘short-term’ priority traits, trait ideotypes to improve N economy in feed/export winter wheats, bread-making winter wheats and WOSR are proposed in Figs 5a, 5b and 5c, respectively. These ideotypes are primarily designed to lower fertiliser N requirements below current RB209 recommendations whilst conserving yield and/or end-use quality, and to optimize protein content and composition in feed grain. However, the ideotypes for feed/export winter wheats and for WOSR should also serve to improve grain yield under low fertility conditions (organic/low N-input environments).
Table 4. Priority traits for the improvement of N economy in UK winter wheat and WOSR in the short and long-term
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Priority TraitsShort term Long term
Root growth- Increase root length density at depth- Increase root longevity (hence post anthesis uptake)
N status signalling (roots to shoots)- Improve NO3 uptake
Root activity- Increase N transporter density- Decreased efflux
Rubisco- High specificity for CO2 (red algae)
Stem N storage- Optimise stem N storage at anthesis according to crop species/end-use
N Remobilization to seed- Optimize ‘stay- green’ traits
N remobilization to seed- Optimize leaf-to-leaf, stem-to-grain, leaf-to-grain transfer according to crop species/end-use (GS/GOGAT)Seed protein composition- Reduce % rumen degradable protein (wheat/barley fed to ruminants)- Increase % essential amino acids (wheat/barley fed to non-ruminants) - Increase % glutens (wheat for bread-making)
Figure 5. Crop ideotypes for improved N economy in (a) winter wheat for feed/export (b) winter wheat for bread-making and (c) winter oilseed rape for feed and human use.
(a) Winter wheat grown for the feed/export markets
Figure 5 (b) Winter wheat grown for the bread-making market
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To lower the fertiliser N requirements of feed wheat varieties and N content of subsequent animal manures relates to high yields of low N grain. The requirements are for high N-uptake efficiency, but low remobilisation of N to the grain.
High N uptake efficiency is favoured by high root length density at depth Low stem N storage may reduce requirements for fertiliser N with little impact on crop photosynthesis. High internal recycling of N from senescing to new leaves is favoured by high glutamine synthetase activity. Low grain % rumen degradable N (ruminants) and high grain % essential a.a. (non-ruminants) may result in low N grain with minimal impact on livestock nutrition.
This ideotype should be associated with reduced requirements for N fertiliser and N content of organic manures.
Figure 5 (c) Winter oilseed rape grown for feed and human use
For feed winter barley, the traits comprising the N economy ideotype would be expected to be broadly the same as those identified for feed winter wheat in Fig 5a. It is possible though that root length density may be a higher priority than in wheat, due to the shorter period for root development to anthesis in barley and the shallower maximum rooting depth.
3.3. The rational application of genomics approaches to target traits
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To lower the fertiliser N requirement of winter oilseed rape varieties, whilst maintaining high yields of high oil content seed, requires high N-uptake efficiency, but low remobilisation of N to the seed.
High N uptake efficiency is favoured by high root length density at depth. Low and/or delayed leaf shed pre-anthesis will improve N remobilisation in the canopy and reduce fertiliser N requirement. N leaching losses should also be reduced. Low vegetative storage protein content in stems may reduce requirements for fertiliser N with little impact on crop photosynthesis. High internal recycling of N from senescing to new leaves is favoured by glutamine synthetase activity.
To improve the grain N% of bread-making wheat whilst maintaining yield and N fertiliser requirement requires a high N-uptake efficiency, and a high remobilisation of N to the grain. A combination of lower crop N uptake and high remobilization of N to the grain would favour accelerated senescence hence reduced yield.
High N-uptake efficiency is favoured by high root length density at depth. High stem N storage may result in increased N remobilizaton and high N grain with no change in N fertiliser requirement. High internal recycling of N from senescing to new leaves is favoured by high glutamine synthetase activity. High grain % glutenins may increase bread-making quality with no change in N fertiliser requirement.
This ideotype would be inconsistent with lowering fertiliser N requirements overall since lower N input implies lower crop N uptake.
The priority traits described above exist at different levels of biological organisation. They can be grouped into: (i) metabolic traits, operating at the level of the molecule and macromolecule, (ii) physiological cellular traits, operating at the level of the organelles and cells and (iii) physiological traits operating at the level of the plant organ, and the plant and community (crop). Generic statements can be made with regard to the applicability of the available genomics platforms for the various levels of trait to be addressed.
3.3.1. Metabolic traitsFor metabolic traits, e.g, those requiring phytochemical analysis or enzymology, phenotyping has involved the use of expensive and time-consuming assays generally precluding genetic analysis in experiments examining large numbers of genotypes. Consequently, the extent of genetic diversity in UK germplasm for these traits is largely unknown, and cost-effective, high-throughput phenotyping in breeders’ trials is difficult. New improved high-throughput metabolomics approaches will in the future help relieve some of these bottle-necks, both to aid phytochemical analysis and for facilitating enzyme activities. In the short-to-medium term, genetic analysis of these traits seems to depend principally on transcriptomics and/or transformation approaches in studies normally examining a relatively small number of genotypes. The success of ongoing studies will depend on the results of allied studies to elucidate: (i) the correlation between trait expression at the metabolic level and at higher levels of organization, (ii) understanding of the G x E between single plants in CE conditions and field crops, and (iii) understanding of the pleiotropic effects of gene(s) on non-target determinants of NUE. The metabolic candidate traits examined in the present study principally relate to nitrate assimilation and photochemistry:
Nitrate assimilation: There is considerable evidence for positive correlations between GS1 activity and components of NUE at the whole plant (glasshouse) level in wheat. Most work to date has focused on effects of over-expression of GS1 in transformed wheat plants. However, assays for GS1, although expensive, are feasible on small mapping populations. In such prospective molecular marker investigations, it may be possible to search for co-linearity between QTLs for the complex trait of NUE and genes coding for GS1 activity. Analysis of N signalling and of complex N/C interactions seems likely to remain within the remit of transformation techniques applied in model species in the long-term (> 20 years). The genetic manipulation of the nitrate/nitrite reductase enzymes may not be profitable since they are not well correlated with NUE.
Photochemistry:The development of tools to manipulate Rubisco amount/activity to improve NUE in breeding programs seems likely to be achievable only in the long-term (> 20 years). The introduction of algal genes coding for high-specificity-factor Rubisco could possibly be expedited by progress in transformation technologies, including the development of chloroplast transformation techniques. However, such breeding efforts may be affected by public acceptance of genetically modified cereals and OSR in European and world markets. In summary, manipulation of Rubisco seems likely to rely on application of transformation techniques in the foreseeable future, with some contribution from directed mutagenesis to make changes to DNA encoding for large/small Rubisco sub-units in cyanobacterial, algal and bacterial Rubiscos. Mutational approaches may also have a role in incorporation of C4
photochemistry into C3 plants, i.e., in the search for genes controlling plant anatomy, specifically the alteration of the arrangement of mesophyll and bundle sheath cells.
3.3.2. Physiological traits: cellularIn the present study, the main cellular traits addressed are root cell-membrane transporter systems affecting the absorption of nitrate and ammonium. To some extent, similar arguments can be applied to these traits as discussed above, with regard to high-throughput phenotyping and availability of reliable field-screening methodologies. For this reason, studies to date have been restricted to where only a limited number of genotypes are simultaneously characterised, e.g., transcriptomics and molecular mutational approaches. There is evidence for positive associations between expression of N transporter systems and crop N uptake, at least in OSR21. In summary, the potential for studies on N transporter systems to address lowering N fertiliser requirements in the short term seems moderately high. The genetic analysis of N transporter systems is most feasible by exploiting transcriptomics, and may thus be restricted to where comprehensive Affymetrix micro-arrays are available in the public domain, e.g., in wheat and barley. In order for transcriptomics techniques to provide useful information
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in terms of specific changes in gene expression, detailed physiological/developmental knowledge of sampled tissues is an absolute requirement. This detailed understanding exists at a sufficiently advanced level to permit transcriptome approaches to analyse root functioning.
3.3.3. Physiological traits: whole-organ Generally these traits are under multi-gene control and their genetic analysis has to date usually been addressed by the application of molecular-marker approaches to detect QTLs. The search for QTLs can now be informed through use of a number of additional genomics approaches. Association genetics mapping can be used to detect correlations arising from close linkage between markers and QTLs in non-experimental populations. Candidate gene approaches can be employed whereby candidate genes are identified either through transcrpitome studies in the relevant crop species or the identification of candidate genes in model species, e.g. rice or Arabidopsis, and the use of bioinformatics to identify the orthologue in the target crop species. Induced mutant alleles in candidate genes can be generated in mutant populations (e.g. TILLING populations) to generate new sources of genetic variation. In all cases, however, the successful genetic dissection of the trait will depend on the availability of precise, high-throughput phenotyping methodologies. Field phenotyping for whole-organ traits, although feasible on experiments examining many genotypes, is still generally time-consuming and expensive. The development of glasshouse or CE screens well correlated with field expression of traits will therefore be of high priority. The physiological whole-organ traits addressed in the present study principally relate to rooting and canopy traits.
Rooting traits:The primary root traits would appear to be rooting depth, rooting length density and root longevity (especially for post-anthesis uptake). Using the genomics tools outlined above to identify QTLs/markers is feasible for root traits in the short term, although there are still a number of obstacles. Phenotyping large mapping populations to identify QTLs for root traits has been demonstrated in the glasshouse, e.g. in rice22. However, these QTLs correlated poorly with QTLs for the same traits screened in the field. Poor correlations between CE and field phenotyping may make the application of mapping approaches to improve rooting traits difficult, since the expense of phenotyping solely in the field is currently generally prohibitive. So the development of screening techniques which are well correlated with field expression of traits will be critical to future success. There is evidence for genetic diversity in NupE and key rooting traits in UK germplasm for wheat in the literature. For OSR less information is available on differences in NupE and there is no information on rooting traits. For both cereals and OSR the current situation is that phenotyping trials to characterise genetic diversity and identify appropriate material must immediately precede genetic dissection of rooting traits. Phenotyping trials are currently ongoing in wheat (DEFRA WGIN NUE trial 04/05) but not in barley or OSR.
Canopy traits:Studies on canopy designs underlying NutE are critical in the genetic improvement of NUE aimed at lowering fertiliser N requirements. It will be important to target a small number of cardinal traits at specific developmental stages with most relevance to NutE. Genomics approaches can be applied to canopy traits in a similar way as described for rooting traits above. Field phenotyping of large mapping populations is generally feasible, but is not high-throughput and is expensive. The extent of genetic diversity for most of the canopy traits discussed in section 3.3 is not known in UK cereals or OSR germplasm, nor the extent of G x E hence likely heritability. Therefore studies addressing genetic analysis of these canopy N traits should include the characterisation of genetic variability for identification of contrasted responses to N deficiency. As for rooting traits, phenotyping trials to characterise genetic diversity and identify appropriate material should immediately precede genetic dissection of canopy traits. Phenotyping trials are currently ongoing in wheat (DEFRA WGIN NUE trials) to identify appropriate material but not in OSR or barley.
4. ROAD MAPS TO IMPROVE N ECONOMY OF UK CEREALS AND OSR
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Figure 6. Summary of inputs, research requirements and goals to underpin breeding of cereals and OSR with improved N economy in the UK.
The inputs and research requirements to deliver new commercial cultivars with improved N economy to reduce UK N emissions whilst conserving or ideally improving economic performance are summarized in figure 6. The generic ‘road map’ for the delivery of new commercial cultivars with improved N economy should include:
- Characterisation of genetic variability… Assessment of variability in NUE (uptake, utilization) and physiological traits … Identification of contrasting responses to low N… Assessment of the genetic variability through crop models… Assessment of variability for N metabolism enzymes
- Detection of QTL… QTLs for NUE (uptake, utilization) and physiological traits at low and high N levels … Comparison of QTL obtained on different crosses/species … Fine mapping of some QTL (backcross carried out)
- Identification of candidate genes… Identification of potential candidate genes through transcriptomal, molecular mutational and bioinformatics studies… Identification and mapping of genes of the N metabolism … Comparison of gene expression on different species
- Plant breeding programme… Identification of potential parents… Progeny selection using indirect selection (QTLs, high-throughput screens) at low N levels
In sections 4.1 to 4.4 below, the currently available resources (germplasm/phenotypic screens/genomics platforms) to deliver cultivar improvement through the ‘road map’ are set out for each of the four priority crop species/end-uses. Research requirements are then identified where investment is needed to fill in the gaps in the ‘road map’. A set of generic recommendations is then outlined.
4.1. Winter Wheat (Feed/export market) 4.1.1. Current available resources (germplasm/phenotyping/genomics)The ideotype combining priority traits for feed winter wheats was described in Fig 5a. Genetic analysis of the target traits firstly requires the characterisation of available genetic variation to identify appropriate material for genetic studies. For this, precise, high-throughput phenotypic screens are
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GENOTYPES
Transcriptomics, molecular markers
User requirementsDefinition of useful traits
Germplasm collections
Physiology/biochemistry
New commercial
varieties
RILs, DHLs
Existingvarieties
Assessment of G x Einteractions
Screens for candidate traits
Breeding
GOALS
INPUTS RESEARCH REQUIREMENTS
Markers for selection
Phenotyping
Modelling
necessary. Secondly there must be access to appropriate state-of-the-art genomics platforms to dissect the target traits.
4.1.1.1. Characterisation of genetic variability (germplasm/phenotyping)Germplasm:The resources currently available in the public domain to UK scientists include:
Germplasm collections:- - Gediflux collection: 500 European varieties including 200 coming from UK NL/RL- BBSRC collection (Triticum): named varieties (1787), breeders’ lines (2135), landraces (3658)- JIC Triticeae collection: wild/semi wild progenitors, advanced/improved cultivars, breeders’ lines,
synthetics, hybrids - JIC precise genetic stocks: (300+) aneuploids, alien introductions and miscellaneous
amphiploids, intervarietal substitutions
Cultivars/advanced lines:- - Adapted germplasm: UK NL/RL varieties, breeders’ advanced lines- Unadapted germplasm:
… CIMMYT’s International Winter Wheat Screening Nursery trial: advanced winter wheat lines (50+) grown at JIC
… CIMMYT synthetics: (500+) available via MTAs from CIMMYT
Mapping populations:- It is beyond the scope of this study to list all the mapping populations held in UK research organizations and private breeding companies potentially available for genetic studies. Summaries of populations in the public domain in Brassica are available (see below) where the number of populations involved is fewer, and a similar repository of information on mapping populations in wheat would be a useful resource to the research community. Nevertheless, the DEFRA WGIN project has identified nine publicly available DH populations available via standard MTAs; those which are relevant to feed/export wheat cultivars are listed below:
- Beaver (feed) x Soissons (bread-making) 65 lines- Rialto (feed/bread-making) x Spark (bread-making) 144 lines - Lynx (feed) x Cadenza (bread-making) 40 lines- Arina (bread-making) x Riband (feed) 120 lines - Lehmi (bread-making) x Claire (export) 120 lines - WEK069 (bread-making) x Hobbit (feed) (100+ lines)
Mutagenesis populations:- - Gamma radiation-derived Highbury spring wheat population (2,000+ M4-derived single seed
descent (SSD)) lines at JIC- DEFRA WGIN Ethyl methane sulphonate (EMS)-derived Paragon spring wheat population (5,000+ M2-derived SSD lines) at JIC- Three EMS-derived populations of Cadenza, in total 5,000 M2 lines, developed under WGIN at Rothamsted Research.
Phenotyping:The extent to which these germplasm resources have been phenotyped for priority traits under low and high N is outlined below:
NUE, NupE, NutE and stem N storage:- N-use efficiency, NupE and NutE are being characterized in DEFRA WGIN NUE trials at Rothamsted Research in 2003/4-5/6 (32 UK and continental cultivars). In addition, phenotyping of commercial cultivars for NUE components and stem N storage is ongoing in DEFRA-LINK project “Green Grain”.
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Rooting length density:-Variation in UK germplasm has not to date been characterised in phenotyping trials under low and high N. High-throughput CE and/or field rooting screens will be necessary to facilitate this phenotyping in future studies.
Root N transporters:-High-throughput screens are not currently available and genetic variation has not to date been characterised in phenotyping trials. New improved high-throughput metabolomics approaches may help in the future help to relieve this bottle-neck. Glutamine synthetase activity and grain protein composition (% EAA and RDP):-For GS activity and %RDP, genetic variation has not to date been characterised in phenotyping trials, although biochemical analytical techniques are available. Assessment of genetic variation in gliadin protein percentage indicative of % EAA is ongoing in DEFRA-LINK project “Green Grain”.
4.1.1.2. Genetic analysis of traits The available genomics resources in the UK were reviewed in Annex 4. This information is briefly summarized below. It should be noted that proteomics and metabolomics platforms were not addressed in this Scoping Study.
Molecular marker approaches:Publicly available molecular marker maps include:
- Maps for WGIN DH populations… Beaver x Soissons 200+ (SSR + AFLP) … Rialto x Spark 800+ (SSR + AFLP) … Avalon x Cadenza (400+ SSR + STMP) … Lynx x Cadenza 81 (SSR)… Arina x Riband 200+ (SSR + AFLP) … Lehmi x Claire 100+ (SSR + AFLP)… WEK069 x Hobbit 200+ (SSR + AFLP)
- International Triticeae Mapping Initiative (ITMI) map: a high density RFLP/SSR map for synthetic x Opata M85 (http://www.scri.sari.ac.uk/ITMI/Default.htm)
More generally, a comprehensive list of wheat maps derived from different crosses worldwide is available at Graingenes: http://wheat.pw.usda.gov/ggpages/maps.shtml. For discovery of highly specific markers, a SNP marker discovery programme is being developed at BBSRC IFG; http://www.cerealsDB.uk.net/discover.htm.
Transcriptome profiling approaches:Currently available wheat arrays include:
- BBSRC IGF array : representing a 10K unigene set (http://www.cerealsdb.uk.net/igf.htm).- Affymetrix wheat chip: released (in 2005) with approximately 20,000 unique genes represented: http://www.affymetrix.com/products/arrays/specific/wheat.affx
Bioinformatics resources for candidate gene discovery include: - Gramene: A Comparative Mapping Resource for Grains: http://www.gramene.org/ - Resources for Comparative Plant Genomics: http://www.plantgdb.org/ - Rice genome programme (Japan) http://rgp.dna.affrc.go.jp- TAIR in the USA: http://www.arabidopsis.org/, NASC in the EU http://nasc.nott.ac.uk/home.html - The Arabidopsis 2010 project: (http://www.nsf.gov/pubs/2002/bio0202/start.htm
Mutagenesis approaches:The available platforms in the UK include:
- Mutagenesis systems: EMS and/or low-level gamma-radiation systems are in place at JIC. - Transposon procedures: systems are in place at JIC and Rothamsted Research
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- TILLING (Targeted Induced Local Lesions In Genomes): procedures developed at JIC are being optimised at Rothamsted Research under DEFRA WGIN to provide a TILLING service to the UK research community.
Transformation approaches:A DEFRA-funded research programme, BRACT, jointly run by Rothamsted Research and JIC is currently optimising protocols as mentioned above and aims to develop a crop transformation service to the UK research community, see: http://www.bract.org/
4.1.2. Research requirements In this section, as guidance to DEFRA, future research requirements are identified where investment is needed to fill in the gaps in the ‘road map’.
4.1.2.1. Characterisation of genetic variability Germplasm:The most efficient use of DEFRA funding will be to put in place core germplasm resources (e.g., mapping populations, mutant populations) that can serve as central resources for the UK research community.
Mapping populations:- Present results (Annex 2) indicate that the WGIN DH population Beaver (high NutE) x Soissons (low NutE) may be suitable as a core resource for investigating traits underlying NutE, e.g. stem N storage and GS activity. No WGIN population, with at least one parent as a feed wheat, could be identified sufficiently contrasting for NupE. So analysis of rooting traits underlying NupE in feed wheats will require the use of alternative existing populations or the development of new population(s). For grain protein composition traits (%EAA and % RDP), preliminary phenotyping studies are needed to identify appropriate germplasm for genetic studies.
Mutant populations:-No mutant population is available in the public domain in a winter wheat background. Although some progress can be achieved by generating new allelic diversity in the spring wheat backgrounds, progress may be faster by developing population(s) in winter wheat.
Germplasm collections:-Appropriate collections are already available as outlined above.
Phenotyping:To facilitate the genetic analysis of traits in the short and long term, there is a general requirement for the development of precise, high-throughput phenotypic screens, e.g. for rooting and stem N storage traits. The lack of the development of such ‘smart-screens’ may constitute a bottle-neck to the successful application of the genomics approaches to improve NUE discussed in this report.
4.1.2.2. Genetic analysis of traits The genomics technologies (marker technology, wheat arrays, mutagenesis systems etc) are largely in place, and there is a requirement now for their exploitation to identify genes/markers for priority traits, as outlined below. Continued emphasis on the development of bioinformatics tools will be important to underpin candidate gene approaches.
Rooting traits, stem N storage and GS regulation:In parallel to mapping and QTL detection, transcriptomics approaches should be applied on specific contrasting lines to define more accurately genetic components and to identify candidate genes through syntenic relationships with Arabidopsis and rice. Studies should aim to identify co-linearity between physical locations of putative QTLs and ESTs. Mutant populations offer scope to test whether wheat orthologues have related functions to candidate genes in Arabidopsis and rice. It should be noted that genetic analysis of stem N storage traits in feed wheats using QTL approaches is ongoing in DEFRA-LINK project “Green Grain” and several QTL relating to GS activity in a Chinese Spring x SQ1 population were recently identified in EU-funded project SUSTAIN (see Annex 3, section 5).
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Grain protein content/composition: There is currently little available information on whether there is sufficient genetic diversity in grain protein composition traits (%EAA and % RDP) to underpin breeding for improved N economy. Preliminary phenotyping to assess variation in UK adapted wheat germplasm is therefore required. It should be noted that assessment of genetic variation for % EEA is on-going in DEFRA-LINK project “Green Grain”.
For all traits, the assessment of two or more mapping populations in multi-locations will be necessary to confirm the stability of QTLs across genetic backgrounds and environments.
4.2. Winter Wheat (Bread-making market) 4.2.1. Current available resources (germplasm/phenotyping/genomics)The ideotype combining priority traits for bread-making winter wheats to improve N economy was described in Fig 5b.
4.2.1.1. Characterisation of genetic variability Germplasm:The germplasm resources currently available in the public domain are essentially the same as those described above for feed wheats in 4.1.1.1 expect that the relevant WGIN DH populations also include Avalon (bread-making) x Cadenza (bread-making), 204 lines.
Phenotyping:The extent to which the germplasm resources have been characterised for priority traits under low and high N for is again largely as described in 4.1.1.1 For the fraction of grain protein as glutenin, genetic variation has not been well characterised to date in phenotyping trials, although biochemical analytical techniques are available.
4.2.1.2. Genetic analysis of traits The available genomics resources are as outlined above in 4.1.1.1, except that an additional molecular high density marker map is available for Avalon x Cadenza (400+ SSR + STMP), developed at JIC under WGIN.
4.2.2. Research requirements 4.2.2.1. Characterisation of the genetic variability Germplasm:The most efficient use of DEFRA funding will again be to put in place core germplasm resources that can serve as central resources for the UK science community.
Mapping populations:- Results of present study (Annex 2) and WGIN NUE trials indicate that the WGIN DH population Avalon (low NupE, bread-making) x Cadenza (high NupE, bread-making) contrasts for NupE and may serve as a core population for analysis of rooting traits. As outlined above, the WGIN population Beaver (feed, high NutE) x Soissons (bread-making, low NutE) may serve as a core population for traits underlying NutE for both feed and bread-making wheats. For the glutenin protein %, preliminary phenotyping studies are needed to identify appropriate germplasm for genetic studies.
Mutant populations:- Resources are already available as described above.
Germplasm collections:- Appropriate collections are already available as described above.
Phenotyoping:The recommendations set out above under 4.1.2.1 in relation to the development of phenotypic screens for feed wheats also apply to bread-making wheats.
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4.2.2.2. Genetic analysis of traitsAs for feed wheats, the genomics technologies (marker maps, wheat arrays, mutatgenesis systems) are largely in place and there is a requirement now for their exploitation to identify genes/markers for each of the priority traits, as outlined below:
Rooting, stem N storage and GS activity:Although the direction of desirable trait expressions is sometimes different (e.g. high stem N storage for bread-making wheats cf. low stem N storage for feed wheats), the road map is essentially as outlined under feed wheats.
Grain protein composition:There is to date little information on whether there is sufficient genetic diversity in protein glutenin % to justify breeding interventions, and therefore preliminary phenotyping studies are needed to identify appropriate germplasm for genetic studies.
4.3. Winter Oilseed rape (all end uses) 4.3.1. Current available resources (germplasm/phenotyping/genomics)The ideotype combining priority traits for winter oilseed rape to improve N economy was described in Fig 5c.
4.3.1.1. Characterisation of the genetic variabilityGermplasm:Oilseed rape (B. napus) has an allotetraploid genome, being made up of the diploid B. rapa and B. oleracea nuclear genomes. When combined in oilseed rape the diploid genomes result in extensive genetic replication which reduces the sensitivity for QTL detection in oilseed rape. Therefore as well as carrying out QTL analyses in oilseed rape, it will be useful to examine the diploid species to aid QTL detection. The germplasm resources currently available in the public domain to UK scientists include:
Germplasm collections:-- DEFRA OREGIN Diversity Fixed Foundation Set (DFFS): 188 lines of B. napus selected to represent the majority of allelic variation within the gene-pool.
Cultivars/advanced lines:- - Adapted germplasm: UK NL/RL varieties, breeders’ advanced lines
Mapping DH populations:- - B. napus
… “TN” Tapidor x Ningyou OREGIN reference mapping population: winter: x semi-winter, 188 lines, developed in China
… “MS” Major x Stellae population: winter x spring, 100 lines, developed in USA … “DY” population: winter x spring, 120 lines, developed in France… “SG” population: spring x reysnthesised, 300 lines, developed in Canada
- B. oleracea DH reference mapping populations (Warwick HRI; WHRI)… A12DHd x GDDH33: rapid cycling (A) x Calabrese (G), 100 lines… CA25 x AC498: cauliflower (N) x Brussels sprout (G), 100 lines
- B. rapa DH reference mapping populations (WHRI)… Chiifu-401 x Kenshin-402… Chinese cabbage (C) x Chinese cabbage (K)
A summary of public domain mapping populations worldwide in B. oleracea and B. rapa is available at: www.brassica.info/resources/cwg_notes_resources.htm
Mutant populations:- No populations have been developed in the UK. A summary of mutant populations in the public domain worldwide is available at: www.brassica.info/resources/cwg_notes_resources.htm
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Phenotyping:Present results suggest there is genetic variation in B. napus in NUE (uptake and utilization), e.g. from yield responses of NL/RL cultivars to contrasting N (Annex 2) and from characterisation of NUE traits in Germany and Australia (Annexes 2 and 3). However, as far as we are aware no phenotyping for NUE (uptake, utilization) or underlying traits has been carried out on any material from the germplasm resources outlined above under low and high N.
4.3.1.2. Genetic analysis of traits The available genomics resources in the UK were reviewed in Annex 4. This information is briefly summarised is below.
Molecular marker approaches:Publicly available molecular marker maps include:
- B. napus (WHRI) … “TN” Tapidor x Ningyou OREGIN reference mapping population: 381-markers (92
SNPs, 184 SSRs and RFLPs). Selected markers from this map are being used to characterize the molecular allelic variation within the OREGIN DFFS.
- B. oleracea (WHRI)… A12DHd x GDDH33 and CA25 x AC498 population: an integrated map (547 markers,
SSRs and AFLPs) for these two populations has been developed.
A detailed summary of publicly available microsatellites can be found at the Brassica Microsatellite Information Exchange www.brassica.info/resources/cwg_notes_resources.htm developed at WHRI.
Transcriptome profiling approaches:Currently available resources in Brassica spp. include:
- Approx. 38,000 EST sequences available at NCBI from various national sequencing programmes for B. napus (http://www.ncbi.nlm.nih.gov/Taxonomy/Browser/wwwtax.cgi?
mode=Info&id=3708&lvl=3&p=17&p=20&p=37&p=38&lin=f&keep=1&srchmode=1&unlock). - Large-scale oligo arrrays are not yet publicly available in Brassica but are currently being
developed in several multinational programmes.- Information on Brassica BAC libraries is available as part of a BBSRC funded IGF project; http://Brassica.bbsrc.ac.uk/ (UK).
Bioinformatics resources for candidate gene discovery include: - Resources for Comparative Plant Genomics: http://www.plantgdb.org - Rice genome programme (Japan) http://rgp.dna.affrc.go.jp- TAIR in the USA: http://www.arabidopsis.org/, NASC in the EU http://nasc.nott.ac.uk/home.html - The Arabidopsis 2010 project: (http://www.nsf.gov/pubs/2002/bio0202/start.htm
Mutagenesis approaches: The available platforms in the UK include:
- Mutagenesis systems: systems based on EMS and low-level gamma-radiation are in place at JIC
- Transposon procedures: systems are in place at JIC and Rothamsted Research - TILLING (Targeted Induced Local Lesions In Genomes): procedures have not yet been
optimised in Brassica spp.
Transformation approaches:The DEFRA-funded research programme, BRACT, jointly run by Rothamsted Research and the John Innes Centre is currently optimising protocols (see: http://www.bract.org).
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4.3.2. Research requirements 4.3.2.1. Characterisation of the genetic variability
Germplasm:Germplasm resources have been put in place by DEFRA OREGIN (Diversity Fixed Foundation Set), and mapping populations with associated high density maps are available from the collections at WHRI as described above. It is not currently know whether the WHRI mapping populations represent sufficient genetic variation for the priority traits to underpin breeding for improved NUE. So preliminary phenotyping trials must precede genetic analysis of traits (see below) to identify the most appropriate material. However, it seems unlikely that new germplasm resources will be required in the short-to-medium term. In the event that the mapping populations do not represent sufficient genetic variation for key traits, the DFFS can be used through association genetics studies to identify genetic loci associated with target traits.
Phenotyping: As for wheat, there is a requirement for the development of precise, high-throughput phenotypic screens, e.g., for rooting and stem N storage traits. Material assessed in phenotyping trials should include selected lines from the OREGIN DFFS and parents of the WHRI mapping populations together with parents of key populations held by the private breeding companies.
4.3.2.2. Genetic analysis of traitsThe marker technologies (existing high density maps, SSR, SNps etc) are largely in place. Large-scale oligo-arrays are not currently available but are in the pipeline and should be available within a 1-2 year timeframe. Continued emphasis on the development of bioinformatics tools will be important to underpin candidate gene approaches. As for wheat, studies bridging the respective genomics platforms and integrating physiological/development analysis are required. There is scope to identify genes/markers for each of the priority traits in the N economy ideotype (Fig 5c). In each case, studies aimed at QTL detection should aim to identify candidate genes through syntenic relationships with Arabidopsis and saturate Brassica maps in the region of the orthologues. Studies on the OREGIN DFFS using association genetics are also justified. As in wheat, the aim should be to address NUE traits in co-ordinated work-packages providing information on QTL stability and trait interactions. It should be noted that two recently commissioned DEFRA-LINK projects, “Breeding oilseed rape with a low requirement for nitrogen fertiliser” and “Novel resources for oilseed rape breeding: Improving harvest index (ORB-LINK)”, will address several of the target traits outlined above. For example, rooting and stem N storage traits will be addressed using QTL approaches in DEFRA-LINK “Breeding oilseed rape with a low requirement for nitrogen fertiliser”
4.4. Winter Barley (Feed/export market) 4.4.1. Current available resources (germplasm/phenotyping/genomics)The ideotype combining priority traits for feed winter barley will likely comprise most of the traits relevant to feed wheats outlined in Fig 5.a, namely: high root length density, high no. N transporters/unit root length namely, high GS activity, low stem N storage, low total grain N, high % EAA and low %RDP.
4.4.1.1. Characterisation of the genetic variability Germplasm:The germplasm resources currently available in the public domain to UK scientists include:
Germplasm collections:-- BBSRC collection (Hordeum): UK holdings 710 named varieties, 924 breeders’ lines. 1954
named varieties, 2038 breeders’ lines, 4500 landraces or selections from landraces, 330 genetic stocks.
Cultivars/advanced lines:- - Adapted germplasm: UK NL/RL varieties, breeders advanced lines- Unadapted germplasm: ICARDA International Winter Barley Screening Nursery trial
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Mapping populations:- It is beyond the scope of this study to list all the mapping populations that UK research organizations and private breeding companies would potentially be prepared to place in the pubic domain and more generally publicly available mapping populations worldwide. As for wheat, a repository of information on mapping populations potentially available for genetic studies via standard MTAs in barley would be a useful resource to the research community. A number of mapping populations in spring barely have been developed at the Scottish Crop Research Institute (SCRI). However, no publicly available populations in feed winter barley are available equivalent to those identified under the WGIN project for winter wheat.
Mutant populations:- Two large-scale EMS-derived mutant populations from spring barley cv. Optic (each 10,000+ M2s) are available at SCRI.
Phenotyping:Present results show evidence for genetic variation in barley in NUE (uptake and utilization) and underlying traits, e.g. rooting traits (Annex 3). However, as far as we are aware, no field phenotyping for NUE or underlying physiological traits has been carried out on any material from the germplasm resources outlined above under low and high N. Using a laboratory-based 2-D plate screen, a DH population Derkado x B83-12/21/5 in spring barley has been characterized for seedling rooting number and root length density for QTL detection. The Optic mutant lines at SCRI have been similarly characterized for rooting traits. 4.4.1.2. Genetic analysis of traits Molecular marker approaches:A comprehensive list of barley maps derived from different crosses worldwide is available at NCBI (http://www.ncbi.nih.gov/mapview/map_search.cgi?taxid=4513).
Transcriptome profiling approaches:Currently available barley arrays include:
- BarleyBase (USA), community resource for barley microarray resources; http://barleypop.vrac.iastate.edu/BarleyBase/
- Barley Affymetrix arrays have been produced as a public-commercial collaboration: http://www.affymetrix.com/products/arrays/specific/barley.affx. SCRI has developed a reference developmental gene expression dataset using the Affymetrix Barley1 GeneChip array.
Bioinformatics resources for candidate gene discovery include those listed for wheat under 4.1 above. ESTs sequenced from N-stressed roots have been developed at SCRI, and affy experiments have been carried out on the same roots. SNP discovery on 1500 differentially expressed root genes (in response to stress) in 8-24 barley genotypes is ongoing at SCRI.
Mutagenesis approaches:The available platforms in the UK include:
- Mutagenesis systems: EMS systems are in place at SCRI. - Mutation grid: A high density barley deletion mutation grid has been developed at SCRI
available as a communal resource funded by the BBSRC Gene Function Initiative.- Transposon procedures: systems are in place as SCRI. - TILLING (Targeted Induced Local Lesions In Genomes): procedures have been optimised at
SCRI.
Transformation approaches:BRACT, jointly run by Rothamsted Research and the John Innes Centre is currently optimising protocols as described above, see: http://www.bract.org/.
4.4.2. Research requirements 4.1.2.1. Characterisation of the genetic variability Germplasm:Again it will be desirable to develop core germplasm resources (e.g. mapping populations, mutant populations) that can serve as central resources for the UK research community.
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Mapping populations:- No mapping populations equivalent to WGIN DH populations are available to UK researchers under standard MTAs in barley. Rooting traits have been assessed in some spring barley mapping populations at SCRI as mentioned above. However, field phenotyping to assess the genetic variation in NUE (uptake, utilization) and underlying traits is required as a preliminary to identifying appropriate mapping populations for respective traits (see below). Mutant populations:- The mutant populations in cv Optic should provide a basis for forward and reverse genetics studies to investigate the genetics of target traits. Phenotypic data are already available from seedling root screens.
Germplasm collections:-Appropriate collections are already available as outlined above.
Phenotyping:The previous comments in relation to the development of phenotypic screens also apply to winter barley.
4.1.2.2. Genetic analysis of traitsThe genomics technologies (marker technology, barley arrays, mutatagenesis systems etc) are again largely in place, and as for the other crop species/end-uses there is a requirement now for their exploitation to identify genes/markers for each of the priority traits, as outlined below:
Rooting traits, stem N storage and GS regulation::Studies on these traits should generally follow the ‘road map’ outlined above under 4.1 for feed wheats. In addition, there is scope to exploit ongoing activities in Association Genetics. An SCRI-led consortium has recently been funded to carry out a large association genetics LINK programme in elite cultivated barleys (AGOUEB). This project involves genotyping >1000 accessions at approximately 3000 SNP loci distributed across the barley genome. The SNPs were derived partially from root genes that are differentially expressed in response to a range of abiotic stresses. The majority of the effort in AGOUEB is devoted to collating historical phenotypic data and supplementing this with data from new trials carried out around the UK. This phenotypic information in AGOUEB will be exclusively above ground characteristics, and there may be scope in new studies to supplement this phenotypic dataset with below-ground rooting characters.
Grain protein content/composition: Preliminary phenotyping studies to assess genetic variation in %EAA and %RDP in UK adapted wheat germplasm is needed to identify appropriate germplasm for genetic studies.
5. GENERIC RECOMMENDATIONS
5.1 Definition of useful mapping populations Further information should be sought about NUE and underlying traits for parental lines of well characterised mapping populations through phenotyping trials. Studies similar to the NUE trials carried under DEFRA WGIN should be considered in OSR and barley.
5.2 CE ‘smart-screens’ for phenotyping genetic diversity To facilitate the genetic analysis of traits underlying NUE in the short and long term, there is a requirement for the development of precise phenotyping methodologies for assessing key traits, for which CE screening is well correlated to field expression of traits.
5.3 Crop physiology: modelling There is a requirement to analyse the effect of changes in physiological traits on NUE to aid trait prioritisation. Crop simulation models provide one approach for achieving this by integrating un-derstanding of complex plant processes. Such quantitative frameworks should be developed with a view to designing virtual crop ideotypes with optimum NUE for specific environments and/or end-uses.
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For this purpose, more information is required about inter-relationships between plant and crop NUE processes and genetic variation, e.g., available models often fail to account for cultivar-specific responses
5.4 Genomics Genomics approaches should be based on well characterised plant material, at the genetic and physiological/developmental levels. Transcriptome analysis should provide useful information on gene expression related to N utilisation and uptake, that may highlight potentially important genes. Mapping in association with marker development should also provide more information on genomic regions associated with NUE. Ideally NUE components (NupE and NutE) and underlying traits should be simultaneously mapped to search for co-located QTLs.
5.5 Informatics Although proteomics and metabolomics were not addressed in this Scoping Study, there will be a likely requirement for the study of appropriate genotypes combining multi-disciplinary approaches, namely transcriptomics, proteomics and metabolomics with appropriate bioinformatics support. Informatics datasets should input into modelling studies.
[These recommendations mirror generic recommendations made recently within the BBSRC Crop Science Review (HREF="http://www.bbsrc.ac.uk/news/reports/crop_sci_review12_05_04.html") for the delivery of high quality crop science addressing traits associated with sustainability of production.]
The aim for future research activities should be to genetically dissect traits for the chosen crops in a suite of co-ordinated work packages which will deliver significant underpinning advances. Coordination of research efforts across several relevant research organisations will be needed to achieve this. There is a requirement for sustained funding to enable the setting up and running of a ‘UK NUE Network’ which is problem (i.e., NUE based) rather than crop based. Provisions should also be made for regular forums for feedback to DEFRA and the user community.
6. ANNEXES
The full details of project findings are presented in five annexes, namely:
(1) Annex 1: An environmental and economic potential-impacts analysis (2) Annex 2: An analysis of varietal differences in NUE in UK National List (NL) and Recommended
List (RL) trials (3) Annex 3: A scientific review of physiological processes influencing N economy (4) Annex 4: A scientific review of crop genomics technologies and their potential application in
improving N economy(5) Annex 5: The basis for the selection of varieties in WGIN NUE phenotyping trial (04/05)
7. ACKNOWLEDGEMENTS
We thank Cereal Evaluation Ltd for extending the NIAB’s access to CEL’s data for the purpose of the present research project in relation to the analysis of genetic variation in NUE components set out in Annex 2. We thank Doug Warner of AERU, University of Hertfordshire for contributing the section on ‘Impact of Reducing Nitrogen Use on Nitrate Leaching and Greenhouse Gas Emissions’ in the potential impacts analysis set out in Annex 1. We thank J. Wiseman and P. Garnsworthy of University of Nottingham for their contributions on protein requirements of livestock diets in Annex 3. We also thank the following scientific experts for their useful and constructive comments on draft manuscripts of Annex 3: Ian Bingham (SAC, Aberdeen), Graham Russell (Univ Edinburgh), R. Sylvester-Bradley (ADAS Boxworth), S. Rawsthorne (JIC), K. Walker (SAC, Aberdeen) and B. Fitt (Rothamsted Research).
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References1. Goulding, K.W.T. 2004. Minimising losses of nitrogen from UK agriculture. Journal of the Royal Agricultural Society of England 165: 1-11.2. Sylvester-Bradley, R. 1993. Scope for more efficient use of fertiliser nitrogen. Soil Use and Management 9, 112-117.3. Sylvester-Bradley, R., Lord, E., Sparkes, D.L., Scott, R.K., Wiltshire, J.J.J. & Orson, J. 1999. An analysis of the potential of precision farming in Northern Europe. Soil use and management 15:1-8.4. Ortiz-Monasterio, J.I., Sayre, K.D., Rajaram, S. & McMahom, M. 1997. Genetic progress in wheat yield and nitrogen use efficiency under four nitrogen rates. Crop Science 37, 898-904. 5. Le Gouis, J., Beghin, D., Heumez, E. & Pluchard, P. 2002. Diallel Analysis of Winter Wheat at Two Nitrogen Levels Crop Science 2002 42, 1129-1134. 6. Nyikako, JA (2003) Genetic variation for nitrogen use efficiency in oilseed rape (Brassica napus L.). PhD Thesis. The University of Gottingen, Germany 7.Yau, SK & Thurling, N (1987) Variation in nitrogen response among spring rape (Brassica napus L.) cultivars and its relationship to nitrogen uptake and utilization. Field Crop Reserach 16, 139-155.8. Rotz, C.A. 2004. Management to reduce nitrogen losses in animal production. Journal of Animal Science 82: 119- 137.9. N.R.C. 1998. Nutrient requirements of poultry. 9th revised edition. National Academy of Science, Washington D.C.10. Han, I.K and Lee, H.H. (2000). The role of synthetic amino acids in monogastric animla production. Asian-Australian Journal of Animal Science 14: 432-444. 11. DEFRA (1999) CAP Reform: Potential for Effects of Environmental Impact on Farming (SA0111). Report for MAFF (ACD) by ADAS and CSL22 January 1999.12. Nix, J., (2005) Farm Management Pocketbook, 34th edition. 13. Hirel, B, Bertin, P, Quillere, I, Bourdoncle, W, Attagnant, C, Dellay, C, Aurelia, G, Sandrine, C, Retaillau, C, Mathieu, M & Gallais, A. (2001) Towards a better understanding of the genetic and physiological basis fro nitrogen use efficiency in maize. Plant Physiology 125, 1258-1270.14. Evans, AS (1991) "Leaf Physiological-Aspects of Nitrogen-Use Efficiency in Brassica campestris L - Quantitative Genetic-Variation across Nutrient Treatments." Theoretical and Applied Genetics 81, 64-70.15. Mickelson, S., et al. (2003). Mapping of QTL associated with nitrogen storage and remobilization in barley (Triticum vulgare L.) leaves." Journal of Experimental Botany 54, 801-812.16. Loudet, O., Chaillou, S., Merigout, P., Talbotec, J. & Daniel-Vedele, F. 2003. Quantitative trait loci analysis of nitrogen use efficiency in Arabidopsis. Plant Physiology 131: 345-358.17. Habash DZ, Massiah AJ, Rong HL, Wallsgrove RM & Leigh RA (2001) The role of cytosolic glutamine synthetase in wheat. Annals of Applied Biology 138, 83-89.18. Rodermel SR, Abbott MS, Bogorad L. (1988) Nuclear-organelle interactions: nuclear antisense gene inhibits ribulose bisphosphate carboxylase enzyme levels in transformed tobacco plants. Cell 56, 673–681.19. VanGinkel, M, Ortiz-Monasterio, I, Trethowan, R & Hernandez, E (2001) methodology for selecting segregating populations for improved nitrogen use efficiency in bread wheat. Euphytica 119 223-230. 20. Malagoli, P, Laine, P, Le Deunff, E, Rossato, L, Ney, B & Ourry, A (2004) Modelling nitrogen uptake in oilseed rape cv capitol during a growth cycle using influx kinetics of root nitrate transport systems and field experimental data. Plant Physiology 134 , 388-400.21. Jeuffroy, MH, Ney B & Ourry, A (2002) Integrated physiological and agronomic modelling of N capture and use within the plant. Journal of Experimental Botany, 53, 809-823 22. Price, AH, Steele, KA., Moore, BJ, Jones, RGW (2002) Upland rice grown in soil-filled chambers and exposed to contrasting water-deficit regimes II. Mapping quantitative trait loci for root morphology and distribution. Field Crops Research 76, 25-43.
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References to published material9. This section should be used to record links (hypertext links where possible) or references to other
published material generated by, or relating to this project.
Genetic improvement of nitrogen economy of winter wheat in the UK (2004) J. Foulkes, P. Barraclough, M. Hawkesford, M. Holdsworth, S. Kerr, J. Law, S. Kightley & P. Shewry. Book of Abstracts of the AAB Centenary Conference, Advances in Applied Biology: providing New Opportunities to Producers and Consumers in the 21st Century. at St Catherine’s College Oxford 15-17 December 2004.
The findings of this project have been used to inform the research activities of the DEFRA Wheat Genetic Improvement Network (WGIN) and the DEFRA Oilseed Rape Genetic Improvement Network (OREGIN). The selection of genotypes phenotyped in the DEFRA WGIN NUE trials 2003/4 – 2005/6 at Rothamsted Research was informed by analysis carried out under objective 1 (see Annex 5).
The findings of the project were discussed with UK breeders through presentations made at Steering Group meetings and Stakeholders meetings of WGIN and OREGIN:
WGIN meetings : i) Presentation by J. Foulkes at the WGIN Traits Workshop at Rothamsted Research 10 June 2004. ii) Meeting to discuss WGIN Research 2004/5 (Phenotyping Trials) 27 August 2004 at ADAS-Boxworth.iii) Discussion of WGIN NUE trial 2003/4 and proposed WGIN NUE trial 2004/5 at WGIN Steering Group meeting held at JIC on 6 July 2004. iv) Presentations by J Foulkes, M. Hawkesford, S. Kerr and P. Barraclough to DEFRA Project AR0714 NUE Workshop held at Rothamsted on 27 October 2004.
OREGIN meetings:i) Presentation by J. Foulkes to OREGIN Stakeholders meeting on 23 March 2004 at HRI, Wellesbourne.ii) Presentation by J. Foulkes to OREGIN Stakeholders meeting on 23 March 2005 at NIAB, Cambridge.
The findings of this project in the form of DEFRA bi-monthly interim reports were also used by DEFRA when assessing DEFRA LINK proposals addressing NUE. During the Scoping Study three DEFRA-LINK funded projects addressing improvement of NUE in cereals and OSR have been funded:
DEFRA-LINK project Genetic reduction of energy use and emissions of nitrogen through cereal production (Green Grain)DEFRA-LINK Project LK0964 Novel resources for oilseed rape breeding. Improving harvest index (ORB-LINK) DEFRA-LINK project DEFRA-LINK project Breeding oilseed rape with a low requirement for nitrogen fertiliser
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