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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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ACCESS TO INFORMATIONThe information collected on this form will be stored electronically and may be sent to any part of Defra, or to individual researchers or organisations outside Defra for the purposes of reviewing the project. Defra may also disclose the information to any outside organisation acting as an agent authorised by Defra to process final research reports on its behalf. Defra intends to publish this form on its website, unless there are strong reasons not to, which fully comply with exemptions under the Environmental Information Regulations or the Freedom of Information Act 2000.Defra may be required to release information, including personal data and commercial information, on request under the Environmental Information Regulations or the Freedom of Information Act 2000. However, Defra will not permit any unwarranted breach of confidentiality or act in contravention of its obligations under the Data Protection Act 1998. Defra or its appointed agents may use the name, address or other details on your form to contact you in connection with occasional customer research aimed at improving the processes through which Defra works with its contractors.

Project identification

1. Defra Project code LS3648

2. Project title

Identification, genetic control and evaluation of traits enhancing environmental quality and bioremediation in multifunctional grassland

3. Contractororganisation(s)

Institute of Grassland and Environmental Research Aberystwyth Research CentrePlas Gogerddan, Aberystwyth,CeredigionSY23 3EB     

54. Total Defra project costs £ 450,819(agreed fixed price)

5. Project: start date................ 01 July 2003

end date................. 30 June 2007

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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.

(b) If you have answered NO, please explain why the Final report should not be released into public domain

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 project aimed to provide an initial identification and map for the genetic elements in perennial ryegrass (Lolium perenne L.), for quantitative traits which could be exploited through ‘marker assisted’ precision breeding to enhance the range of ‘ecosystem services’ and environmental benefits provided by UK grassland. The traits surveyed included those associated with bioremediation of heavy metals and other pollutants, 'buffer zone' efficiency for nitrate, C-sequestration, functional soil microbial activity and aspects of plant water relations, none of which have been targeted in forage species breeding programmes before. The precision breeding of new cultivars conferring ‘added environmental value’ for use in multi-functional grassland systems meets Defra’s Strategy for Sustainable Farming and Food as a measure to enhance the environment and add environmental value to enterprises, and to provide new options within future agri-environment schemes.

The approach taken throughout the project was to characterise the variation in the traits within an existing perennial ryegrass mapping family, at a range of scales from single plant to sward, and to identify Quantitative Trait Loci (QTLs) on an outline genetic map based on molecular markers produced by Amplified fragment length polymorphism (AFLP) analysis. IGER’s amenity x forage type Lolium perenne mapping family was selected for this purpose, primarily because it includes a wide range of growth and Phenotyping (> 150 traits) across 94 mapping family genotypes was conducted over four years on four experimental platforms to promote cross-referencing at a range of scales from the single plant to the field-based sward. (1) IGER’s flowing solution culture system was used primarily at the single plant level to characterise heavy metal tolerance and accumulation. (2) Sand culture mini-swards were used for screening rhizosphere decomposition of organic matter, winter persistency and net productivity in relation nitrate buffering and C-sequestration. (3) Horizontal sand-bed lysimeters were developed for assessment of nitrate buffering/interception efficiencies and aspects of plant water relations. (4). Field plots were established with the intention of performing sward-scale assessments of traits associated with C sequestration and infiltration rate, and of providing a unique longer term experimental resource for further trait analysis within the amenity x forage mapping family.

The results revealed promising variation (> two-fold across the mapping population) in the majority of the traits measured. However, it was apparent that some traits are far more difficult to screen for than others in terms of time-scale and/or technical/experimental resources required (i.e. C sequestration). QTL were identified and mapped onto a pair of outline AFLP molecular marker-based linkage maps, constructed during the project, for a total of 43 traits. Notable amongst these, under Objective 1, heavy-metal specific QTLs were identified for tolerance (in terms of growth) to Fe (linkage group 1), Zn (linkage group 4) and Pb (linkage group 4). Under Objective 2, heavy-metal specific QTLs were identified for plant content of Fe

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(linkage group 1) and Pb (linkage group 5), together with a range of traits associated with the accumulation and partitioning of Fe, Zn and Pb between roots and shoots. Under Objective 3, an extensive QTL region for stomatal conductance was identified on linkage group 1, partially coinciding with QTLs for transpiration rate per unit leaf area, but distinct from QTLs for sward transpiration rate expressed on a ground area basis (linkage groups 4, 6 & 7). Under Objective 6, extensive QTL regions were identified on linkage group 1 for nitrate interception by mini-swards, specific to steady-state conditions of nitrate inflow. However, a specific QTL for nitrate interception under ‘pulsed’ (i.e. episodic) nitrate supplies was detected on linkage group 5. A non-specific QTL for net decomposition of added organic matter in the rhizosphere (Objective 7) was identified on linkage group 1 (@ 14.4 cM), together with specific (linkage group 2) and non-specific (linkage group 5 ) QTLs for C:N ratios of organic matter residues. A specific QTL for the C return in litter (Objective 8) was detected on linkage group 5 and a very strong non-specific QTL region for this trait (LODs 6.6-10.4) was also detected on linkage group 1, coinciding with a number of growth-related QTLs.

Based on the number and significance of the QTLs detected, it should be technically possible to embark on selection programmes for most of the traits associated with the provision of ‘ecosystem services’ covered by this project. Progress is, arguably, likely to be most rapid with respect to (a) nitrate interception efficiency and (b) heavy metal tolerance and accumulation (i.e. for bioremediation applications), the latter also being highly relevant to the global problems of micronutrient deficiencies in cereal crops destined for human consumption. More detailed and robust assessment of traits associated with soil microbial activity and profile C sequestration is required before confident statements can be made regarding the feasibility of incorporating these traits into selective breeding programmes.

In conclusion, although this project should be viewed a preliminary survey of a very wide territory, the results have highlighted the opportunities for, and the feasibility of, exploiting genetic variation in forage grasses for enhancing environmental quality through the provision of an improved range of ‘ecosystem services’ and the viability of using a marker-assisted selection procedure to achieve these.

Project Report to Defra8. 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).

Scientific objectivesObjective 1. Identify QTLs for 'physiological' tolerance to Zn, Pb and Fe.Objective 2. Identify QTLs for hyper-accumulation of Zn, Pb and Fe.Objective 3. Identify QTLs for leaf water conductance.Objective 4. Identify QTLs for rainfall infiltration rates.Objective 5. Identify QTLs for 'sink-capacity' for NOx.Objective 6. Identify QTLs for 'winter buffering efficiency' for soil nitrate.Objective 7. Identify QTLs for soil microbial activity and functional biodiversity. Objective 8. Identify QTLs for net C-sequestration in the soil profileObjective 9. Evaluation and prioritisation of Enhanced Environmental Quality functions for subsequent incorporation into marker assisted selection programmes

IntroductionBackground to problem The project addressed the problem of finding new ways of exploiting the genetic potential of forage grasses to enhance the environmental sustainability of grassland-based enterprises by means other than optimising forage

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quality and resource-use efficiency. Specifically, it aimed to pave the way for development of varieties and ecotypes with functional 'added environmental value', by identifying and genetically mapping traits associated with ‘ecosystem services’ and/or environmental quality that could be incorporated in future precision breeding programmes, utilizing marker assisted selection procedures. The development of such varieties would promote multi-functional patterns of grassland management in which forage production is combined with, and/or replaced by provision of enhanced 'ecosystem services’. In turn, this will assist implementation of CAP and WTO-driven reforms, based on the decoupling of support measures from production and their replacement by agri-environment and wider rural development measures.

R&D underpinning the genetic improvement of grasses for UK agriculture has until very recently focussed entirely on improving agronomic performance and resource use efficiency. Selection for environmentally important objectives such as bioremediation, enhanced biodiversity and C-sequestration has not been regarded as a priority. Furthermore, in many cases the traits associated with ‘ecosystem services’ or promoting environmental quality have not been identified or characterised, let alone incorporated into modern commercial varieties, unless serendipitously. Consequently, farmers do not currently have the option of using varieties combining both high forage quality and yields with high environmental benefit. Combining these attributes in new varieties would have immediate application in programmes of environmentally responsible management.

The project’s focus on perennial ryegrass (Lolium perenne L.) was justified on the grounds of (a) available genetic information, (b) its pre-eminent economic position in UK grassland production systems, (c) the perception in some quarters that it is not currently 'environmentally friendly' and (d) the established ‘pipeline’ for variety development.

Defra support was justified on the grounds that the objective of facilitating the subsequent development of environmentally friendly varieties for use by farmers and other land managers constitutes an 'enabling means' in a wide range of policy objectives outlined in Defra’s 'The Strategy for Sustainable Farming and Food' (Defra, 2002) specifically:-

As a measure to aid farm diversification (i.e. grassland systems for recovery of waste applications). As a measure to enhance the environment and adding environmental value to enterprises. As a measure to provide new options within ‘the single farm payment scheme’ and broadly based agri-

environment schemes that reward management practises that go beyond current regulations and market demands.'

As a measure to mitigate agriculture's contribution to climate change. As a measure to 'aid rural communities' by diversification within farming and environmentally friendly

farming.

Research approachThe research approach was based on characterising the genetic variation in target traits in an existing perennial ryegrass mapping family, at a range of scales from single plant to sward, and to identify Quantitative Trait Loci (QTLs) based on molecular markers produced by Amplified fragment length polymorphism (AFLP) analysis. The project ‘speculatively’ targeted traits associated with bioremediation of heavy metals and other pollutants, 'buffer zone' efficiency for nitrate interception, C-sequestration, functional soil microbial biodiversity and flood mitigation, none of which have been considered in the selective breeding of forage grasses before. The decision to address a wide range of traits, rather than concentrating on those associated with a single aspect of environmental quality, was justified on the grounds that little or no information is available to indicate the viability or otherwise of genetic improvement as a means of improving environmental quality in any of these areas. Hence, the project aimed to provide an initial evaluation of the feasibility of improvement and hence prioritise traits for further work.

Experimental platformsTrait assessment, the main activity throughout the project, was conducted on four experimental platforms (Fig 1), three of which were developed during the project’s life-time, to promote cross-referencing at a range of scales from the single plant to the field-based sward. (1) IGER’s flowing solution culture system was used primarily at the single plant level to characterise heavy metal tolerance and accumulation (Objectives 1& 2). (2) Sand culture mini-swards were used for screening rhizosphere decomposition of organic matter (Objective 7), winter persistency and net productivity in relation nitrate buffering (Objective 6) and C-sequestration (Objective 8). (3) Horizontal sand-bed lysimeters were developed for assessment of nitrate buffering/interception efficiencies (Objective 6) and transpiration (Objective 4). (4). Field plots were established with the intention of performing sward-scale assessments of traits associated with C sequestration (Objective 8) and infiltration rate (Objective 4), and of providing a unique longer term experimental resource for further trait analysis within the amenity x forage mapping family.

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Fig. 1. Experimental platforms used for trait assessments during the project: Clockwise from top left: (A) Flowing solution culture system, (B) Sandbox mini-swards, (C) Horizontal sand-bed lysimeters and (D) Clonal 1m2 field plots.

Materials and methodology Plant materialPhenotypic characterisation and mapping of candidate traits was conducted throughout the project using IGER’s amenity x forage type Lolium perenne mapping family, in order to maximise the potential for cross referencing between studies conducted on the four experimental platforms used in the project. The main advantage of this mapping family over others available within IGER stemmed from the wide range of growth and morphological types exhibited: it was anticipated that morphological attributes may be significant determinants of several of the processes considered in the project. However, to broaden the genetic base, particularly with respect to heavy metal tolerance, a limited number of wild ecotypes of Lolium perenne were collected as part of this project from several sites in Ceredigion known to be contaminated with heavy metals as a result of former mining activities. Amenity x forage mapping family:A back-cross mapping family was derived from an initial cross between contrasting amenity-type and forage-type genotypes of Lolium perenne, followed by backcrossing of a single F1 genotype to the amenity type parent, by Dr D Thorogood at IGER. In total, 198 progeny genotypes were grown on in potting compost and maintained indefinitely as ‘primary mother plants’ in an unheated greenhouse. This family offered a very wide range of growth and morphological phenotypes, reflecting the diversity of the parents. The amenity-type parent was selected from the cultivar, AberImp, characterised by extremely high shoot density, small leaves, and a slow relative growth rate. The forage-type parent was selected from a wild ecotype, accession number Ba12142, characterised by low tiller number, large, broad leaves and a high relative growth rate. A random sample of 94 progeny genotypes, together with the two parental genotypes, was selected for evaluation in the current project from amongst the 198 ‘primary mother plant’ genotypes. The number of genotypes studied was limited by the capacity of IGER’s flowing solution culture (FSC) system, given the desirability of avoiding ‘batch screening’ of traits due to the associated environmental variation introduced (Rauh et al., 2002). Multiple tillers were taken from each of the genotypes to provide duplicate sets of ‘project mother plants’: one set was maintained in 9 inch pots containing potting compost (John Innes No. 3) in a cold greenhouse over the project’s lifetime and the second set maintained in culture units belonging to IGER’s flowing solution culture (FSC) system described below.

Collection of heavy metal tolerant ecotypes:Traits conferring 'physiological tolerance' to and hyper-accumulation of heavy metals have not been well characterised although inter-specific differences in 'constitutive tolerance' have been demonstrated in some cases. Phenotypic variation can be assessed and mapped in terms of Tolerance Index (fitness in presence of metal / fitness in absence of metal) and various metal efficiency indices. However low gene frequencies for 'tolerance' in normal populations, not subjected to selection pressures, mean that existing mapping families may not contain the genes of interest and additional mapping families may need to be constructed from adapted ecotypes. For this reason ecotypes of Lolium perenne L. were collected from several sites in Ceredigion known to be contaminated with heavy metals as a result of former mining activities. Source information was obtained from the Dyfed Wildlife Trust Mid-Wales Metal Mine Vegetation Survey conducted in 1992/1993. Of 34 abandoned mine sites described, seven included Lolium perenne growing on or nearby the contaminated spoil tips.

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Landowners were traced for five sites ((1) Castell, (2) Clara mine, (3) Nant yr Arian, (4) Bwlch, (5) North Cwmsymlog) and permission was obtained for field work and collections to be made from the associated revegetated tailings. Other species (e.g. Dechampsia spp and various Fescues) were also collected to broaden the genetic variation in heavy metal tolerance and accumulation available to the project. The ecotypes were subsequently multiplied up by IGER’s Genetic Resources Unit.

Experimental Programme(A) Heavy metal tolerance in flowing solution culture:Experiment 1:23:51 Characterisation of mapping family under optimal conditions of macro- and micro-element nutrition. Experiment 1:23:59 Trial to identify concentration range of Fe in flowing nutrient solution eliciting toxicity symptoms in selected genotypes.Experiment 1:23:60 Characterisation of mapping family under conditions of supra-optimal Fe supply.Experiment 1:23:62 Trial to identify concentration range of Zn in flowing nutrient solution eliciting toxicity symptoms in selected genotypes.Experiment 1:23:64 Characterisation of mapping family under conditions of supra-optimal Zn supply.Experiment 1:23:65 Trial to identify concentration range of Pb in flowing nutrient solution eliciting toxicity symptoms in selected genotypes.Experiment 1:23:66 Characterisation of mapping family under conditions of supra-optimal Pb supply.(B) Organic matter decomposition and plant productivity in sand-box mini-swards:Experiment 1:23:53 (A) Characterisation of rhizosphere organic matter decomposition across the mapping family using a litter bag technique.Experiment 1:23:53 (B) Productivity under repeated cutting and nitrogen recovery.Experiment 1:23:53(C) Characterisation of net C deposition in litter across the mapping family. (C) Nitrate interception efficiency in horizontal sand-bed lysimeters:Experiment 1:23:69. Comparative variation in nitrate interception as affected by cutting and environmental conditions.(D) Plant water relations in flowing solution culture and horizontal sand-bed lysimeters:Experiments 1:23:64 and 1:23:69. Transpiration rate in flowing solution culture.Experiment 1:23:69 transpiration rates and stomatal conductance in horizontal sand bed lysimeters(E) Characterisation in field plots:Experiment 1:23:56 Establishment and appraisal of mapping family under field conditions.(F) Molecular characterisation and map construction

Methodology

(A) Screening for heavy metal tolerance in flowing solution culture:The UK and global markets for bioremediation are expanding rapidly and there is an increasing demand for novel and sustainable remediation technologies. Phytoremediatory approaches have the potential to play an increasing role particularly in reclamation of brown field sites, amelioration of 'sludge' and waste applications to land and soil and air pollution mitigation. The genetic control of tolerance is complex (Macnair, 1993) and there have been very few, if any, attempts to selectively breed specialised varieties. As part of this project it was intended to identify QTLs in Lolium perenne for 'physiological' tolerance to Zn, Pb and Fe. A series of screening experiments (1:23:51, 1:23:60, 1:23:64, 1:23:66) were performed with the 94 genotypes selected from the amenity x forage Lolium perenne mapping family, as described above, together with the two parental genotypes, in a system of flowing solution culture housed in an air conditioned greenhouse, incorporating automatic control of concentrations of NO3

-, NH4+, K+ and H+

in solution (Clement et al., 1974; Hatch et al., 1986). The chronology common to all four experiments consisted of an establishment period of 40 days followed by a screening period of 28 days (14 days in Expt 1:23:51).

Additional screens were performed with selected ecotypes from amongst those collected from contaminated mine tailings. These formed part of two M.Sc Theses (University of Wales, Aberystwyth) assessing tolerance and hyper-accumulation of Cu, Pb and Zn comparatively with selected genotypes from the mapping family, grown in mixtures of contaminated mine-spoil and sand.

Preliminary trials: In the absence of unequivocal evidence from the literature regarding critical concentrations of heavy metal ions in flowing solution culture eliciting toxicity in Lolium perenne (e.g. Qu et al., 2003), a series of preliminary trials were conducted to determine appropriate supra-optimal concentrations of Fe (Expt 1:23:59), Zn ( Expt 1:23:62) and Pb (Expt 1:23:65) for the main screening experiments. In brief, these trials compared the growth and metal tolerance of two contrasting genotypes (with respect to growth rate under optimal conditions) and four ‘adapted’ ecotypes of perennial ryegrass collected from mine tailings. Plants were grown in flowing solution culture using customised ‘mini-culture units’ (Soussana et al, 2002), and exposed to three or four different concentrations of the metal in question over 43 days prior to harvesting. Initial concentrations were as follows: Expt 1:23:59:- 10.8, 54 and 540 μM fe; Expt 1:23:62:- zero, 0.15, 1.5 and 15.3 μM Zn; Expt 1:23:65:- zero, 10, 100 μM Pb.

Main screen plant establishment and culture:

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For each of the main screening experiments, 12 tillers, visually uniform in size, were removed from each of the 94 progeny and two parental genotypes constituting the set of ‘project mother plants’ maintained in flowing solution culture, trimmed to a standard shoot length of 10cm and root length of 2 cm, then divided into two similar groups of 6 tillers on the basis of fresh weight. Each tiller group was transplanted into one of 24 culture vessels within each of the 8 plant culture units containing 200 dm3 of re-circulating nutrient solution. The design of the culture vessels enabled measurement of shoot attributes on individual plants, but root measurement per vessel (i.e. bulked across the six plants) because of the entanglement of the individual plant root systems within a given culture vessel.

The eight plant culture units were treated as two replicate blocks of four units, each block containing one culture vessel (i.e. six plants) of each genotype. The grouping of genotypes within each culture unit was common across the two blocks, although the position of each genotype within a given culture unit was random. The plants were grown on for 40 days prior to a screening period lasting 28 days.

The initial composition of the nutrient solution in each culture unit was (μM): NO3-, 250; K+, 250; Ca2+, 344;

SO42-, 424; Mg2+, 100; H2PO4

-, 50; Fe2+, 5.4, with appropriate micronutrients (Clement et al.,1978a), and solution pH 6.0 ±0.5. All culture units were drained and refilled on day 35 of the establishment period with 300 dm3 of nutrient solution of the same initial composition except for NO3

- (50 μM ) and Ca2+, (344 μM ). Natural light was supplemented by a single 400W HPI-T lamp (Philips) suspended 1.5 m above the surface of each culture unit from day 10 onwards, producing 250 ± 50 μmol m-2 s-1 PAR at top of plant canopy over a 12 h photoperiod (0600 – 1800 h). From day 34 onwards, light was supplied solely by a 400 W HPI-T and 400 W SON-T (Philips) lamp suspended 1.5 m above the surface of each culture unit, producing 550 ± 50 μmol m-2 s-1 PAR at top of plant canopy. Air temperature was 20/15oC (±2oC) day/night and solution temperature was 18-19oC throughout the entire experiment.

Nutritional control during the screening period:From day 40, nutrient concentrations were controlled automatically with reference to the NO3

- concentration in each culture unit. This was measured every 28 minutes (Orion Nitrate Electrode Mod. 93-07, Boston, USA) and a ‘set-point’ concentration of 50 ±5 μM NO3

- maintained by automatic addition of Ca(NO3)2, stock solution (containing 15 mgN/g) together with all other nutrients, barring the heavy metal under test, supplied in proportion. Solution pH 6.0 ±0.1 was maintained by automatic titration of Ca(OH)2/H2SO4. Net uptake of NO3

- per culture unit (i.e. 24 genotypes) was given on a daily basis by the amount of NO3

- required to maintain the set-point concentration. Experiment-specific conditions were as follows:-Experiment 1:23:51(optimal nutrition): The set point concentration of 50 ±5 μM NO3

- in all culture units was maintained throughout the screening period by supplying Ca(15NO3)2 (1.00 Atom% 15N), to enable calculation of NO3

- uptake over the 28 days by each genotype. Samples of solution were taken regularly for the analysis of NO3- by

automated colorimetry (Henriksen and Selmer-Olsen, 1970) as a check. Experiment 1:23:60 (Fe toxicity):- Four culture units (i.e. one culture vessel containing 6 plants of each of the 96 genotypes) received a ‘high Fe’ treatment as 100 μM Fe EDDHA added at the start of the screening period. The remaining four culture units were designated as ‘controls’ and received an initial 5.4 μM FeSO4. Thereafter, additional Fe was supplied continuously to both ‘high’ Fe and ‘control’ Fe units as FeEDDHA solution (containing 45.4 mg Fe dm-3 ) in a ratio of 1:1 by weight with Ca(NO3)2 stock solution (containing 15 mg NO3-N /g) automatically supplied to maintain the ‘set point’ concentration of 50 ±5 μM NO3

-. Hence, Fe was supplied to culture units according to the aggregate plant demand for NO3

- within the unit. Analysis of [Fe] in culture solutions on days 7 and 14 by inductively coupled plasma atomic emission spectrophotometry (Varian Liberty ICP-AES), gave means of 98.4 μM (d7) and 96.7 μM (d14) across the four ‘high’ Fe units compared with 0.3 μM (d7) and 0.7 μM (d14) across the ‘control’ units.Experiment 1:23: 64 (Zn toxicity):- Four culture units received a ‘high Zn’ treatment as 100 μM Zn (ZnSO4 7H2O) at the start of the screening period. The remaining four units were designated ‘controls’ and received an initial 0.076 μM Zn. Thereafter, additional Zn was supplied to both ‘high’ Zn and ‘control’ culture units as a component of a standard ‘complete’ nutrient stock-solution containing, amongst other nutrients, 15 mg NO3-N/g and 15 μg Zn /g. This stock solution was supplied automatically to maintain the ‘set point’ concentration of 50 ±5 μM NO3

-. Hence, Zn was supplied according to the aggregate plant demand for NO3

- within the unit. Analysis of [Zn] in culture solutions on day 21 by ICP-AES gave a mean of 76.6 μM Zn across the four ‘high’Zn units compared with 0.07 μM Zn across the ‘control’ units. Unlike the others, this experiment was conducted under natural light during April and May. Experiment 1:23:66(Pb toxicity):- Four culture units received a ‘high’ Pb treatment in the form of 25 μM Pb (Pb(NO3)2) at the start of the screening period, equivalent to a total addition of 1.554 g Pb per culture unit. The remaining four units were designated ‘controls’ and contained zero Pb throughout the experiment . No further Pb was added to the ‘high’ Pb units until day 15 when 1.037 g Pb (as Pb(NO3)2) was added to the 200 dm3 of culture solution remaining in each unit, equivalent to a 25 μM increment in the concentration of Pb. Analysis of [Pb] in culture solutions on day 27 by ICP-AES gave a mean of 0.58 μM Pb across the four ‘high’Pb units compared with 0.0074 μM Pb across the ‘control’ units. This suggests that significant precipitation of added Pb occurred, a view supported by the observation of a cloudy white precipitate dispersing from the surface of the roots of plants under the ‘high’ Pb treatment when agitated in the nutrient solutions.

Plant harvests and analyses:Total plant fresh weights per culture vessel (i.e. bulked for six plants) were recorded non-destructively on days 0, 7, 14, 21 and 28 of the screen, for calculation of fresh weight relative growth rates. Leaf extension rates (Expt 1:23:51 only) were assessed on day 7, when five expanding leaves of plants in each culture vessel (i.e. two

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vessels per genotype) were marked at the junction with the ligule with acrylic red paint. Forty eight hours later the distance ‘travelled’ from the ligule by the marker was measured with a ruler.

All plants were harvested on day 28 (day 14 for Expt 1:23:51) and separated into shoot and root fractions (per vessel). Tiller numbers, fresh weights and total leaf area (Licor Mod. 3100 Area Meter) were recorded. All fractions were freeze-dried prior to reweighing and milling (< 0.5mm mesh, Glencreston Mod. DFH48). All plant fractions from Expt 1:23;51 were analysed for total N and 15N by continuous flow mass spectroscopy (Twenty-twenty, Europa Scientific Ltd, Crewe, UK) linked to a C/N analyser (Roboprep CN, Europa Scientific Ltd, Crewe, UK), and net uptake of NO3

- by each genotype over the 14 day screen calculated according to Wilkins et al. (1997). Total Fe, Zn and Pb in plant fractions from the relevant experiments were determined by standard ICP-AES procedures in IGER’s Analytical Chemistry Section, with results expressed on a dry weight basis. The statistical distributions of trait data were tested for normality by quantile plots and histograms of residuals (Genstat ).

(B) Screening in sand-box mini-swards:Experiment 1:23:53(A): Plant residue decomposition in the rhizosphere using a litter bag technique.Mini swards of the 94 progeny genotypes selected for screening, together with the two parental genotypes, were established during 2004 to enable trait assessment at the sward level. Litter bags provide a convenient and proven method for measuring litter decomposition, and hence rhizosphere microbial activity, in terrestrial ecosystems (Wieder and Lang, 1982). Although they may underestimate actual decomposition, the results reflect trends characteristic of unconfined litter, as residue confinement creates an environment that does not deviate substantially from the natural environment (Wieder & Lang, 1982). Given the importance of physicochemical characteristics in determining tissue life-span (Ryser, 1996) and that plant material with large C:N dry weight ratios tend to decompose more slowly than those with low C:N ratios (Brady, 1974), it was decided to screen the mapping population for decomposition of two types of residue: perennial ryegrass (C:N = 18) and barley straw (C:N = 73).

Mini-sward establishment:200 dark blue polypropylene rectangular storage containers (36 cm length x 25 cm width x 15 cm height to internal horizontal line at base of handles) were lined with a woven black plastic sheeting allowing free drainage, after drilling 12 x 9 mm diam. drainage holes in the base. Each container was filled with 17.5 kg of air dried, course washed ‘Bunker’ sand (air dry bulk density = 1.45 g/ cm3, water saturated bulk density = 1.786 g/ cm3, saturated water filled volume fraction = 0.34), with a total water holding capacity at field capacity of 4.1 litres. At the time of filling, a polymer-coated slow release fertiliser (Pursell, Polyon 18-6-12 + Trace element mix; 6 months fully controlled release) was incorporated as a layer at 10 cm depth into the sand, at a rate of 200 kg N/ha. Each container received 2 x 5dm3 tap water washings ten days prior to sowing up (March 2004) with 20 vegetative tillers taken from the mother plants maintained in flowing solution culture and trimmed to 7cm shoot length. A soluble fertiliser dressing (Phostrogen 14-10-27 plus trace elements) was applied to the surface at a rate of 100 kg N/ha followed by 2 dm3 of tap water. Two mini-swards per genotype were prepared together with spare swards for each of genotypes 63 and 192, ‘bare sand’ +/- fertiliser ‘controls.’ Sward establishment was encouraged by repeated splitting of tillers and infilling. The mini-swards were transferred to an outside standing area in May 2004 and arranged in replicate blocks with an appropriate fertiliser, irrigation and cutting regime throughout 2004 to promote high sward density. Following establishment of closed canopies the sward area per box was 900 cm 2. Each sward was classified visually either as amenity, forage or amenity x forage type on the basis of canopy morphology and growth habit. Measurements were made throughout the period July 2004- July 2007.

Litter bag design:Litter bags were constructed from Stomacher lab system circulator 400 filter bags (Ba6141/STR filter bags, Seward Ltd, UK). Material was cut to shape then heat sealed on two sides to give rectangular bags of approximately 60 mm x 26 mm. Each bags were filled with between 0.45 - 0.55 g of the appropriate oven dried (80oC) plant residue, weighed to 3 decimal places, then closed with nylon thread leaving a 10-15 cm length to which a coloured marker bead was attached to enable recovery off the bag after burial.

Two types of plant residues were used in the litter bags: (1) perennial ryegrass and (2) barley straw. The perennial ryegrass consisted of a 1 kg bulk sample (size fraction 1-2 mm) of oven-dried (80oC) leaf, stem and flowering heads from the 96 mapping family genotypes used in the project. It was obtained from clippings collected during a routine maintenance cut of the mapping family field plots (1m2) in Cae Penryn at IGER. After drying, the sample was ground (Glencreston Mill) and passed through a 2mm sieve but was retained by a 1 mm. The barley straw consisted of a 1 kg bulk sample of baled straw (size fraction 1-2 mm), oven dried, ground and sieved as for the ryegrass. A total of 600 ryegrass and 1200 barley straw litter bags were made.

Screen design:The mini-swards were arranged into two adjacent blocks (A & B) each containing one sward of each of the 94 mapping family genotypes, the two parental genotypes and four ‘sand-only’ controls. Two decomposition experiments were performed during the project, referred to hereafter as ‘Run 1’ and ‘Run 2’. Weight loss was only recorded at the end of the experiments. Hence decomposition rates per se (i.e. rate constants assuming simple exponential decay models could not be calculated). However, the approach provided a ‘snap shot’ of variation in the cumulative decomposition across the mapping family.

SID 5 (Rev. 3/06) Page 9 of 29

In Run 1, mini-swards in Block A received perennial ryegrass litter bags and those in Block B received barley straw bags. In each case, five replicate litter bags were inserted on 09/08/05 into the rhizosphere beneath each mini-sward, by removing a sward/sand plug with a 15mm cork borer to a depth of 10 cm, inserting the litter bag then replacing the plug and tamping it down. The position of the litter bag was marked by the coloured bead attached by the bag’s nylon thread. Further litter bags of both residue types were inserted into spare mini-swards of genotypes Nos. 63 and 192 to enable the progress of decomposition over time to be gauged without compromising the experiment. Surface and profile temperatures at 10 cm depth were monitored using a Squirrel data logger. Swards were subjected to intermittent irrigation in addition to rainfall to prevent them drying out, with volumes recorded by three rain gauges positioned across the standing area. Litter bags remained in situ for 21 days in Block A (ryegrass bags) and 48 days in Block B (barley straw), after which they were removed intact from the profile, oven dried at 80oC overnight, then brushed clean of sand and any attached root material. Final dry weights were recorded and absolute loss of dry weight and % loss of the initial dry weight calculated. The contents of the five replicate bags per mini-sward were then combined, ground (<0.5mm) prior to analysis of total N and total C by stable isotope mass spectroscopy as described above.Run 2, designed to assess decomposition over a longer period under winter conditions, was confined to swards in Block B, each of which received five barley straw bags on 15/12/05. The protocol was identical to Run 1, but bags were left in situ for 131 days. Experiment 1:23:53 (B) Productivity under repeated cutting.Based on the assumption that variation in net above ground productivity will to some extent reflect variation in net C capture and hence C sequestration, the sand-based mini-swards of the 94 mapping family genotypes, plus parents were screened for herbage yield under repeated cutting over an 15 month period between July 2004 and September 2005. following establishment (2005-2006).

The two replicate blocks of mapping family mini-swards, established as described under Expt 1:23:53(A), were cut to a height of 3 cm above sand level on six occasions (13/07/04, 15/09/04, 5/05/05, 15/06/05, 20/07/05, 30/09/05). Herbage fresh weights were recorded prior to oven drying at 80oC, reweighing and grinding for total N analysis as described for Expt 1:23:53(A).

Experiment 1:23:53(C) Net C deposition in accumulated litter. As an adjunct to Expt 1:23:53(B), a further herbage cut was taken from all the sand-based mini-swards on 6/07/06. Additionally, all litter/thatch and dead plants (including root systems) were removed. Both fractions were oven dried, weighed and analysed for total N and C as described for Expt 1:23:53(A).

(C) Nitrate interception in horizontal sand-bed lysimeters:Experiment 1:23:69. Nitrate interception efficiencies as affected by cutting and environmental factors.The use of grass buffering strips within and around arable cropping areas to reduce nutrient losses (i.e. N and P) to adjacent water courses is well established (e.g. Scholefield D et al, 1998; Fiener and Auerswald, 2003). However, there has been no attempt to increase the interception efficiency of these strips through genetic improvement. The objectives of this study were to evaluate variation in interception efficiency for nitrate across the project’s mapping family, with a view to identifying QTLs with potential application in subsequent genetic improvement programmes. The study focussed on the interception of nitrate during horizontal flow through the rooting zone, as opposed to surface run off. In order to simulate real conditions (i.e. horizontal solute flow through an area of sward), a shallow gradient sand-bed lysimetry system was designed and constructed providing for the simultaneous phenotyping of 80 genotypes, grown as mini-swards in 1m lengths of plastic guttering. This was interfaced with the automatic nutrient control provided by IGER’s flowing solution culture (FSC) system, enabling nitrate interception efficiencies to be measured under both steady-state and variable (i.e. pulse) inputs of nitrate. In view of the ‘demand driven’ characteristics of nitrate uptake, the study focussed on the impact of light intensity and cutting on interception efficiencies.

Construction of sand-bed lysimeters:A rectangular support frame (5.5m length x 2m width x 1.15m height) was constructed in IGER’s FSC air conditioned greenhouse from tubular steel to a herring-bone design, accommodating 40 x 1m lengths of plastic guttering (White PVC square guttering: 5.7 cm deep, 12 cm wide at top, 7cm wide at bottom) containing plants. Each gutter was filled with 4.75 kg of air-dried washed ‘bunker sand’ (holding 1360 cm3 of water at saturation). A single drainage hole was drilled at each end of the gutter, centred 16 mm above the base through which a 60 mm length of polyethylene tubing (ID 9mm) was inserted, the internal end of this tube fitted with a filter (20 x 20 mm single layer of Seward Stomacher 400 circulator filter bags), sleeved onto the drainage tubes with a 1 cm length collar of 11mm ID translucent PVC tubing (Portex) to prevent loss of sand in drainage. Both drainage tubes extended 45 mm external to the gutter to facilitate manual collection of outflow, although during operation one of the tubes was closed with a bung. The provision for drainage from either end of the gutter enabled their orientation on the support frame to be reversed periodically to minimise the variation in plant growth due to nutrient gradients. A double layer of spherical black alkathene beads (diam. 2-3 mm) was applied to the surface (600 g per gutter) to inhibit algal growth

The gutters (labelled respectively 1-40 and 41-80, were arranged perpendicular to a central conduit gutter supplying nutrient solution to one end of each gutter by gravity (constant head), via a 60mm length of plastic

SID 5 (Rev. 3/06) Page 10 of 29

tubing (ELKAY autoanalyser PVC tube) delivering at rates of 2-10 ml/minute depending on the I.D. of the selected tube. Drainage outflow (gradient 3%) from each gutter returned to a bulk nutrient tank containing 300 dm 3 of nutrient solution via a conduit gutter, as was the overflow from the main supply conduit. The composition of the nutrient solution in the bulk tank was controlled automatically by IGER’s FSC system. Pulse trials with sand-filled gutters indicated solute flow, determined by EC measurements under saturated conditions, to approximate ‘piston flow, with a transfer time of 4.5 hrs depending on the diameter of the inflow tubes used.’

Plant establishment:Seventy-eight mapping family genotypes were selected from the 94 genotypes available, together with the two parents. The 16 genotypes omitted were the least persistent and/or of lowest productivity in the project’s sand-box mini-sward experiments. A single gutter was established per genotype. In each case, 30 clonal tillers were removed from mother plants in FSC on 30/01/06, shoots trimmed to 10 cm and roots to 4 cm, then planted in two rows down the length of the tap-water saturated, sand-filled gutter. Gutters were placed on the support frame and subjected to a management regime to promote full canopy establishment (0.115 m2 per gutter) over a five month period, including regular in situ subdivision of tillers and infilling of gaps. Nutrients were supplied by flushing through with recirculating nutrient solution on a cycle of one day ‘on’ and three days ‘off’, using a ‘double’ strength standard ryegrass FSC nutrient solution (Clement et al., 1978) containing 500 µM NO3

-. Solution pH was manually adjusted on a weekly basis from approx pH 7.4 to approx pH 6.0 by the addition of 0.5M Sulphuric acid. Nutrient depletion in the recirculating solution was assessed regularly for NO3

- using ‘Nitrate-test strips’ (Merckoquant 1.10020 Nitrat-test) and nutrients added to the bulk nutrient tank as appropriate.

Screen design: Nitrate interception efficiency was assessed in a repeated measures approach on 23 occasions (Runs 1-23) over a 6 month period. In each case a constant concentration of 500 µM NO3

- was maintained in the nutrient solution entering the mini-sward lysimeters. Other nutrients supplied at concentrations given by Clement et al. (1978). Sward uptake of nitrate was calculated from the difference between the nitrate flux entering and leaving the gutters, such that:- Nitrate flux out of gutter (FO) = Nitrate flux into Gutter (FI) – Nitrate flux into the plants (FP). Nitrate fluxes were expressed in units of micromoles NO3

-/minute/gutter and were calculated as the product of nitrate concentration (µM) in the inflow (or outflow) solution and the inflow (or outflow) rate (ml H2O per minute) of solution, measured for each of the gutters. The sampling procedure, common to all Runs, consisted of sequentially collecting outflow solution from each gutter (nos 1-80) in 10 ml polystyrene vials and measuring the outflow rate. The procedure took one hour and was performed between 1400-1500 hrs, corresponding with the maximum point in the diurnal cycle of nitrate uptake. Inflow solution (common to all gutters) was sampled from the supply conduit at the start, middle and end of the sampling period. A ‘control’ gutter without any plants was included. All samples were frozen prior to analysis of NO3

- by automated colorimetry (Henriksen and Selmer-Olsen, 1970).

Runs 1-11 were conducted under ‘pulse’ conditions with respect to prior N nutrition, whilst Runs 12-23 were conducted under ‘steady-state’ conditions. ‘Pulsed’ runs were designed to simulate an episodic supply of nitrate in the soil and swards were allowed to deplete the concentration of nitrate in the nutrient solution to zero over a period of 12 hrs prior to 0900 hrs on the run day, at which point nitrate was added to give 500 µM NO3

-. In contrast, ‘steady state’ runs were conducted against a background of a constant 500 µM NO3

- at pH 6.0 maintained automatically by IGER’s FSC system. All swards were cut back to a height of 6cm on four occasions during the experiment and most runs were conducted under natural light conditions (Table 1). Air temperature was controlled at 20/15oC day/night and the gutter surface temperature was 20 ± 2 oC unless stated. Transpiration rates per gutter were measured by weight loss on five occasions, to provide correction factors for use in the flux calculations. Table 1. Environmental conditions during nitrate interception runs 1-23. Runs performed under natural light unless stated. Supplementary lighting provided by 400W Philips HPT/1 Mercury halide lamps and 400 W SONT high pressure lamps (Philips) suspended 1m above the swards giving an additional PAR of 500 ± 50 µmol m-2 s-1 at canopy height. Inflow rates: high = 6-10 ml/min; low =, 6 ml/min. Swards cut to 6 cm height; Runs 1-6 performed before first cut. Run Prior N

NutritionWeather Days after

cutting swards

InflowRate

Additional information

1 Pulse Overcast n/a High2 Pulse Sunny n/a High3 Pulse Overcast n/a Low4 Pulse Overcast n/a High5 Pulse Sunny n/a High6 Pulse Sunny n/a High Transpiration7 Pulse Sunny 14 High Transpiration8 Pulse Sunny 25 Low9 Pulse Mixed 1 Low10 Pulse Overcast 6 Low

SID 5 (Rev. 3/06) Page 11 of 29

11 Pulse Overcast 29 High Transpiration 12 Steady-state Sunny 48 Low Transpiration13 Steady-state Mixed 49 Low Transpiration 14 Steady-state Mixed 50 High15 Steady-state Overcast 51 High16 Steady-state Sunny 7 High17 Steady-state Overcast 8 High18 Steady-state Overcast 15 Low19 Steady-state Overcast 16 Low Supplementary

lighting20 Steady-state Sunny 22 High Supplementary

lighting21 Steady-state Overcast 23 High Supplementary

lighting22 Steady-state Sunny 24 High Surface temp 12oC23 Steady-state Overcast 25 High Surface temp 12oC

(D) Plant water relationsExperiments 1:23:63, 1:23:64 & 1:23:69: Transpiration and stomatal conductancePrevious work at the single plant level has demonstrated the heritability of traits associated with plant water relations in Lolium perenne such as leaf water conductance (Gay, 1994). However, the impact of variation in physiological attributes of individual leaves on transpiration by swards may be attenuated as a result of scaling effects (Jarvis and McNaughton, 1986). Transpiration was targeted in this project, primarily because it is conveniently measured and also crucial in determining water use efficiency. In view of scaling effects, variation in rates across the project mapping family was assessed at both single plant and mini-sward scales.

MethodsTranspiration was measured at the single plant level in solution culture (Expts 1:23:63 & 1:23:64) and at the mini-sward level (Expt 1:23:69). In both cases a simple weight loss technique was used. Measurements in solution culture were confined to the 96 mapping family genotypes in ‘control’ treatments (i.e. cultured under optimal mineral nutrition). Expt 1:23:63, a mapping family screen for tolerance to Zn deficiency, was not formally part of the current project. However, the experimental design was identical to Expt 1:23:64 described above. In both experiments, a series of transpiration measurements were made by removing a single culture vessel per genotype (i.e. containing six plants) from the culture units and immersing the root system in a plastic beaker containing 1 dm3 of aerated nutrient solution of similar composition as the flowing solutions between 1000-1400 hrs. Net weight loss was measured after 4 h, corrected for evaporative loss from containers without plants, and attributed solely to transpiration (i.e. ignoring any increment in plant dry weight). Transpiration loss by the 80 genotypes in mini-swards (0.115 m2) established in 1m length gutters (Expt 1:23:69) was determined on five occasions (Table 1). On each occasion, the inflow of nutrient solution was terminated at 1000 hrs, gutters were weighed, replaced on the support frame and reweighed after two hours. The inflow of nutrient solution to gutters was subsequently restored. Net weight loss, corrected for evaporation from ‘control’ gutters without plants, was attributed to transpiration. In conjunction with the transpiration measurements associated with nitrate interception Run 12, stomatal conductance was measured (Delta-T AP4 Porometer: RH setting at 50%; Barometric Pressure from Aberporth Met station) on 7 fully expanded leaves per genotype.

(E) Field plots:Experiment 1:23:56: Establishment and appraisal of mapping family under field conditions. Replicated (x2) field plots (1m x 1m) of the 94 F1 genotypes and the two parents of the mapping family established during Spring 2005, were subject to a regular regime of cutting and fertilising during 2005 to promote dense and genetically uniform sward cover required for infiltration measurements (Objective 4). However, due to the lack of vigour and persistency of many genotypes over the winter of 2005/2006, severe problems were encountered with weed ingress, necessitating extensive renovation of plots, including hand-weeding and tiller infilling throughout the remaining duration of the project.

(F) Molecular characterisation of mapping family using AFLPsDNA extraction and AFLP analysis:Samples of youngest fully expanded leaf tissue (50 mg) were taken (5/2/04) from the 94 mapping family genotypes and parental genotypes (source: mother plants maintained IGER’s FSC system) for DNA extraction using a high throughput Qiagen kit (DNeasy96 plant kit). The DNA was quantified by spectrophotometry (GeneQuant Pharmacia Biotech) and quality checked by gel electrophoresis on a 96 well gel kit (Advanced Biotechnologies), prior to storage at -20C. Amplified fragment length polymorphism (AFLP) analysis was performed on an ABI 3100 genetic analyser using a standard in-house protocol by Kirsten Skøt (Plant Genetics and Breeding Department, IGER) adapted from Vos et al. (1995). Selective amplification of restriction fragments was conducted with 15 primer pairs (Table 2). Approximately 300 potentially usable markers were identified using

SID 5 (Rev. 3/06) Page 12 of 29

‘Genotyper’.The frequency distribution of marker numbers per genotype, classified according to parental presence or absence is shown in Fig .2.

Table 2. Mapping family AFLP markers identified for each primer pair. Values in parentheses are numbers falling within an arbitrarily imposed range of acceptable segregation ratios in the 94 F1 progeny (where X = number of F1 progeny with band). For markers present in only one parent the acceptable range was set as 25 < X < 75. For Markers present in both parents the acceptable range was X > 50, with no upper limit defined although markers present in 85-90 genotypes had been discarded at an earlier stage of analysis. Primer Pair Bands present in only

one parentBands present in both parents

ACA-CAA 24 (16) 12 (8)ACA-CAC 13 (13) 16 (13)ACA-CTA 11 (9) 8 (5)ACC-CAA 26 (24) 11 (8)ACC-CAC 12 (8) 7 (4)ACC-CCC 11 (10) 9 (6)ACC-CCT 16 (13) 12 (9)ACC-CTG 11 (11) 10 (9)ACG-CTA 10 (10) 3 (2)ACG-CTG 11 (9) 6 (5)ACT-CAA 26 (21) 9 (8)ACT-CAC 10 (7) 3 (2)ACT-CTA 15 (15) 10 (8)ACT-CTC 17 (14) 7 (5)ACT-CTG 17 (16) 10 (7)Totals 230 196 133 99

0

10

20

30

40

50

60

1-10 11-20 21-30 31-40 41-50 51-60 61-70 71-80 81-90 91-100

Nos genotypes

Nos

mar

kers

Markers present in one parent only Markers present in both parents Markers absent in both parents

Fig. 2. Frequency distribution for AFLP markers identified in 94 F1 progeny according to their presence/ absence in the two parental genotypes of the mapping family.

Genetic map construction:Data from all 94 of the progeny genotypes together with the parents were included. An outline map was produced using JoinMap Version 3.0, with markers grouped at a log of odds (LOD) value at a minimum of 7.0. Linkages between markers were assessed with a recombination fraction (REC) of < 0.4, and a LOD >1, these being the standard default settings for JoinMap 3.0. The software’s ‘Ripple command’ was used after each marker to test the order. Map distances were calculated using the Kosambi mapping function (Kosambi, 1944). Two workable AFLP-based outline maps (amenity alleles and forage alleles) both with seven linkage groups were produced. For both maps, interval mapping and Kruskal-Wallis nonparametric single-locus analysis were applied to all mapped and unmapped markers to assess associations between markers and traits, using MapQTL Version 4.0 (Van Ooijen et al., 2002).

Results and discusssion

SID 5 (Rev. 3/06) Page 13 of 29

Heavy metal tolerance and accumulationThe four screening experiments (Expts 1:23:51, 1:23:60, 1:23:64, 1:23:65) for physiological tolerance to supra-optimal/toxic concentrations of Fe (100 µM), Zn (100 µM) and Pb (25 µM), conducted in flowing solution culture with the 94 mapping family genotypes and parents, generated a very large amount of trait data and revealed a number of significant relationships between the variation in different physiological attributes across the family. metal accumulation and translocation to the shoots generally varied more than two-fold across the mapping family (e.g. Fig. 3A), with several genotypes exhibiting ‘extreme’ phenotypes. Tolerance to high metal concentrations, in terms plant growth response, differed significantly between metals. For example, there was little reduction in growth across the mapping family in the presence of 100 µM Fe (Fig.3B), but most genotypes showed diminished growth rates (circa 50%) in the presence of 100µM Zn (Fig. 4).

Fig. 3. Variation in (A) total plant content of Fe across 94 genotypes of the mapping family grown under ‘high’ or ‘control’ levels of Fe supply and (B) the relationship between shoot content of Fe and total plant dry weight.

0

2

4

6

8

10

12

0 2 4 6 8 10 12Plant d.wt under control Zn (g)

Plan

t d.w

t und

er to

xic

Zn (g

)

Fig. 4. Relationship between final total plant d.wt of 94 genotypes of the mapping family grown under ‘high’ or ‘control’ levels of Zn for 28 days.

According to Bonnet et al. (2000), hyperaccumulating species are able to tolerate up to 40 mg Zn /g DW in their shoots, whilst the normal concentration of Zn in plants growing on unpolluted soil ranges from 0.02 – 0.4 mg Zn /g d.wt. In their study with Lolium perenne grown at 50 mM Zn in conventional solution culture, plants only reached a shoot concentration of 17.3 mg Zn /g, hence were not classifiable as hyperaccumulators. However, other studies have revealed ryegrass to have a great capacity to absorb Zn without any disturbance in its metabolism, compared with other species tested (i.e. Davis and Beckett, 1978; MacNicol and Beckett, 1985).

Results for lead uptake from 25 µM into the shoots (Fig. 5A and B) showed several fold variation in total shoot content of Pb and in mean Pb concentrations in shoot tissue after 28 days exposure. The results were promising from the standpoint of selecting for high and low Pb accumulation, in so far as there was no association between total Pb accumulation per plant and tissue concentration of Pb across the population (Fig. 5A). Interestingly, the concentrations of Pb in the shoots were generally far higher than those recorded in the previously with ryegrass (Jones et al., 1973; Jarvis et al., 1977; Arienzo et. al., 2004).

SID 5 (Rev. 3/06) Page 14 of 29

0

20

40

60

80

100

120

0 50 100 150 200 250

Pb concentration (microg /g shoot d.w t)

Tota

l Pb

cont

ent o

f sho

ot (m

icro

g

/ pla

nt)

A

R2 = 0.770

20

40

60

80

100

120

0.0 0.5 1.0 1.5 2.0Shoot d.w t (g/plant)

Tota

l Pb

cont

ent o

f sho

ot (m

icro

g

/ pla

nt)

B

Fig. 5 Variation in (A) total lead content of the shoots and tissue concentrations of lead across 96 genotypes of the mapping family grown in flowing nutrient solutions containing 25 μM Pb, and (B) the relationship between shoot content of lead and final harvest shoot dry weight.

Tolerance to Pb, indexed by final shoot dry weight, also varied significantly across the population (Fig. 6A) but was generally higher than for Zn (Fig. 6B), for which most genotypes showed diminished growth rates ( circa 50%) in the presence of 100µM Zn. Interestingly there was little if any reduction in growth rate across the mapping family in the presence of 100 µM Fe.

0.0

0.5

1.0

1.5

2.0

0.0 0.5 1.0 1.5 2.0Shoot d.wt with zero Pb (g/plant)

Shoo

t d.w

t with

25m

M P

b g/

plan

t)

A

0

2

4

6

8

10

12

0 2 4 6 8 10 12Plant d.w t under control Zn (g)

Plan

t d.w

t und

er to

xic

Zn (g

)

B

Fig. 6. Comparison between tolerance in terms of dry matter production to (A) Pb (25 µM) and (B) Zn (100 µM) in flowing solution culture across 94 genotypes of the project mapping family. Straight lines indicate 1:1 relationship.

Plant residue decomposition in the rhizosphere in sand-box mini-swards:Plant-mediated variation in organic matter decomposition rates in the rhizosphere of sand-box mini-swards was assessed (Expt 1:23:53(A)) by incubation of buried ‘litter bags’ containing chopped L. perenne shoots (21 day incubation) and barley straw (36 day incubation) under summer conditions, and also under winter conditions with barley straw (131 day incubation). The results showed substantial variation across the mapping family in terms of proportional weight losses in the litters bags (Fig. 7A) and the C: N ratios of the residual organic matter (Fig. 7B), although there was no correlation between the two litter types (Fig. 7A). .

40

50

60

70

80

10 15 20 25 30 35 40Barley straw (% initial d.wt lost)

Rye

gras

s le

af li

tter

(% in

itial

d.

wt l

ost)

A

R2 = 0.130

50

100

150

200

250

10 15 20 25 30 35 40

% initial d.wt lost

C :

N d

.wt r

atio

of r

esid

ue B

Fig. 7. Genetic variation in organic matter decomposition rates: (A) Comparison of variation in d.wt losses of buried ryegrass ( over 21 days)and barley straw (over 36 days) litter bags incubated under mini-swards of 94 genotypes of the amenity x forage mapping family in sand-boxes (n=5 bags) under summer conditions. (B) Relationship between the d.wt C:N ratio of barley straw residue in litter bags and the proportion of the initial d.wt lost over the 36 day incubation for data shown in (A).

SID 5 (Rev. 3/06) Page 15 of 29

Comparison between barley straw decomposition under summer and winter conditions showed generally lower rates under the latter (Fig. 8A), but, disappointingly, there was little correlation across the genotypes (Fig. 8B).

0

10

20

30

40

50

< 10 10-15 15-20 20-25 25-30 30-35 35-40 > 40% initial d.wt lost

Num

ber o

f gen

otyp

es

summerwinter

A

05

10152025303540

10 15 20 25 30 35 40Summer (% initial bag d.wt lost)

Win

ter (

% in

itial

bag

d.w

t los

t) B

Fig. 8. (A) Frequency diagram comparing barley straw litter bag decomposition rates across the mapping family under summer (36 days) and winter (131 days) conditions, and (B) the relationship between decomposition rates measured for each of the 94 genotypes under summer and winter conditions.

Summarising the results, the experiments showed (1) dry matter losses were proportionately higher from ryegrass compared with barley litter bags, (2) limited variation between genotypes in terms of d.wt loss as proportion of initial d.wt, (3) little if any correlation amongst genotypes with respect to the extent of decomposition of the two litter types, and (4) insignificant differences in decomposition characteristic between amenity, forage or hybrid amenity x forage sward types.

Nitrate interception efficiencies in horizontal sand-bed lysimeters:Nitrate interception efficiency by 80 genotypes belonging to the project mapping family was measured in mini-swards grown in horizontal sand-bed lysimeters (Expt 1:23:69). The data set consisted of 23 runs (see Table 1). Inflow rates to gutters were not measured on all runs and it was assumed that the limited variation in inflow rates occurring between the gutters containing different genotypes within an inflow class (i.e. ‘low’ v ‘high’ rates) would not seriously bias nitrate interception rates. This proved true, in so far as there was little or no relationship between inflow and nitrate uptake (Fig. 9A). That there was no need to measure individual inflow rates was underlined by the close agreement (r2=0.98) between relative interception rates indexed against outflow from the ‘control zero- plant’ gutter and individual inflows to each gutter (Fig. 9B).

R2 = 0.12

0.0

0.5

1.0

1.5

2.0

2.5

3.0

2.0 2.5 3.0 3.5 4.0 4.5 5.0 5.5Inflow (micromoles NO3

- / min / tray)

Upt

ake(

mic

rom

oles

/ min

/tra

y) R2 = 0.98

-0.4

-0.2

0.0

0.2

0.4

0.6

0.8

1.0

-0.4 -0.2 0.0 0.2 0.4 0.6 0.8 1.0

1-(No/Nb)

(Ni -

No)

/Ni

Fig. 9. (A) Dependence of measured nitrate interception rates across 80 mapping family genotypes and actual inflow rates of nitrate into the horizontal lysimeters measured under conditions of ‘low inflow rates ‘ of leachate. (B) The relationship between ‘relative’ plant interception of nitrate expressed as (X-axis) proportional interception relative to blank tray outflow of nitrate (Nb) and (y-axis) proportional interception relative to measured inflow of nitrate (Ni), where No is the measured outflow of nitrate in both cases.

The variation across the mapping family in nitrate interception under prior pulse- and steady-state conditions with respect to nitrate nutrition was measured under a range of current and antecedent environmental (temperature, irradiance) and management (time after cutting) conditions. The data showed reasonable agreement in genotype ranking in absolute interception rates (Fig. 10A) under different light intensities and in terms of proportion of nitrate inflow removed (Fig. 10B).

SID 5 (Rev. 3/06) Page 16 of 29

R2 = 0.360.0

0.5

1.0

1.5

2.0

2.5

3.0

0.0 0.5 1.0 1.5 2.0 2.5 3.0Run 3 (micromoles NO3

- /min/tray)

Run

2 (m

icro

mol

es N

O3- /

min

/tray

)

A

R2 = 0.690.0

0.2

0.4

0.6

0.8

1.0

0.0 0.2 0.4 0.6 0.8 1.0Interception/inflow (Run 3)

Inte

rcep

tion/

inflo

w (R

un 2

) B

Fig.10. Variation in nitrate interception across 80 genotypes belonging to the project mapping family: (A) comparison between absolute rates of nitrate interception (uptake) measured on successive days (Runs 2 and 3) and (B) comparison of proportional interception of nitrate inflows. Run 2 was conducted under bright sunlight (high light intensity) and Run 3 under overcast conditions (low light intensity).

Plant water relationsTranspiration rate, expressed as a specific rate per unit leaf area and measured in flowing solution culture (Expts 1:23:63, 1:23:64) under both artificial and natural light, varied two-fold across the 94 mapping family genotypes (Fig. 11A). However responses under the contrasting light conditions showed little correlation, indicating further assessment is required to establish a basis for a robust QTL for specific transpiration rate. Nevertheless, the observation that specific transpiration rate appears to be independent of total plant leaf area (Fig. 11B), hence plant size, suggests that it may be possible to select for this without affecting growth.

Fig. 11. Variation in specific transpiration rates across 94 clones belonging to the amenity x forage perennial ryegrass mapping family, (A) measured in different experiments under constant artificial illumination (PAR of 500 µmol/m2/s) or fluctuating levels of natural illumination (PAR of 380-600 µmol/m 2/s) over 4 hours, and (B) the relationship between of specific transpiration rate under artificial illumination and total leaf area per plant.

Transpiration loss, expressed on a sward area basis, and stomatal conductance were also measured across the 80 genotypes grown in horizontal sand-bed lysimeters (Expt 1:23:69) under saturated conditions with respect to the water content of the rooting medium (Fig. 12). Transpiration rates varied more than two-fold across the family and showed reasonable correlation under overcast and sunny conditions (Fig. 12A). However, rates expressed on a sward area measured in sand-beds showed little correlation with the specific rates measured in flowing solution culture on single plants (Fig. 12B).

R2 = 0.560.10

0.20

0.30

0.40

0.50

0.60

0.70

0.10 0.15 0.20 0.25 0.30 0.35Run 4 (gH2O/min/tray)

Run

5 (g

H2O

/min

/tray

) A

0

50

100

150

200

100 200 300 400 500

g H20/h/m 2surface area

g H 20

/h/m

2 leaf

are

a

B

Fig. 12. (A) Variation in transpiration rates per mini-sward ( 0.115 m2 area) across 80 genotypes grown in sand-bed lysimeters under natural light conditions. Rates were measured on two occasions at the same point in the photoperiod: Run 4 was overcast and Run 5 (48 hrs later) was sunny. (B) Comparison between transpiration

SID 5 (Rev. 3/06) Page 17 of 29

rates per mini-sward in sand-bed lysimeters (measured under natural sun light (PAR of 1000-1200 µmol/m2/s) and specific transpiration rates measured on single plants in flowing solution culture (expressed per unit leaf area), under fluctuating levels of natural illumination (PAR of 380-600 µmol/m2/s) over 4 hours.

020406080

100120140160

50 100

150

200

250

300

350

400

450

500

Mor

e

Class (mmol/m2/s)

Freq

uenc

y

A

R2 = 0.15

0.10

0.20

0.30

0.40

0.50

50 150 250 350Stomatal conductance (mmol/m2/s)

Tran

spira

tion

(gH

2O/m

in/tr

ay)

B

Fig. 13. (A) frequency distribution for stomatal conductance measurements made on 7 leaves of each of the 80 genotypes grown in sand-bed lysimeters, and (B) The relationship between areal transpiration rates (means of runs 4&5 shown in Fig.12A) and mean stomatal conductance measured for the genotype.

Individual stomatal conductance measurements showed a non normal distribution across the 80 genotypes (Fig. 13A). Single factor ANOVA indicated a significant genotype effect (p = 0.002). However, there was little correlation between net transpiration loss expressed on an area basis and conductance (Fig. 13B).

Carbon return in litter As an adjunct to Expt 1:23:53(B), a final herbage cut was taken from all the sand-based mini-swards on 6/07/06. Additionally, all litter/thatch and dead plants (including root systems) were removed to provide an estimate net C return (Fig. 14).

0

50

100

150

200

250

300

0 20 40 60

Herbage cut C content (gC/m2)

Litt

er &

dea

d pl

ant C

con

tent

(g

/m2)

Fig. 14. Comparison between the total C content of litter and dead plant material removed from sand box mini swards of 94 mapping family genotypes and the content of the herbage cut taken at the same time. Values are means of two sand boxes per genotype.

Quantitative trait loci (QTLs)QTLs (threshold LOD>2.0) were detected for 15 traits on the amenity allele map (Table 3) and 28 traits on the forage allele map (Table 4). Data were also mapped onto a pre-existing SSR-based map for the population, revealing QTLs for a total of 38 traits (data not presented). QTLs, frequently overlapping, were detected for traits associated with the most of the ‘ecosystem services’ addressed in the project. The majority of LOD scores ranged between 2-3 (Tables 2 & 3), with ‘the percentage of variance accounted for’ ranging between 10-15%. However, there were several QTLs with LODs between 5-10 ( 20-50% variation accounted for). Notable, amongst these were the multiple QTLs for C deposition in litter (trait 262) on linkage group 1 of the forage allele map, and the coincidental QTLs for nitrate interception (traits 342-343). The locations of the QTLs are shown on the outline linkage maps for the forage alleles (Figs. 15 & 16) and the amenity alleles (Fig. 17).

Under Objective 1, heavy-metal specific QTLs were identified for tolerance (in terms of growth) to Fe (linkage group 1), Zn (linkage group 4) and Pb (linkage group 4). Under Objective 2, heavy-metal specific QTLs were identified for plant content of Fe (linkage group 1) and Pb (linkage group 5), together with a range of traits associated with the accumulation and partitioning of Fe, Zn and Pb between roots and shoots. Under Objective 3, an extensive QTL region for stomatal conductance was identified on linkage group 1, partially coinciding with QTLs for transpiration rate per unit leaf area, but distinct from QTLs for sward transpiration rate expressed on a

SID 5 (Rev. 3/06) Page 18 of 29

ground area basis (linkage groups 4, 6 & 7). Under Objective 6, extensive QTL regions were identified on linkage group 1 for nitrate interception by mini-swards, specific to steady-state conditions of nitrate inflow. However, a specific QTL for nitrate interception under ‘pulsed’ (i.e. episodic) nitrate supplies was detected on linkage group 5. A non-specific QTL for net decomposition of added organic matter in the rhizosphere (Objective 7) was identified on linkage group 1 (@ 14.4 cM), together with specific (linkage group 2) and non-specific (linkage group 5 ) QTLs for C:N ratios of organic matter residues. A specific QTL for the C return in litter (Objective 8) was detected on linkage group 5 and a very strong non-specific QTL region for this trait (LODs 6.6-10.4) was also detected on linkage group 1, coinciding with a number of growth-related QTLs.

Table 3. QTLs with LOD > 2.0 detected on the project amenity x forage map (amenity alleles). The recorded QTL position is that of the peak LOD score given by interval mapping. The significance level of the Kruscal-Wallis test statistic associated with each of the QTLs is also given. % variance explained = percentage phenotypic variation explained by the QTL. Trait number refers to the project’s referencing system. Category Trait

NoDescription Linkage

groupPositio

n(cM)

Marker / locus LODscore

% varianceexplained

Kruscal-WallisSignificance

(P)Fe toxicity 89 Tiller numbers

relative to control plants

1 0 a_ACC-CCC.88 2.12 9.9 0.001

92 Shoot d.wt relative to control plants

1 0 a_ACC-CCC.88 2.17 10.1 0.001

101 [ Fe] in roots relative to control plants

5 73.6 a_ACT-CAA.159 2.56 11.8 0.001

Zn toxicity 145 Relative growth rate (f.wts)

4 34.8 a_ACTCTC.210 2.5 11.5 0.001

155 Shoot:root ratio relative to control plants

3 7.5 a_ACA-CAC.27 2.3 10.7 0.005

Pb toxicity 175 Relative growth rate (f.wts)

4 0 a_ACA-CAC.35 2.11 9.8 0.005

181 Shoot d.wt 5 73.6 a_ACT-CAA.159 2.2 10.2 0.005188 Total Pb content

of plant5 73.6 a_ACT-CAA.159 3.03 13.8 0.001

190 Shoot Pb content 5 73.6 a_ACT-CAA.159 2.48 11.4 0.001Rhizosphere decomposition

196 C:N ratio of long termbarley straw residue

2 15 a_ACTCTC.201 2.06 9.6 0.005

Plant waterRelations

270 Transpiration per unit ground area(overcast)

4 50.4 a_ACA-CAA.19 3.07 16.6 0.0005

274 Transpiration per unit ground area(sunny)

4 1.1 a_ACTCTG.228 2.22 12.3 0.005

C deposition 259 Total C in herbage cut

1 44.7 a_ACTCTC.207 3.05 13.9 0.05

259 5 78 a_ACTCTC.199 2.5 11.5 0.0005259 5 79.1 a_ACT-CAA.168 2.27 10.5 0.001259 5 79.1 a_ACC-CCT.108 2.27 10.5 0.001259 5 79.1 a_ACT-CAA.152 2.27 10.5 0.001259 5 95.3 a_ACC-CAA.69 2.49 11.5 0.0005260 5 37.6 a_ACC-CCT.113 2.44 11.3 0.005260 5 41.7 a_ACC-CCC.87 2.54 11.7 0.005262 Total C in litter 5 37.6 a_ACC-CCT.113 3.04 13.8 0.005262 5 41.7 a_ACC-CCC.87 2.91 13.3 0.001262 5 42.4 a_ACC-CAC.75 2.81 12.8 0.005262 5 46.1 a_ACT-CAA.167 2.85 13 0.005

Nitrate 341 Nitrate interception (pulsed supply)

5 73.6 a_ACT-CAA.159 2.1 11.6 0.005

buffering 341 5 78 a_ACTCTC.199 2.18 12.1 0.005341 5 79.1 a_ACT-CAA.168 2.25 12.4 0.005341 5 79.1 a_ACC-CCT.108 2.25 12.4 0.005341 5 79.1 a_ACT-CAA.152 2.25 12.4 0.005

SID 5 (Rev. 3/06) Page 19 of 29

Table 4. QTLs with LOD > 2.0 detected on the project amenity x forage map (forage alleles). The recorded QTL position is that of the peak LOD score given by interval mapping. The significance level of the Kruscal-Wallis test statistic associated with each of the QTLs is also given. % variance explained = percentage phenotypic variation explained by the QTL. Trait number refers to the project’s internal referencing system.Category(Table 4.)

TraitNo.

Description Linkagegroup

Position(cM)

Locus LODscore

% variance explained

Kruscal-WallisSignificance

(P)Fe toxicity 82 F.wt gain 1 22.9 f_ACC-CAC.84 2.04 9.5 0.005

100 [Fe] in roots 6 51.7 f_ACT-CTA.183 2.66 12.2 0.005104 Total Fe content

of plant relative to control

1 22.9 f_ACC-CAC.84 2.84 13 0.001

104 2 0 f_ACC-CCT.104 2.15 10 0.001106 Proportional Fe

content of shoot 4 24.4 f_ACC-CCT.103 3.09 14 0.0001

Zn toxicity 145 Relative growth rate (f.wts)

4 24.4 f_ACC-CCT.103 1.99 9.3 0.005

148 Tiller number 1 26 f_ACC-CAC.82 2.23 10.3 0.005154 Shoot:root ratio 1 22.9 f_ACC-CAC.84 2.32 10.8 0.005154 1 26 f_ACC-CAC.82 2.32 10.8 0.005160 [Zn] in roots 1 26 f_ACC-CAC.82 2.4 11.1 0.005160 6 8.3 f_ACA-CTA.39 2.51 11.6 0.0005160 6 20.7 f_ACG-CTG.145 2.75 12.6 0.0005160 6 24.3 f_ACC-CCC.97 3.32 15 0.0001160 6 26.1 f_ACTCTC.202 3.21 14.5 0.0001160 6 28.7 f_ACT-CAA.151 2.59 11.9 0.0005161 [Zn] in roots

relative to control plants

7 20 f_ACC-CAA.70 2.43 11.2 0.0005

161 7 32.2 f_ACC-CCC.96 2.18 10.1 0.005166 Proportional Zn

content of shoot 6 8.3 f_ACA-CTA.39 3.5 15.8 0.0001

166 6 20.7 f_ACG-CTG.145 5.15 22.3 0.0001166 6 24.3 f_ACC-CCC.97 6.16 26 0.0001166 6 26.1 f_ACTCTC.202 5.39 23.2 0.0001166 6 28.7 f_ACT-CAA.151 3.44 15.5 0.0001166 6 37 f_ACG-CTG.138 2.38 11 0.001167 Proportional Zn

content of shoot relative to controls

6 8.3 f_ACA-CTA.39 2.76 12.6 0.0005

167 6 20.7 f_ACG-CTG.145 3.29 14.9 0.0001167 6 24.3 f_ACC-CCC.97 4.17 18.5 0.0001167 6 26.1 f_ACTCTC.202 3.68 16.5 0.0001

Pb toxicity 186 [Pb] in shoot 1 0 f_ACT-CTA.187 2.51 11.6 0.001186 1 6 f_ACG-CTA.129 3.07 14 0.0005186 1 9.7 f_ACC-CAA.64 2.63 12.1 0.001186 1 12 f_ACA-CAC.37 2.55 11.7 0.005186 1 14.4 f_ACC-CCC.91 2.83 12.9 0.001186 2 0 f_ACC-CCT.104 3.16 14.4 0.005188 Plant Pb content 1 0 f_ACT-CTA.187 2.41 11.1 0.001188 1 14.4 f_ACC-CCC.91 2.3 10.7 0.005190 Shoot Pb content 1 0 f_ACT-CTA.187 2.32 10.7 0.0005190 1 9.7 f_ACC-CAA.64 2.12 9.9 0.005190 1 14.4 f_ACC-CCC.91 2.48 11.4 0.001

Rhizospheredecomposition

192 C:N ratio of ryegrass litter residue

5 21.6 f_ACC-CAA.58 2.23 10.3 0.0005

192 5 21.6 f_ACC-CCT.105 2.23 10.3 0.0005192 5 49.7 f_ACTCTG.222 2.04 9.5 0.005193 Proportional

decomposition of barley straw

1 14.4 f_ACC-CCC.91 2.05 9.5 0.005

Plant waterrelations

268 Transpiration rate (unit leaf area)

1 12 f_ACA-CAC.37 2.17 10.1 0.005

268 1 14.4 f_ACC-CCC.91 2.24 10.4 0.005

SID 5 (Rev. 3/06) Page 20 of 29

Category(Table 4.)

TraitNo.

Description Linkagegroup

Position(cM)

Locus LODscore

% variance explained

Kruscal-WallisSignificance

(P)269 Transpiration

rate (unit leaf area)

1 9.7 f_ACC-CAA.64 2.11 9.8 0.005

269 1 12 f_ACA-CAC.37 2.52 11.6 0.005269 1 14.4 f_ACC-CCC.91 2.52 11.6 0.005270 Transpiration

rate (unit sward area):overcast

7 14.7 f_ACC-CCC.94 3.19 17.2 0.0005

270 7 20 f_ACC-CAA.70 3.33 17.8 0.0005270 7 23.4 f_ACG-CTG.136 2.24 12.4 0.005270 7 32.2 f_ACC-CCC.96 2.06 11.5 0.005272 Transpiration

rate (unit sward area): overcast

6 26.1 f_ACTCTC.202 2.19 12.1 0.001

273 Transpiration rate (unit sward area): overcast

7 14.7 f_ACC-CCC.94 2.28 12.6 0.005

273 7 20 f_ACC-CAA.70 2.67 14.9 0.005276 Transpiration

rate (unit sward area): sunshine

5 21.6 f_ACC-CAA.58 2.43 13.4 0.001

276 5 21.6 f_ACC-CCT.105 2.43 13.4 0.001277 Stomatal

conductance1 6 f_ACG-CTA.129 2.18 12.1 0.005

277 1 12 f_ACA-CAC.37 2.11 11.7 0.005277 1 14.4 f_ACC-CCC.91 2.43 13.4 0.005277 1 22.9 f_ACC-CAC.84 2.46 13.5 0.001277 1 26 f_ACC-CAC.82 2.09 11.6 0.005277 2 19.7 f_ACC-CAA.73 2.18 12.1 0.005277 3 7.3 f_ACT-CAA.166 2.67 14.6 0.001277 3 10.4 f_ACC-CTG.114 2.59 14.2 0.005

C deposition 259 Total C in herbage

1 0 f_ACT-CTA.187 3.22 14.6 0.0001

259 1 6 f_ACG-CTA.129 2.31 10.7 0.0005259 1 9.7 f_ACC-CAA.64 2.58 11.9 0.0005259 1 12 f_ACA-CAC.37 3.26 14.7 0.0001259 1 14.4 f_ACC-CCC.91 2.27 10.5 0.0001259 1 22.9 f_ACC-CAC.84 2.53 11.7 0.0005259 1 26 f_ACC-CAC.82 2.28 10.6 0.0005259 6 37 f_ACG-CTG.138 2.44 11.2 0.005262 Total C in litter 1 0 f_ACT-CTA.187 2.75 12.6 0.001262 1 6 f_ACG-CTA.129 7.52 30.8 0.0001262 1 9.7 f_ACC-CAA.64 10.42 40 0.0001262 1 12 f_ACA-CAC.37 8.89 35.3 0.0001262 1 14.4 f_ACC-CCC.91 9.24 36.4 0.0001262 1 22.9 f_ACC-CAC.84 7.99 32.4 0.0001262 1 26 f_ACC-CAC.82 7.66 31.3 0.0001262 1 40.8 f_ACT-CAA.149 6.39 26.9 0.0001

Nitrate buffering

342 Nitrate interception (constant supply)

1 0 f_ACT-CTA.187 6.62 32.4 0.0001

342 1 6 f_ACG-CTA.129 8.5 39.5 0.0001342 1 9.7 f_ACC-CAA.64 8.09 38 0.0001342 1 12 f_ACA-CAC.37 8.88 40.8 0.0001342 1 14.4 f_ACC-CCC.91 7.95 37.5 0.0001342 1 22.9 f_ACC-CAC.84 10.37 45.6 0.0001342 1 26 f_ACC-CAC.82 8.75 40.4 0.0001342 1 40.8 f_ACT-CAA.149 2.27 12.6 0.005342 2 0 f_ACC-CCT.104 2.46 13.5 0.001342 6 28.7 f_ACT-CAA.151 2.02 11.3 0.005342 6 37 f_ACG-CTG.138 2.24 12.4 0.005

SID 5 (Rev. 3/06) Page 21 of 29

Category(Table 4.)

TraitNo.

Description Linkagegroup

Position(cM)

Locus LODscore

% variance explained

Kruscal-WallisSignificance

(P)343 Nitrate

interception (high temp)

1 0 f_ACT-CTA.187 5.55 27.9 0.0001

343 1 6 f_ACG-CTA.129 8.01 37.7 0.0001343 1 9.7 f_ACC-CAA.64 8.21 38.4 0.0001343 1 12 f_ACA-CAC.37 8.69 40.1 0.0001343 1 14.4 f_ACC-CCC.91 7.78 36.4 0.0001343 1 22.9 f_ACC-CAC.84 11.5 49.3 0.0001343 1 26 f_ACC-CAC.82 10.03 44.7 0.0001343 1 40.8 f_ACT-CAA.149 3.37 18 0.0005343 2 0 f_ACC-CCT.104 3.46 18.5 0.0005344 Nitrate

interception (low temp)

1 0 f_ACT-CTA.187 6.4 31.5 0.0001

344 1 6 f_ACG-CTA.129 9.02 41.3 0.0001344 1 9.7 f_ACC-CAA.64 7.51 35.8 0.0001344 1 12 f_ACA-CAC.37 9.21 41.9 0.0001344 1 14.4 f_ACC-CCC.91 8.5 39.5 0.0001344 1 22.9 f_ACC-CAC.84 11.9 50.5 0.0001344 1 26 f_ACC-CAC.82 10.24 45 0.0001344 1 40.8 f_ACT-CAA.149 3.38 18.1 0.0005344 2 0 f_ACC-CCT.104 2.28 12.6 0.005

SID 5 (Rev. 3/06) Page 22 of 29

amenity x forage Lolium map (forage alleles)

f_ACT-CTA.1870.0

f_ACG-CTA.1296.0

f_ACC-CAA.649.7f_ACA-CAC.3712.0f_ACC-CCC.9114.4

f_ACC-CAC.8422.9f_ACC-CAC.8226.0

f_ACT-CAA.14940.8

Pb(188,190)

Pb(188)

Zn(154)

Pb(186)

Fe(82,104)

Decom

position(193)

190190

Zn(148,160)

1

f_ACC-CCT.1040.0

f_ACC-CAA.7319.7f_ACC-CAA.6821.9f_ACC-CTG.11924.2f_ACA-CAA.2227.2f_ACC-CCT.10030.3

f_ACC-CCC.9236.2

[Pb] in shoots (186)

Fe content relative to controls (104)

2

f_ACC-CAA.510.0f_ACC-CAA.524.2f_ACTCTC.2035.1f_ACTCTG.2306.8f_ACT-CAA.1667.3f_ACC-CTG.11410.4f_ACA-CAA.1512.4

f_ACTCTG.22726.5

3

f_ACG-CTG.1390.0

f_ACT-CTA.1908.6

f_ACTCTG.21717.3

f_ACC-CCT.10324.4

f_ACTCTG.22531.6

f_ACC-CCT.9965.5

Fe: proportion tranlocated (106)

Zn: relative growth rate (145)

4

f_ACT-CAC.1810.0

f_ACG-CTA.131f_ACA-CTA.4615.6

f_ACC-CAA.58f_ACC-CCT.10521.6

f_ACT-CAA.16436.8

f_ACTCTG.22249.7

f_ACC-CTG.12359.7

Decom

position(192)D

ecomposition(192)

5

f_ACT-CAA.1700.0

f_ACA-CTA.398.3

f_ACG-CTG.14520.7

f_ACC-CCC.9724.3f_ACTCTC.20226.1f_ACT-CAA.15128.7

f_ACG-CTG.13837.0

f_ACT-CTA.18351.7

Zn: relative shoot content (167)

[Zn] roots (160)

Zn: shoot content (166)[Fe] in roots(100)

6

f_ACA-CTA.470.0

f_ACC-CCC.9414.7

f_ACC-CAA.7020.0

f_ACG-CTG.13623.4

f_ACC-CCC.9632.2

Rel. [Zn] roots (161)161)

7

Fig. 15. Linkage map (forage alleles) showing QTLs (LOD>2.0) for traits associated with heavy metal tolerance and rhizosphere decomposition of organic matter. Different colours are used to denote each metal/process. The trait identification number given in parenthesis refers to the listing in Table 4.

SID 5 (Rev. 3/06) Page 23 of 29

amenity x forage Lolium map (forage alleles)

f_ACT-CTA.1870.0

f_ACG-CTA.1296.0

f_ACC-CAA.649.7f_ACA-CAC.3712.0f_ACC-CCC.9114.4

f_ACC-CAC.8422.9f_ACC-CAC.8226.0

f_ACT-CAA.14940.8

277S

tom.conductance (277)

Transpiration(268,269)

C deposition (259)

C depos(262)

N03 buffering (constant supply)(342,343,344)

1

f_ACC-CCT.1040.0

f_ACC-CAA.7319.7f_ACC-CAA.6821.9f_ACC-CTG.11924.2f_ACA-CAA.2227.2f_ACC-CCT.10030.3

f_ACC-CCC.9236.2

NO

3 buff (342,343,344)(277)

2

f_ACC-CAA.510.0f_ACC-CAA.524.2f_ACTCTC.2035.1f_ACTCTG.2306.8f_ACT-CAA.1667.3f_ACC-CTG.11410.4f_ACA-CAA.1512.4

f_ACTCTG.22726.5

Stom

atal conductance(277)

3

f_ACG-CTG.1390.0

f_ACT-CTA.1908.6

f_ACTCTG.21717.3

f_ACC-CCT.10324.4

f_ACTCTG.22531.6

f_ACC-CCT.9965.5

4

f_ACT-CAC.1810.0

f_ACG-CTA.131f_ACA-CTA.4615.6

f_ACC-CAA.58f_ACC-CCT.10521.6

f_ACT-CAA.16436.8

f_ACTCTG.22249.7

f_ACC-CTG.12359.7

Transpiration(sunny) (276)

5

f_ACT-CAA.1700.0

f_ACA-CTA.398.3

f_ACG-CTG.14520.7

f_ACC-CCC.9724.3f_ACTCTC.20226.1f_ACT-CAA.15128.7

f_ACG-CTG.13837.0

f_ACT-CTA.18351.7

NO

3 buffering(342)

C depos(259)Transp.(272)

6

f_ACA-CTA.470.0

f_ACC-CCC.9414.7

f_ACC-CAA.7020.0

f_ACG-CTG.13623.4

f_ACC-CCC.9632.2

Transpiration(270)

Transpiration(overcast( (273)

7

Fig. 16. Linkage map (forage alleles) showing QTLs (LOD>2.0) for traits associated with aspects of plant water relations, C deposition and nitrate buffering capacity. Different colours are used to denote each metal/process. The trait identification number given in parenthesis refers to the listing in Table 4.

SID 5 (Rev. 3/06) Page 24 of 29

Amenity x forage Lolium map (amenity alleles)

a_ACC-CCC.880.0

a_ACTCTC.19832.7

a_ACT-CAA.16142.8a_ACTCTC.20744.7a_ACC-CAA.4949.8a_ACT-CAA.147a_ACC-CTG.11750.7

a_ACTCTG.21472.1a_ACG-CTG.14277.1a_ACT-CAA.16082.3

Fe growth (89,92)

C deposition (259)

1

a_ACT-CAC.1800.0

a_ACT-CTA.19612.9a_ACTCTC.20115.0

a_ACG-CTA.13422.4a_ACA-CAA.1227.8a_ACTCTG.22332.7a_ACA-CAA.1437.5

Decom

position(196)

2

a_ACA-CAC.250.0

a_ACA-CAC.277.5a_ACA-CAA.139.5a_ACTCTG.22913.9

a_ACT-CTA.19321.2a_ACC-CAA.6628.6a_ACTCTC.20929.3a_ACC-CCT.10130.1a_ACA-CAA.438.1a_ACA-CTA.4242.5

a_ACA-CAA.262.1

Zn shoot:root (155)

3

a_ACA-CAC.350.0a_ACTCTG.2281.1

a_ACG-CTA.12516.9

a_ACC-CTG.12126.3

a_ACTCTC.21034.8

a_ACA-CAA.1950.4

Pb grow

th (175)Zn grow

th (145)

Transpiration:(sunny) (274)(overcast) (270)

4

a_ACT-CAA.1480.0

a_ACT-CAA.15614.0

a_ACC-CCT.11337.6a_ACC-CCC.8741.7a_ACC-CAC.7542.4a_ACT-CAA.16746.1a_ACC-CAC.8149.2

a_ACC-CCC.9364.0

a_ACT-CAA.15973.6a_ACTCTC.19978.0a_ACT-CAA.168a_ACC-CCT.108a_ACT-CAA.152

79.1

a_ACC-CAA.6995.3

a_ACC-CTG.116111.8

C deposition (260)

Fe root conc (101)

Pb grow

th and content (181,188,190)

C deposition (262)

C deposition (259)

NO

3 buffering (pulsed supply) (341)

5

a_ACC-CCT.1090.0

a_ACT-CAC.17511.2

a_ACTCTG.21621.8a_ACG-CTA.13326.4a_ACT-CAA.16328.8a_ACA-CAC.3231.9

a_ACT-CAA.16956.4

6

a_ACT-CTA.1940.0a_ACA-CAC.304.2a_ACA-CAC.3311.1a_ACC-CAC.8612.1

a_ACT-CTA.18529.3

7

Fig. 17. Linkage map (amenity alleles) showing QTLs (LOD>2.0) for 15 traits associated with heavy metal tolerance, rhizosphere decomposition of organic matter, aspects of plant water relations, C deposition and nitrate buffering capacity. Different colours are used to denote each metal/process. The trait identification number given in parenthesis refers to the listing in Table 3.

SID 5 (Rev. 3/06) Page 25 of 29

Evaluation and prioritisation of traits The project was conducted in liaison ‘operationally’ with colleagues in IGER’s plant breeding department, particularly in the ‘amenity’ sector, to ensure take up germplasm and mapping information for marker assisted selection and incorporation of ‘environmental’ traits. When appropriate, it is envisaged that demonstration of results to the user community will be through the existing ‘IGER Grassland Technology Transfer’ program of activities. Discussions regarding the prioritisation of ‘ecosystem service’ traits for incorporation into commercial breeding programmes highlighted a number of uncertainties when judged against including:-

1. The need for an economic analysis of prospective market size and profitability in the UK and abroad.2. The comparative economic importance of different prospective ecosystem services in the UK and the

cost-benefits of incremental improvements (i.e. 5%, 10%, 20% etc) through use of new varieties. 3. The absence of variety testing, trial and certification procedures with respect to ‘ecosystem service’

performance.4. The likelihood of statutory (i.e. Defra) incentives and inclusion in existing ‘environmental stewardship

schemes’ to encourage take-up of varieties by farmers.5. The net environmental impact of widespread re-sowing (i.e. on soil organic matter levels).6. The impact of future changes in Government policy with respect to the balance between production and

environmental protection goals.7. The need for more detailed studies of the genetic basis for ‘ecosystem service’ traits and their efficacy

within a variety of genetic backgrounds.8. Demonstration of the quantitative impacts at the field/catchment scale.9. The likelihood of significant inter-specific variation in efficacy and arguments for species other than

Lolium perenne as preferred subjects for some ecosystem services.

It was also apparent that some traits are far more difficult to screen for than others in terms of time-scale and/or technical/experimental resources required (i.e. C sequestration). Hence, informed judgements regarding the feasibility of breeding for these traits are not yet possible. It was, however, concluded that it was technically possible to embark on selection programmes for all the traits covered by this project. However, progress was most likely to be most rapid with respect to (a) nitrate interception efficiency and (b) heavy metal tolerance and accumulation, the latter also being highly relevant to the global problems of micronutrient deficiencies in cereal crops destined for human consumption.

Commercial Exploitation:Commercial exploitation of the project outputs will primarily be through the transfer of information to IGER’s operational breeders in the forage and amenity sectors, as well as other interested parties (e.g. in the bioremediation industry) for the development of varieties. Importantly, the project provides the basis for a marker assisted selection approach to achieving the above objectives as opposed to a GMO approach. The project was conducted in liaison ‘operationally’ with several colleagues in IGER’s plant breeding department, particularly in the ‘amenity’ sector, to ensure take up germplasm and mapping information for marker assisted selection and incorporation of ‘environmental’ traits. Pilot demonstration of results to the user community will be through the existing ‘IGER Grassland technology Transfer’ program of activities.

Development of 'multi-functional' (i.e. forage/environmental quality) and 'specialist' (environmental quality) varieties would assist the implementation of Defra’s policy of encouraging environmental stewardship of land, providing land managers with a new mechanism for 'adding environmental value' to enterprises, which could be formalised through qualification for 'environmental support payments' by Defra. ‘Specialist' environmental quality varieties and ecotypes will also benefit the UK's 'waste disposal' industries (i.e. via new opportunities for amelioration of land-applications ) and the phytoremediatory component of the growing global bioremediation industry, the market being an estimated £50 billion in 2000 according to OECD figures.

Knowledge transfer:Contacts with commercial companies active in the bioremediation field are currently being developed through IGER’s Business Office to explore the wider potential for development of 'ecosystem service' ecotypes and varieties targeted at the UK's land-remediation and 'waste disposal' sectors (i.e. to develop new techniques and products for brown-field site amelioration), given that the global bioremediation industry is valued at an estimated £50 billion in 2000 according to OECD figures.

Future work:This project constituted a ‘first look’ at the feasibility of selectively breeding forage grasses for a range of ‘ecosystem services’ previously disregarded as breeding objectives on economic grounds, but now recognised as increasingly important for society as a whole. Potentially useful genetic variation in a number of plant attributes associated with a range of processes impacting on environmental quality was demonstrated in the project. However, the results can only be viewed as a preliminary and highly superficial assessment, given the size of the project and the broad range of traits surveyed. This applies in particular to C sequestration, which merits a far more sophisticated assessment, given its importance in the context of Global warming. Detailed genetic appraisal of traits deemed to be priorities by Defra would be prudent prior to investing the considerable resources required

SID 5 (Rev. 3/06) Page 26 of 29

for variety development. Nevertheless, the identification of QTLs for traits in Lolium perenne conferring environmental benefits provides a basis for economically important new initiatives in germplasm improvement tailored towards the emerging markets of environmental protection, remediation and improvement, and complementing improvements in forage productivity, quality and resource use efficiency.

The experimental platforms developed for trait assessment in mapping families during this project constitute useful tools for further research into the genetics of environmental protection. The horizontal sand-bed lysimeters and the mini-swards lend themselves to lysimetric approaches to evaluating (plant) genetic determinants of key N-cycle processes including leaching, nitrification and mineralisation. Likewise, the clonal field-plots offer the opportunity to assess the genetic control of above ground as well as below ground biodiversity associated with traits such as canopy heterogeneity and its dependence on management (i.e. cutting frequency and height)

Specific gaps in the knowledge identified1) The feasibility of ‘scaling up’ in terms of traits promoting environmental quality and ecosystem services.2) The impact of incorporating traits promoting environmental quality into agronomically elite genetic material.3) The identity of the genes underlying the relevant QTLs in Lolium perenne and other grasses.4) The extent of synteny with other monocots including as wheat and rice, and the potential application of this. Globally, this would be particularly valuable for heavy metal tolerance and accumulation as there is currently relatively little information on their genetic basis.5) The absence of information on the long term effects of different grass species and varieties on the C status of the soil.

References:Arienzo M Adamo P Cozzolino V 2004. The potential of Lolium perenne for revegetation of contaminated soil from a metallurgical site. Science of the Total Environment 319, 13-25. Bonnet M Camares O Veisseire P 2000. Effects of zinc and influence of Acremonium lolii on growth parameters, chlorophyll a fluorescence and antioxidant enzyme activities of ryegrass (Lolium perenne L. cv Apollo). Journal of Experimental Botany 51, 945-953.Brady NC 1974. The Nature and Properties of Soil . Macmillan, New York.Clement CR Hopper MJ Canaway RJ Jones LHP 1974. A system for measuring the uptake of ions by plants from solutions of controlled composition. Journal of Experimental Botany 25, 81-99.Clement CR Hopper MJ Jones LHP 1978a. The uptake of nitrate by Lolium perenne from flowing nutrient solution. I. Effect of NO3

- concentration. Journal of Experimental Botany 29, 453-64.Davies RD Beckett PHT. 1978. Upper critical levels of toxic elements in plants. II. Critical levels of Cu in young barley, wheat, rape, lettuce and rye grass and of Ni and Zn in young barley and rye grass. New Phytologist 80, 23-32. Defra. 2002. The Strategy for Sustainable Farming and Food. Defra Publications, London. 52p.Fiener P Auerswald K 2003. Concept and effects of a multipurpose grassed waterway. Soil Use and Management 19, 65-72.Gay A. 1994. Breeding for leaf water conductance, its heritability and its effect on water use in Lolium perenne. Aspects of Applied Biology 38, 41-46.Hatch DJ Hopper MJ Dhanoa MS 1986. Measurement of ammonium ions in flowing solution culture and diurnal variation in uptake in Lolium perenne. Journal of Experimental Botany 37, 589-96.Henriksen A Selmer-Olsen AR. 1970. Automatic methods for determining nitrate and nitrite in water and soil extracts. Analyst 95, 514-518.Jarvis SC Jones LHP Clement CR 1977. Uptake and transport of lead by perennial ryegrass from flowing solution culture with a controlled concentration of lead. Plant and Soil 46, 371-379.Jarvis PG. McNaughton KG. 1986. Stomatal control of transpiration: scaling up from leaf to region. In: Advances in Ecological Research 15, 1-49. London: Academic press.Jones LHP, Clement CR Hopper MJ 1973. Lead uptake from solution by perennial ryegrass and its transport from roots to shoots. Plant and Soil 38, 403-414.Kosambi, DD. 1944. The estimation of map distances from recombination values. Annals of Eugenics 12.Macnair MR. 1993. The genetics of metal tolerance in vascular plants. New Phytologist 124, 541-559.MacNicol RG Beckett PHT 1985. Critical tissue concentrations of potentially toxic elements. Plant and Soil 85, 107-130.Qu RL Li D Du R Qu R. 2003. Lead uptake by roots of four turfgrass species in hydroponic cultures. HortScience 38, 623-626.Rauh BL Basten C Buckler IV ES 2002 Quantitattive trait loci analysis of growth response to varying nitrogen sources in Arabidopsis thaliana Theoretical Applied Genetics 104, 743-750.Ryser P. 1996. The importance of tissue density for growth and life span of leaves and roots: a comparison of five ecologically contrasting species. Functional Ecology 10, 717-723.Scholefield D, Chadwick D, Macey N. 1998. Design criteria for effective buffer zones. Ecological Aspects of Grassland Management 17th EGF Meeting, 1998, 587-590.Soussana, J-F Minchin FR Macduff JH Raistrick N Abberton MT Michaelson-Yeates TPT 2002. A simple model of fed-back regulation for nitrate uptake and N2 fixation in contrasting phenotypes of white clover. Annals of Botany 90, 139-147.

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Van Ooijen JW Boer MP Jansen RC Maliepaard C. 2002. Map QTL® 4.0, software for the calculation of QTL positions on genetic maps. Wageningen, The Netherlands: Plant Research International.Vos P Hogers R Bleeker M Reijans M van de Lee T Hornes M Frijters A Pot J Peleman J Kuiper M Zabeau M. 1995. AFLP: a new technique for DNA fingerprinting. Nucleic Acids Research. 23 No. 21 4407-4414.Wieder RK Lang GE 1982. A critique of the analytical methods used in examining decomposition data obtained from litter bags. Ecology 63, 1636-1642.Wilkins PW Macduff JH Raistrick N Collison M 1997. Varietal differences in perennial ryegrass for nitrogen use efficiency in leaf growth following defoliation: performance in flowing solution culture and its relationship to yield under simulated grazing in the field. Euphytica 98, 109-119.

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.

SID 5 (Rev. 3/06) Page 28 of 29

Warrender R. 2005. The Phytoextraction potential of Lolium perenne for the remediation of heavy-metal contaminated mine spoil, with particular reference to genotypic variation in tolerance within a mapping family. M.Sc Thesis: Environmental Monitoring and Analysis, Institute of Geography and earth Sciences University of Wales, Aberystwyth.

Macro A. 2005. Genotypic variation within adapted ecotypes of Lolium perenne for tolerance and phytoremediation potential to contaminated mine spoil. M.Sc Thesis: Environmental Monitoring and Analysis, Institute of Geography and earth Sciences University of Wales, Aberystwyth.

Project content/progress has been reported to delegate parties from:-1) 10th International Turfgrass Research Conference, Llandudno (July 2005).2) 4th International Symposium on the Molecular Breeding of Forage and Turf & Post-Congress Satellite Workshop of the XX International Grassland Congress - Genetic improvement of grasses and other forage crops, UWA Aberystwyth (2005).

A number of research publications based on the results obtained in this project are currently in preparation.

SID 5 (Rev. 3/06) Page 29 of 29