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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.

This form is in Word format and the boxes may be expanded or reduced, as appropriate.

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 HH3504SPO

2. Project title

Sustainable Phosphorus Fertilisation of Potatoes

3. Contractororganisation(s)

Warwick HRIUniversity of WarwickWellesbourneWarwickCV35 9EFUK

54. Total Defra project costs £ 569,007(agreed fixed price)

5. Project: start date................ 01 April 2004

end date................. 31 March 2008

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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.Background to HH3504SPO

The UK horticultural and agricultural industries rely on large inputs of phosphate (Pi) fertilisers to maintain crop yields and quality. However, the use of non-renewable, chemical Pi fertilisers is unsustainable, and the alternatives to chemical Pi-fertilisers must be identified as an immediate priority. Preliminary observations indicate that a natural waste-product, struvite [(NH4)Mg(PO4)·6(H2O)], could provide an alternative to chemical Pi fertilisers for crop production. Struvite precipitates out of sewage sludge and can be reclaimed from animal wastes. Its disposal to landfill is expensive, and raises the risk of local pollution. Thus, the use of struvite as a fertiliser is an attractive proposition. The first aim of this project is to assess the potential of struvite as a Pi fertiliser for potatoes and to compare the effectiveness of struvite with a chemical Pi fertiliser, triple super phosphate (TSP), in field trials. Excessive Pi fertiliser applications are also costly, and can lead to unnecessary pollution. Inefficient Pi fertilisation is a particular problem for the potato crop. Often more Pi is applied than is required because chemical assays of soil and plant phosphorus (P) are unreliable. Consequently, a more sustainable use of Pi fertilisers is required. Since most plants have a natural ability to acclimate to growth under low P conditions, and this acclimation is affected through changes in the expression of specific genes, there is great interest in identifying these genes and the processes they influence. Modern molecular biological techniques are being used to identify these genes. The genes that respond rapidly and specifically to P deficiency could be used as indicators of crop P deficiency. The concept of exploiting knowledge of changes in plant gene expression that occur under P starvation, could better inform Pi fertiliser applications. The second aim of this project is to develop an oligonucleotide microarray ("Potato Chip") to monitor the expression of diagnostic genes in the youngest fully expanded leaves of potatoes and, thereby, deduce the P status of the potato crop. In practice, these Potato Chips may become a management tool for precision agriculture. They will allow farmers to monitor the immediate physiological P status of their crops in order to optimise the application of Pi fertilisers.The suitability of struvite as an alternative to chemical Pi fertilisers was investigated in the potato crop under field conditions. Analysis of data from plants harvested at tuber initiation revealed that plants supplied with Pi in the form of struvite had higher tissue dry weights and tissue nitrogen, P and magnesium (Mg) concentrations compared to plants supplied with Pi in the form of TSP. However, at commercial maturity, the final harvest showed that plots supplied with Pi in the form of TSP had similar commercial yields to plots supplied with Pi in the form of struvite. A slight depression in yield for some plots supplied with Pi in the form of struvite might be attributed to a potential potassium deficiency observed in plants grown on these plots. Since struvite also contains Mg, the additional Mg may affect the availability of other elements in the soil or the plants ability to take up potassium from the soil. However,

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the potential for struvite as an alternative to chemical Pi fertilisers is still realistic based on these data. Further research must address whether any potassium deficiency might be remedied, using alternative sources of struvite or different agronomic practices. There is also a need to confirm the effects of struvite are robust under different soil and climatic conditions.

The potential for struvite as a renewable source of Pi for agriculture is great. In 2007, the agricultural industry in Great Britain (GB) used approximately 229,000 tonnes of P2O5 (Defra, 2007). This equates to 99,844 tonnes of P. A recent survey of the sources of P entering the surface waters of GB, estimated that 44,000 tonnes of P enters GB surface waters from sewage treatment works annually (White and Hammond, 2006). If all this P was captured as struvite at the sewage treatment works, struvite could potentially supply 44% of GB fertiliser requirements. This would also represent a local source of Pi fertiliser, and could result in a reduction in our reliance on imported Pi fertilisers. To achieve these rates of recovery and use of struvite, additional work on the efficiency and scale with which struvite is recovered from sewage is required. More in depth assessments of struvite as a product are also required, including the chemical consistency of struvite recovered from sewage and the level of biological and chemical contaminants potentially present in struvite. Agronomically, more field trials under different soil and climatic conditions and evaluation of methods for spreading struvite in the field are required.

Develop a diagnostic microarray to monitor the P status of the potato crop

Phosphorus starvation in plants initiates a myriad of transcriptional, biochemical and physiological responses that serve either to enhance the plant’s ability to acquire P from the soil or improve the efficiency with which plants utilise P internally. Our knowledge of how plants sense their P status and initiate responses to P starvation is increasing rapidly, although much still remains to be discovered. It is probable that plants can detect both whole plant P status, enabling efficient use of P internally, and local variations in P availability, enabling the proliferation of roots in P rich patches. One important aspect of this improved understanding will be the ability to identify plants that are P deficient through changes in their gene expression, using biosensor plants or diagnostic microarrays. Candidate genes that can differentiate P deficient and P replete plants must 1) be specific to P deficiency responses, 2) become active rapidly to allow detection and remediation of P deficiency symptoms and 3) be expressed in an easily accessible tissue i.e. leaf tissue.

Initially, a literature review and meta-analysis of transcriptional studies was undertaken to identify genes consistently and specifically up regulated in plants in response to P deficiency (Objective 02). A total of 86 genes were identified that were up regulated in transcriptional profiling studies of P deficient Arabidopsis plants. To identify genes from potato, which respond specifically to P deficiency, a custom potato microarray was designed and built and used to monitor the expression of genes in the diagnostic leaves of potato plants subjected to P deficiency (Objective 03 and 04). A total of 1,659 genes were identified as being differentially expressed in potato leaves in response to P deficiency. The identities of these genes were consistent with those identified in Objective 02 that are involved in re-routeing C metabolism, alternative lipid metabolism and genes with phosphatase activity. These data were successfully used to predict the P status of diagnostic leaf samples taken from field grown potatoes (Objective 05). A support vector machine algorithm was used to define 200 diagnostic genes and then to classify samples as being P deficient or P replete.

This demonstrates the ability of genetic diagnostic markers for classifying the physiological status of crop plants. The ability to diagnose P deficiency, based on levels of gene expression, has the potential to more accurately define the P requirements of a crop plant, enabling more precise management of Pi fertiliser applications required to obtain optimal growth. This could ultimately optimise fertiliser applications, minimising the potential of excess fertilisers polluting surface waters. Further testing of these genetic diagnostic markers is now required in larger field trials and in crops compromised with different biotic and abiotic stresses.

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

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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).

*Note, the project management of HH3504SPO has changed during the lifetime of the project. Initially, Philip White was project manager. Following Philip’s appointment to Scottish Crops Research Institute in May 2006, the project management transferred to John Hammond. Philip has continued to make substantial intellectual and practical inputs to HH3504SPO since his departure, through academic collaborations with John Hammond and through formal consultancies agreed with Warwick HRI.

8.1 Scientific background to HH3504SPO

The UK horticultural and agricultural industries rely on large inputs of phosphate (Pi) fertilisers to maintain crop yields and quality. However, the use of non-renewable, chemical Pi fertilisers is unsustainable, and the alternatives to chemical Pi-fertilisers must be identified as an immediate priority. Preliminary observations indicate that a natural waste-product, struvite [(NH4)Mg(PO4)·6(H2O)], could provide an alternative to chemical Pi fertilisers for crop production. Struvite precipitates out of sewage sludge and can be reclaimed from animal wastes. Its disposal to landfill is expensive, and raises the risk of local pollution. Thus, the use of struvite as a fertiliser is an attractive proposition. The first aim of this project is to assess the potential of struvite as a Pi fertiliser for potatoes and to compare the effectiveness of struvite with a chemical Pi fertiliser, triple super phosphate (TSP), in field trials on P gradients (Defra soil P indices between 2/3 and 9) established at Warwick HRI.

Excessive Pi fertiliser applications are also costly, and can lead to unnecessary pollution. Inefficient Pi fertilisation is a particular problem for the potato crop, which utilises little of the Pi fertiliser applied (Defra, 2000). Often more Pi is applied than is required because chemical assays of soil and plant phosphorus (P) are unreliable. Consequently, a more sustainable use of Pi fertilisers is required. Since most plants have a natural ability to acclimate to growth under low P conditions, and this acclimation is affected through changes in the expression of specific genes, there is great interest in identifying these genes and the processes they influence. Modern molecular biological techniques are being used to dissect the genetics underlying these acclimatory mechanisms (Hammond et al., 2003, 2004ab; Wu et al., 2003; Franco-Zorrilla et al., 2005; Misson et al., 2005; Amtmann et al., 2006; Hermans et al., 2006; Jain et al., 2007; Karthikeyan et al., 2007; Morcuende et al., 2007; Müller et al., 2007; Hammond and White 2008a; White and Hammond 2008). The identification of genes influencing P acquisition and use efficiency can then be used to assist traditional breeding programs, or to modify the crops genetically. The development of crops efficient in the use and acquisition of P will not only serve to reduce Pi fertiliser inputs, but may also benefit farmers in developing countries who cannot afford expensive Pi fertilisers (Frossard et al., 2000; Vance 2001; Lynch 2007). An alternative purpose for identifying genes that respond rapidly and specifically to P deficiency is to use them as indicators of P deficiency. The concept of exploiting knowledge of changes in plant gene expression that occur under P starvation, could better inform Pi fertiliser applications. These technologies provide an insight into the immediate physiological P requirement of the crop. The second aim of this project is to develop an oligonucleotide microarray ("Potato Chip") to monitor the expression of diagnostic genes in the youngest fully expanded leaves of potatoes and, thereby, deduce the P status of the potato crop. In practice, these Potato Chips may become a management tool for precision agriculture. They will allow farmers to monitor the immediate physiological P status of their crops in order to optimise the application of Pi fertilisers.

8.2 Policy background to HH3504SPO

Excessive use of Pi fertiliser causes environmental problems, with 12,800 tonnes of P being lost to UK waters from agriculture annually (White and Hammond, 2006).This is important in developed countries, where agriculture relies on large inputs of Pi fertilisers, a non-renewable resource. In Europe, massive net imports of Pi fertilisers (2.5 Mt in 2005, FAO, 2007) had previously met this demand, but have recently become compromised by limited availability on world markets. This has resulted rapid price increases for Pi fertilisers - prices have doubled in the last six months. Thus, future sustainable agriculture will depend on restricted use of inorganic Pi fertilisers and the use of renewable sources of Pi fertilisers through precision agriculture, combined with growing crops with

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improved abilities to acquire and utilise P more efficiently. Reducing P pollution to UK waters will also create an improved living environment, encouraging recreation and tourism, contributing to the viability of rural businesses.

In 2004, the primary Defra policy objective underpinning HH3504SPO (HH35 ROAME A) was to support the horticultural and potato industry in reducing inorganic fertiliser inputs in order to protect and improve the environment, to preserve biodiversity, to promote a sustainable supply of high-value crops to the food chain, and to preserve natural resources. Currently, HH35 policy objectives have been superseded by SID1 WQ01 objectives, which seek to minimise the adverse impacts of UK agriculture on water quality. HH3504SPO delivers the WQ01 scientific objective, to mitigate transportation of pollutants into watercourses, notably the management of fertiliser nutrient additions to mitigate losses to water systems. HH3504SPO delivers to these by (1) testing a renewable source of Pi (struvite) for fertilising crops, thus reducing our reliance on non-renewable sources of Pi and informing policy on the environmental and agronomic use of struvite and (2) developing new strategies (potato chips) to maximise the efficient use of Pi fertilisers for plant growth, while minimising impact on the environment. HH3504SPO also delivers to other Defra activities including the Water Quality Division’s interests in the Water Framework Directive and the activities of the Nutrient Management Unit.

8.3 Aims and objectives

Aim 1 - Assess the potential of struvite as a phosphate fertiliser for potatoes

Objective 01 To perform three field trials to assess the potential of struvite as an alternative to inorganic Pi fertilisers (within 40 months).

Aim 2 - Develop a diagnostic microarray to monitor the P status of the potato crop

Objective 02 To shortlist P-responsive genes in leaves of Arabidopsis thaliana (within 8 months).Objective 03 To shortlist sequenced transcripts of between 20 and 50 P-responsive genes expressed in

potato leaves (within 23 months).Objective 04 To design, manufacture and test a prototype Potato Chip (within 30 months).Objective 05 To produce and test an alpha-design Potato Chip (within 48 months).

8.4 Assess the potential of struvite as a phosphate fertiliser for potatoes

8.4.1 Introduction

Struvite [(NH4)Mg(PO4)·6(H2O)] is a natural waste product. Preliminary observations indicated that struvite may be a good alternative Pi (nitrogen and magnesium) fertiliser for crop production (Johnston and Richards, 2003). Struvite precipitates out of sewerage sludge and animal waste, and can build up in sewers and in sewage treatment works. This causes operational difficulties and decreased efficiency (Jaffer et al., 2002). The physical removal and disposal to landfill of crystallised struvite is expensive and unsustainable. Therefore, the use of struvite as an alternative Pi fertiliser is an attractive proposition. In addition, struvite can also be recovered from animal wastes, principally pig slurry, but also chicken litter (Battistoni et al., 1997; Greaves et al., 1999). Because conventional disposal of untreated animal wastes increases the risk of pollution and because such practices are becoming legally restricted, alternative disposal routes for struvite must be considered. Since it may be economical to recover struvite from both industrial and agricultural sources for use as an alternative Pi fertiliser, this project investigated the potential of using struvite as a Pi fertiliser for potato production.

8.4.2 Materials and methods

8.4.2.1 Plant materialSeed potatoes (Solanum tuberosum var. Kennebec) were obtained from Higgins Agriculture Ltd. (Finningley, Doncaster, UK). Seed tubers prior to planting had a mean dry weight of 29.03 g plant -1 (±1.99 SEM). Seed tubers were also analysed for elemental concentrations to provide background data (data not shown).

8.4.2.3 StruviteThree batches (500kg each) of chemically synthesised struvite (Budit 370) were obtained from Budenheim Ibérica (Spain). Synthesised struvite was used due to the large quantities required for a field trial. The availability of N from synthesised struvite may differ from recovered struvite, where it may be present in more organic forms, which will require mineralisation before becoming available to the crop. The synthetic struvite was a very light, fine white powder. Chemical analysis of the struvite showed it to be a 40:60 mixture of NH 4MgPO4·6H2O : NH4MgPO4·H2O, with a P content of 13.8%.

8.4.2.3 Experimental design and cultivations

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Two sets of P-fertiliser gradients were established on a field site of low P-status at Wharf Ground, Warwick-HRI, Wellesbourne (latitude 52°12′31″ N, longitude 01°36′38″ W, 48.8 m above sea level). This soil is a sandy loam of the Wick series in the English classification (Whitfield, 1973). The field had not received Pi and K fertilisers for about 20 years, but was regularly cropped during that period. One set of gradients was established using triple super-phosphate (TSP) and the other was established using struvite as the source of Pi. Each set of gradients consisted of three independent gradients, each containing eight plots. The soil P index of each plot was then adjusted by the addition of either TSP or struvite, to give a range of Defra soil P indices from three to nine. Soil samples from each plot were analysed before and after establishment of the gradients to ensure the correct amount of Pi was applied. Soil samples were also taken and analysed before and after each experiment to determine soil nutrient status. Nitrogen and potassium fertiliser applications were made based on soil analysis results and RB209 recommendations for a long haulm longevity potato crop.

Potatoes were grown on the gradients over three years (2004-2006). Seed potatoes were planted on the 31 March 2004, 13 April 2005 and 12 April 2006. Potatoes were subsequently cultivated according to best agronomic practice and treated with irrigation and pesticides when appropriate. Shoot, root and tuber tissues from three plants per plot were sampled at tuber initiation, indicated by flowering, on the 24 June 2004, 21 June 2005, and 29 June 2006 and tubers were sampled at commercial maturity on the 28 September 2004, 03 October 2005 and 05 October 2006. At each harvest, sample fresh weights (FW) were recorded immediately, and sample dry weights (DW) after conventional oven-drying at 80 ºC for 72 h. Dried samples were subsequently milled. Total shoot Ca, Cu, Fe, K, Mg, Mn, Na, P, and Zn concentrations were determined using the micro Kjeldahl method, c. 0.1 g subsample of dried plant material was digested for 1 h, following the addition of 1 mL of H 2O2 and 2 mL of a H2SO4/Se catalyst (Bradstreet, 1965). Inductively-coupled plasma emission spectrometry (JY Ultima 2, Jobin Yvon Ltd., Stanmore, Middlesex, UK) was used to determine elemental tissue concentrations. To determine tissue C and N concentrations, an aliquot of dried tissue sample was loaded directly into a combustion analyzer (CN 2000, LECO UK, Stockport, Cheshire, UK) and analyzed for percentage of C and N via an internal thermal conductivity detector. At commercial maturity tubers were graded into 3 size grades; <40mm, 40 to 65mm and >65mm. The weights of each grade size were recorded.

8.4.2.4 Data analysisAll data were analysed using a two-way ANOVA (GenStat 9 th Ed., VSN International Ltd, UK) to determine the effects of the source of Pi (treatment) and the level at which Pi was supplied (level) on the potato yield and tissue elemental composition.

8.4.3 Results and discussion

To monitor the crop during growth, shoot, root, and tuber tissues were harvested from three plants per plot. Analysis of data from samples collected at tuber initiation show, that with the exception of boron, there was a significant (P<0.05) effect of trial year on all traits measured at tuber initiation. This highlights the significant influence of environmental factors on the availability of nutrients to potato plants and their subsequent growth. At tuber initiation, there was a significant effect of soil P index on shoot dry weight, with shoot dry weights increasing with increasing soil P index for plants supplied with TSP or struvite, however there was no significant difference between the two treatments (Figure 1A). The soil P index had a significant effect on the shoot concentrations of N, P, K, Ca, Mg, B, Cu, Mn and Zn. Shoot P concentrations increased significantly with increasing soil P index for plants supplied with struvite or TSP (Figure 1B). Both shoot N and Mg concentration increased significantly with increasing soil P index in plants supplied with struvite, but not in plants supplied with TSP, as a consequence of the additional Mg and N in struvite (Figure 1C, F). The shoot K and Ca concentrations both decrease significantly with increasing soil P index in plants supplied with struvite, but not in plants supplied with TSP. This might be a consequence of the additional Mg supplied with the struvite, which may act to reduce the availability of these cations in the soil or reduce the ability of the plant roots to take them up. Further research into this phenomenon is required with additional investigation on different soil types.

Data collected from samples taken at commercial maturity from the three trial years show there was no significant (P<0.05) difference in the commercial yield between plots supplied with TSP and plots supplied with struvite as their source of Pi (Figure 2A). This suggests that struvite is capable of supplying Pi to the potato crop under agronomic conditions and enables the potato crop to produce commercial yields similar to plants supplied with a commercial inorganic Pi fertiliser. However, these data should be treated with caution, given that 1) the occasion to occasion variation was significant and commercial yields in some plots were not comparable in all years and 2) these data are restricted to one field trial site, and it is likely that soil type and irrigation practices could have a significant impact on the availability of Pi supplied by struvite. Both sources of Pi elicited a significant (P<0.05) response in commercial yield in response to the amount of Pi supplied. Tuber yields from potatoes supplied with struvite increased from a minimum of 37.6 t ha -1 at a soil P index of 3 to 45.0 t ha -1 at a soil P index of 8. Tuber yields from potatoes supplied with TSP increased from a minimum of 37.4 t ha -1 at a soil P index of 3 to 47.3 t ha-1

at a soil P index of 8 (Figure 2A). Following harvest of the tuber, the tubers were graded to establish if there was any effect of Pi source or soil P index on tuber size (Figure 3). There was no significant (P<0.05) effect on the weights of different grades attributed to the source of Pi supplied to the plants. There was a significant effect of

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soil P index on the largest grade size (tubers >65mm), with more tubers allocated to this grade with increasing soil P index.

The effect of soil P index had a significant effect (P<0.05) on tuber P concentration with tuber P concentration increasing with soil P index for both treatments (Figure 2B). There was a significant effect of soil P index (P<0.05) on tuber Mg and N concentrations for plants supplied with struvite (Figure 2C, F). Tuber K concentration was consistently significantly higher in tubers from potato plants supplied with TSP compared to tubers from potato plants supplied with struvite (Figure 2D). Tuber Ca concentrations decreased with increasing soil P index for plants supplied with struvite, but did not change greatly with soil P index in plants supplied with TSP (Figure 2E).

Figure 1. Average potato shoot dry weights (A), shoot P concentration (B), shoot Mg concentration (C), shoot K concentration (D), shoot Ca concentration (E), and shoot N concentration (F), at tuber initiation for plants supplied with either struvite (black bars) or TSP (white bars) as the source of phosphate. Potatoes were grown under field conditions at Warwick HRI, Wellesbourne UK over three years (2004-2006). Error bar represents least significant differences of means (5% level) with n = 9 (3 plots per treatment x data from 3 experiments performed over 3 years).

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Figure 2. Average commercial yield of potato tubers (A), tuber P concentration (B), tuber Mg concentration (C), tuber K concentration (D), tuber N concentration (E), and tuber Ca concentration (F) at commercial maturity for plants supplied with either struvite (black bars) or TSP (white bars) as the source of phosphate. Potatoes were grown under field conditions at Warwick HRI, Wellesbourne UK over three years (2004-2006). Error bar represents least significant differences of means (5% level) with n = 9 (3 plots per treatment x data from 3 experiments performed over 3 years).

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Figure 3. Average grade weights of potato tubers that were <40mm (black), between 40 and 65mm (light grey) or >65mm (dark grey) in size, from plants supplied with either struvite (A) or TSP (B) as the source of phosphate. Potatoes were grown under field conditions at Warwick HRI, Wellesbourne UK over three years (2004-2006). n = 9 (3 plots per treatment x data from 3 experiments performed over 3 years).

8.4.5 Conclusions

The suitability of struvite as an alternative to chemical Pi fertilisers was investigated in the potato crop under field conditions. Analysis of data from plants harvested at tuber initiation revealed that plants supplied with Pi in the form of struvite had higher tissue dry weights and tissue N, P and Mg concentrations compared to plants supplied with Pi in the form of TSP (Figure 1). However, at commercial maturity, the final harvest showed that plots supplied with Pi in the form of TSP had similar commercial yields compared to plots supplied with Pi in the form of struvite (Figure 2). A slight depression in yield for some plots supplied with Pi in the form of struvite might be attributed to a potential potassium deficiency observed in plants grown on these plots. The potential for struvite as an alternative to chemical Pi fertilisers is still realistic based on these data. Further research must address whether any potassium deficiency might be remedied, using alternative sources of struvite or different agronomic practices. There is also a need to confirm the effects of struvite are robust under different soil and climatic conditions.

The potential for struvite as a renewable source of Pi for agriculture is great. In 2007, the agricultural industry in Great Britain (GB) used approximately 229,000 tonnes of P2O5 (Defra, 2007). This equates to 99,844 tonnes of P. A recent survey of the sources of P entering the surface waters of GB, estimated that 44,000 tonnes of P enters GB surface waters from sewage treatment works annually (White and Hammond, 2006). If all this P was captured as struvite at the sewage treatment works, struvite could potentially supply 44% of GB fertiliser requirements. This would also represent a local source of Pi fertiliser, and could result in a reduction in our reliance on imported Pi fertilisers. To achieve these rates of recovery and use of struvite, additional work on the efficiency and scale with which struvite is recovered from sewage is required. More in depth assessments of struvite as a product are also required, including the chemical consistency of struvite recovered from sewage and the level of biological and chemical contaminants potentially present in struvite. Agronomically, more field trials under different soil and climatic conditions and evaluation of methods for spreading struvite in the field are required.

8.5 Develop a diagnostic microarray to monitor the P status of the potato crop

8.5.1 Introduction

Phosphorus starvation in plants initiates a myriad of transcriptional, biochemical and physiological responses that serve either to enhance the plant’s ability to acquire P from the soil or improve the efficiency with which plants utilise P internally (Vance et al., 2003; Hammond et al., 2004a; Jain et al., 2007; White and Hammond 2008). Our knowledge of how plants sense their P status and initiate responses to P starvation is increasing rapidly, although much still remains to be discovered. It is probable that plants can detect both whole plant P status, enabling efficient use of P internally, and local variations in P availability, enabling the proliferation of roots in P rich patches (Williamson et al., 2001; Forde and Lorenzo, 2001; Amtmann et al., 2006). One important aspect of this improved understanding will be the ability to identify plants that are P deficient through changes in their gene expression, using biosensor plants (Hammond et al., 2003) or diagnostic microarrays (Hammond and White 2008b). Candidate genes that can differentiate P deficient and P replete plants must 1) be specific to P deficiency responses, 2) become active rapidly to allow detection and remediation of P deficiency symptoms and 3) be expressed in an easily accessible tissue i.e. leaf tissue.

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To utilise existing knowledge for the development of diagnostic markers for P deficiency in the potato crop, a literature review was undertaken of the transcriptional responses of plants to P deficiency (Objective 02; Hammond et al., 2004a), which has been updated and summarised here.

8.5.1.1 Signalling P deficiencyA complex series of signalling cascades is emerging that control plant responses to P starvation. These include many transcription factors. The first transcription factor implicated in regulating plant P starvation responses was PHR1 (Rubio et al., 2001). The PHR1 protein is a MYB transcription factor that binds to an imperfect-palindromic sequence (P1BS; GNATATNC) present in the promoter regions of many genes whose expression responds to P starvation (PSR genes). These include genes encoding transcription factors, protein kinases, Pi transporters, RNases, phosphatases, metabolic enzymes and enzymes involved in the synthesis of sulfolipids and galactolipids (Rubio et al., 2001; Hammond et al., 2004; Franco-Zorrilla et al., 2004; Schünmann et al., 2004; Misson et al., 2005; Hammond and White 2008a). The expression of PHR1 appears to be constitutive, but the PHR1 protein is targeted by a small ubiquitin-like modifier (SUMO) E3 ligase (SIZ1), whose expression is increased by P starvation (Miura et al., 2005). Since the Arabidopsis siz1 mutant constitutively exhibits phenotypic characteristics of P-deficient plants, it is hypothesised that SIZ1 acts as a repressor of plant responses to P starvation (Miura et al., 2005). One target of the PHR1 protein appears to be the microRNA family, miR399 (Bari et al., 2006; Chiou 2007). The expression of miR399 is specifically and rapidly up-regulated by P starvation (Fujii et al., 2005; Bari et al., 2006; Chiou et al., 2006). The target gene for miR399 is an ubiquitin E2 conjugating enzyme, also identified as the gene responsible for the pho2 mutant phenotype (AtUBC24; At2g33770; Sunkar and Zhu 2004; Fujii et al., 2005; Aung et al., 2006; Bari et al., 2006; Chiou et al., 2006) and the expression of AtUBC24 is downregulated during P starvation (Fujii et al., 2005; Bari et al., 2006; Chiou et al., 2006). It is thought that AtUBC24 is a negative regulator of the expression of a subset of P starvation responsive genes, possibly through other intermediary transcription factors (Chiou 2007). Interestingly, there is some sequence similarity between miR399 and the TPSI1/Mt4/At4 family of non-coding transcripts, which allows them to bind to miR399 (Shin et al., 2006; Chiou 2007; Franco-Zorrilla et al., 2007). The expression of the TPSI1/Mt4/At4 family is induced rapidly and specifically in response to P starvation (Liu et al., 1997; Burleigh and Harrison 1999; Martín et al., 2000; Shin et al., 2006), and these non-coding transcripts sequester miR399 and serve to attenuate the miR399-mediated transcriptional responses to P starvation (Franco-Zorrilla et al., 2007). The recent characterisation of the At4 T-DNA knockout mutant suggests that it has a role in the internal redistribution of P from the shoots to the roots (Shin et al., 2006). It has a similar phenotype to the pho2 mutant, which accumulates more P in leaves than wildtype plants (Delhaize and Randall 1995).

The signals that regulate, or are regulated by, these transcriptional cascades and initiate plant P starvation responses, including morphological, biochemical and physiological adaptations, are a topic of current debate. Since it is likely that plants can detect both tissue P status and local variations in soil Pi availability, signalling molecule(s) that initiate plant P starvation responses may be different for local and systemic responses, with the potential for crosstalk between local and systemic signals at the point of action. There is evidence that some of these signalling molecules might share signalling cascades with other stresses. Also the transcript abundance of many transcription factors is low and there expression can be transient. This would make them unsuitable as diagnostic markers for P deficiency. Downstream of these signalling molecules are genes that control specific morphological, biochemical and physiological adaptations to P deficiency that might be more suitable as diagnostic markers for P deficiency.

8.5.1.2 Shoot responses to P starvationPhosphorus is present in many chemical forms in plant cells (Marschner 1995). Some cellular compounds containing P are present at low concentrations or can be diminished and/or replaced with little consequence. It is the P-containing compounds that have unique cellular roles and those that are required in high concentrations by plant cells that define the absolute P requirement of plants (Hammond and White 2008a). The acclimatory responses of plants to P starvation are directed towards maintaining essential cellular functions, either by utilising plant P efficiently or by increasing P acquisition by the root system.

Phosphorus is an essential component of DNA and RNA, in which phosphodiester bridges link the deoxyribonucleotides or ribonucleotides. The requirement for DNA and RNA is greatest in tissues undergoing rapid cell division and/or cell expansion (Ågren 1988; Elser et al., 2000; Niklas 2008). The plant cannot dispense with DNA or RNA and although DNA and RNA concentrations in plant cells can be reduced during P starvation this has a significant affect on plant growth rate (Raven 2008). In addition, P is required as ADP in photosynthesis and respiration, as ATP for energy transfer reactions in, for example, nucleic acid synthesis, metabolism, cytoskeletal rearrangements and membrane transport, as GTP for energy transfer reactions during nucleic acid biosynthesis, as NADPH in biosynthetic reactions and as signalling molecules such as GTP and cAMP. It is possible for a cell to reduce some dependence on ATP by rerouting biochemical pathways and utilizing PPi as an energy substrate (Plaxton and Carswell 1999; Hammond et al., 2004; Hammond and White 2008a), but a finite requirement for ATP cannot be avoided.

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A considerable quantity of cellular P occurs in the many phosphorylated intermediates of metabolic pathways. Phosphorylated compounds occur, for example, in the Calvin cycle, in the photorespiratory pathway, in glycolysis, in the pentose phosphate pathway, in nitrogen and sulphur assimilation, in the pathways of amino acid and nucleotide metabolism, and in pathways leading to the synthesis of polyphenols and lignin (Coruzzi and Last 2000; Dennis and Blakeley 2000; Malkin and Niyogi 2000; Siedow and Day 2000). In addition, where integrated metabolic transformations occur in different cellular compartments, it is often phosphorylated compounds that are transported across membranes.

A reduction in the cytoplasmic concentration of free Pi impacts directly on photosynthesis, glycolysis and respiration (Plaxton and Carswell 1999; Hammond et al., 2004; Hammond and White 2008a), and changes in carbohydrate metabolism are reinforced by transcriptional reprogramming (Hammond et al., 2003, 2005; Wu et al., 2003; Misson et al., 2005; Hermans et al., 2006; Wasaki et al., 2006; Morcuende et al., 2007; Müller et al., 2007). This results in organic acids, starch and sucrose accumulating in leaves of P starved plants (Rao et al., 1990; Cakmak et al., 1994; Ciereszko and Barbachowska 2000; Müller et al., 2004, 2005, 2007; Wissuwa et al., 2005; Hermans et al., 2006; Morcuende et al., 2007). Metabolism is rerouted by employing reactions that do not require Pi or adenylates (Plaxton and Carswell 1999; Vance et al., 2003; Hammond et al., 2004; Hammond and White 2008a) and, under severe P-deficiency, intracellular phosphatases and nucleases are induced that remobilise P from cellular metabolites and nucleic acids (Bariola et al., 1994; Berger et al., 1995; Bosse and Köck 1998; Brinch-Pedersen et al., 2002; Petters et al., 2002; Hammond et al., 2003; Wasaki et al., 2006; Morcuende et al., 2007; Müller et al., 2005, 2007). An increased leaf sucrose concentration also results in the upregulation of transporters delivering organic acids and sucrose to the phloem, which facilitates the movement of these compounds to the root (Gaume et al., 2001; Hermans et al., 2006).

In cell membranes, P occurs in phospholipids (phosphatidyl serine, phosphatidyl ethanolamine, phosphatidyl choline, phosphatidyl inositol and diphosphatidylglycerol), and the intermediate compounds of their biosynthesis (Somerville et al., 2000). In addition to their structural roles, phospholipids serve as substrates for the production of biochemical signals, such as inositol trisphosphate (IP3), diacylglycerol, lysophosphatidyl choline, jasmonate and free headgroups (inositol, choline, ethanolamine, serine). Membrane lipids are required in abundance by photosynthetic tissues and tissue undergoing rapid cell division and/or cell expansion. The thylakoid membrane of the chloroplast is predominantly composed of sulphoquinovosyldiacylglycerol (SQDG), digalatosyldiacyglycerol (DGDG) and monogalatosyldiacyglycerol (MGDG). By using these lipids in chloroplast membranes, plants reduce their requirements for phospholipids. Furthermore, when plants are starved of P, the relative abundance of SQDG, DGDG and MGDG increases in plant membranes, through the upregulation of genes involved in their biosynthesis, thereby contributing to tissue P economy (Essigmann et al., 1998; Härtel et al., 2000; Dörmann and Benning 2002; Andersson et al., 2003, 2005; Jouhet et al., 2004; Benning and Ohta 2005; Kobayashi et al., 2006; Li et al., 2006).

In P-replete plants, over 85% of the cellular Pi is located in the vacuole (Marschner 1995). However, vacuolar Pi concentrations decrease rapidly when plants lack sufficient P, to maintain cytoplasmic Pi concentration in the range 3 to 20 mM (Lee et al., 1990; Schachtman et al., 1998; Mimura 1999). If the P supplied to P-replete plants is reduced to the minimal amount required for optimal plant growth only the P in the inorganic fraction decreases substantially, which reflects the mobilisation of surplus Pi from the vacuole (Marschner 1995). However, when the P supply to plants is decreased from an optimal to a suboptimal level, the P associated with nucleic acids, lipids, small metabolites and inorganic fractions all decrease.

8.5.1.3 Meta-analysis of transcriptional profiling studiesWith advances in microarray technology it is now possible to determine the expression levels of thousands of genes in a sample simultaneously. This technology has been applied to identify genes whose expression changes in response to P deficiency (Hammond et al., 2003, 2004, 2005; Uhde-Stone et al., 2003; Wasaki et al., 2003; Wu et al., 2003; Misson et al., 2005; Morcuende et al., 2007; Müller et al., 2007; Calderon-Vazquez et al., 2008). Several of these studies have used the Arabidopsis Affymetrix GeneChip array platform, enabling a global comparison of gene expression studies. Data were collected from Hammond et al. (2003), Wu et al. (2003), Misson et al. (2005), Morcuende et al. (2007) and Müller et al. (2007) representing genes with higher transcript levels under P deficient conditions compared to P replete control conditions in the leaves of Arabidopsis plants. These data were compared to identify genes whose expression was up regulated by P deficiency represented in at least four out of the five experiments (Table 1). These genes represent genes involved in lipid metabolism, altered C metabolism, nutrient transport, and release of P from metabolites. Since, the expression of these genes increases rapidly and specifically in responses to P deficiency, they may act as good diagnostic indicators of plant P status. To identify orthologs of these genes in potato, which respond specifically to P deficiency (Objective 03), a custom potato microarray was designed and built (Objective 04). This was validated using different tissue samples that have distinct, but characteristic, gene expression profiles. Following the development of this array platform, this project enabled access to an international consortium, the Potato Oligo Chip Initiative (POCI) led by Wageningen University, which developed an oligonucleotide array representing 42,034 potato sequences (Kloosterman et al., 2008). Since this array contained twice as many features, enabling a greater coverage of the transcriptome, this platform was used to identify potato genes that respond specifically to P deficiency. These

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genes were then used as diagnostic markers to predict the P status of potato plants grown under field conditions and supplied with different amounts of P fertiliser (Objective 5).

Table 1. Arabidopsis genes whose expression increases rapidly and specifically in response to P deficiencyAGI locus Gene description GenBank IDAT5G64000 3'(2'),5'-bisphosphate nucleotidase NM_125796AT3G59140 ABC transporter family protein NM_115776AT3G17790 acid phosphatase type 5 (ACP5) NM_112660AT3G03790 ankyrin repeat family protein NM_202484AT1G35720 annexin 1 (ANN1) NM_103274AT3G12500 basic endochitinase NM_112085AT4G36350 calcineurin-like phosphoesterase family protein NM_119798AT1G13750 calcineurin-like phosphoesterase family protein NM_101243AT3G51860 cation exchanger, putative (CAX3) NM_115045AT1G30500 CCAAT-binding transcription factor NM_179402AT4G34200 D-3-phosphoglycerate dehydrogenase NM_119583AT3G11670 digalactosyldiacylglycerol synthase 1 (DGD1) NM_111999AT1G72890 disease resistance protein NM_105947AT1G72070 DNAJ heat shock N-terminal domain-containing protein NM_105865AT1G68740 ERD1/XPR1/SYG1 family protein NM_105547AT3G44520 esterase/lipase/thioesterase family protein NM_114320AT1G08310 esterase/lipase/thioesterase family protein NM_100704AT1G71130 ethylene response factor subfamily B-5 NM_105782AT4G17030 expansin-related NM_117807AT5G40690 expressed protein NM_123434AT4G31240 expressed protein NM_119273AT3G44510 expressed protein NM_114319AT4G37680 expressed protein NM_119931AT3G56040 expressed protein NM_115462AT1G70900 expressed protein NM_105758AT1G17830 expressed protein NM_101646AT1G67920 expressed protein NM_105462AT5G20790 expressed protein NM_122086AT1G67600 expressed protein NM_105427AT1G17710 expressed protein NM_101633AT2G04460 expressed protein NM_126479AT1G73010 expressed protein NM_105959AT2G34810 FAD-binding domain-containing protein NM_129034AT3G12350 F-box family protein NM_112070AT2G29460 glutathione S-transferase NM_128500AT3G47420 glycerol-3-phosphate transporter NM_114610AT3G02040 glycerophosphoryl diester phosphodiesterase family protein NM_111070AT1G74210 glycerophosphoryl diester phosphodiesterase family protein NM_106081AT3G18080 glycosyl hydrolase family 1 protein NM_112690AT4G19810 glycosyl hydrolase family 18 protein NM_118101AT2G38740 haloacid dehalogenase-like hydrolase family protein NM_129431AT5G43350 inorganic phosphate transporter (PHT1) NM_123701AT5G43370 inorganic phosphate transporter (PHT2) NM_123703AT2G32830 inorganic phosphate transporter (PHT5) NM_128843AT4G01480 inorganic pyrophosphatase, putative (soluble) NM_116378AT3G53620 inorganic pyrophosphatase, putative (soluble) NM_115222AT3G02870 inositol-1(or 4)-monophosphatase, putative NM_111155AT2G27190 iron(III)-zinc(II) purple acid phosphatase (PAP12) NM_128277AT2G34210 KOW domain-containing transcription factor NM_128972AT3G03310 lecithin:cholesterol acyltransferase family protein NM_111202AT4G00500 lipase class 3 family protein NM_116274AT1G23120 major latex protein-related NM_102160AT3G48850 mitochondrial phosphate transporter NM_114744AT5G09470 mitochondrial substrate carrier family protein NM_120984AT5G51050 mitochondrial substrate carrier family protein NM_124484

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Table 1. Arabidopsis genes whose expression increases rapidly and specifically in response to P deficiencyAGI locus Gene description GenBank IDAT2G11810 monogalactosyldiacylglycerol synthase (MGDG) NM_126865AT5G20410 monogalactosyldiacylglycerol synthase (MGD2) NM_122048AT1G56650 myb family transcription factor (MYB75) NM_104541AT5G61510 NADP-dependent oxidoreductase NM_125544AT5G63130 octicosapeptide/Phox/Bem1p (PB1) domain-containing protein NM_125707AT5G20400 oxidoreductase, 2OG-Fe(II) oxygenase family protein NM_122047AT2G38940 phosphate transporter (PT2) NM_129452AT3G54700 phosphate transporter, putative NM_115327AT3G14940 phosphoenolpyruvate carboxylase NM_112356AT1G08650 phosphoenolpyruvate carboxylase kinase NM_100738AT1G22170 phosphoglycerate/bisphosphoglycerate mutase family protein NM_102067AT2G17280 phosphoglycerate/bisphosphoglycerate mutase family protein NM_127283AT3G05630 phospholipase D, putative (PLDP2) NM_111436AT2G16430 purple acid phosphatase (PAP10) NM_127196AT2G18130 purple acid phosphatase (PAP11) NM_127370AT5G63680 pyruvate kinase NM_125763AT4G35750 Rho-GTPase-activating protein-related NM_119741AT4G21470 riboflavin kinase/FAD synthetase family protein NM_118267AT2G02990 ribonuclease 1 (RNS1) NM_126351AT3G08720 serine/threonine protein kinase (PK19) NM_111706AT3G10420 sporulation protein-related NM_180222AT2G26660 SPX (SYG1/Pho81/XPR1) domain-containing protein NM_128223AT5G20150 SPX (SYG1/Pho81/XPR1) domain-containing protein NM_122022AT1G73220 sugar transporter family protein NM_105981AT4G33030 sulfolipid biosynthesis protein (SQD1) NM_119457AT5G01220 sulfolipid synthase (SQD2) NM_120200AT3G52190 transducin family protein / WD-40 repeat family protein NM_115079AT1G05000 tyrosine specific protein phosphatase NM_100379AT4G03960 tyrosine specific protein phosphatase family protein NM_116634AT2G36970 UDP-glucosyl transferase family protein NM_129253AT3G11230 yippee family protein NM_111958Genes are those whose expression was greater in the leaves of P deficient Arabidopsis plants compared to the leaves of P replete Arabidopsis plants as defined by at least four of the following studies; Hammond et al. (2003), Wu et al. (2003), Misson et al. (2005), Morcuende et al. (2007) and Müller et al. (2007).

8.5.2 Materials and Methods

8.5.2.1 Plant material and growth conditions for array validationSolanum tuberosum var. Kennebec seed tubers (Higgins Agriculture, Doncaster, UK) were planted into field at Warwick HRI, Wellesbourne, Warwickshire, UK (latitude 52°12′31″ N, longitude 01°36′38″ W, 48.8 m above sea level). Seed tubers were planted on the 13th April 2005. Potatoes were grown using best agronomic practice. Irrigation was supplied using oscillating lines when required and the field received 185 kg ha -1 N, supplied as NH4NO3, 325 kg ha-1 K2O, supplied as K2SO4 (also supplying 292 kg ha-1 SO3) and 180 kg ha-1 P2O5, supplied as triple-super-phosphate prior to planting. Plants were harvested on the 7th July 2005, 85 days after sowing. Three plants were harvested at random from within the field for each biological replicate. Three biological replicates were harvested in total at the midpoint of the photoperiod i.e. midday. Plants were separated in to the youngest fully expanded leaves, taken as the second leaf below the crown of the plant, fruits, roots and tubers. Roots and tubers were washed in the field and blotted dry. Tissues were bulked within each biological replicate and snap frozen in liquid nitrogen in the field. Tissue samples were ground under liquid nitrogen and stored at -80 °C prior to RNA extraction.

8.5.2.2 Plant material and growth conditions for monitoring the P response of potato plantsSolanum tuberosum var. Kennebec micro-plants (Higgins Agriculture, Doncaster, UK) were initially transferred to rockwool plugs (3.5 x 3.5 x 4 cm; Grodan, Hedehusene, Denmark) and watered with tap water in plastic trays. The plastic trays were covered with plastic film to maintain humidity, and placed in a weaning room held at 25 °C. Once established, rockwool plugs were transferred to a NFT hydroponic system in the glasshouse described previously (Broadley et al., 2003). The experiments were carried out between May 2003 and June 2004 in a 40 m2 glasshouse compartment at Wellesbourne, UK (latitude 52° 12′ 18″ N, longitude 1° 36′ 00″ W, 48.8 m above

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sea level). The glasshouse was set to maintain temperatures of 20 °C by day and 15 °C at night using automatic vents and supplementary heating. The NFT system comprised 12 individual gullies. The gullies were spaced 0.26 m apart (centre-to-centre) in two groups of six within the same glasshouse compartment. Each gully was connected to one of two water-storage tanks that each contained 200 L of deionised water to which mineral nutrient salts were added. The nutrient solutions contained 2 mM Ca(NO3)2, 2 mM NH4NO3, 0.75 mM MgSO4, 0.5 mM KOH, 0.25 mM KH2PO4, 0.1 mM FeNaEDTA, 30 µM H3BO3, 25 µM CaCl2, 10 µM MnSO4, 3 µM CuSO4, 1 µM ZnSO4, 0.5 µM Na2MoO4. Nutrient solutions were adjusted daily to pH 6, using H2SO4, and solutions were replaced completely twice a week. Samples of nutrient solutions were analysed for elemental composition before and after nutrient solutions were changed. To induce P deficiency, the P supplied as KH2PO4, was replaced with K2SO4 to supply the same concentration of K.

Once the plants were established in the NFT system, the nutrient solution supplying half of the plant was replaced with one containing no P, whilst the nutrient solution supplying the remaining plants was maintained as a full nutrient solution. Shoots of plants were harvested destructively during the course of the experiment. At each harvest, diagnostic leaves, defined as the youngest fully expanded leaves, taken as the second leaf below the crown of the plant, from three plants supplied with a full nutrient solution and three plants supplied with a nutrient solution containing no P were sampled and snap frozen in liquid nitrogen prior to RNA extraction. The remaining shoot tissue was harvested and fresh weights (FW) of leaf and stem tissue recorded. Sample dry weights (DW) were recorded after conventional oven-drying at 80 ºC for 72 h. Dried samples were subsequently milled and analysed for elemental tissue concentrations as described previously (Section 8.4.2.3). As plants were sampled during the experiment, the resulting gaps in the PVC strips were immediately covered to maintain humidity and to reduce algal growth in the gullies. Potato plants supplied with a nutrient solution containing no P were grown for 28 days, after which P was re-supplied, and the plants grown for a further seven days.

All data were analysed using (GenStat 9th Ed., VSN International Ltd, UK) to determine the effects of the withdrawal of P over time on shoot biomass and tissue elemental composition. Data were log transformed and summarised using REML analysis, with a Fixed model as days after P withdrawal*treatment and a random model of Block/Row/Plant. Predicted means were back transformed and standard errors were back transformed and converted to 95% confidence intervals.

8.5.2.2 Plant material and growth conditions for test samplesTest samples were taken from experimental field plots of potatoes growing as part of Objective 01. Diagnostic leaves, defined as the youngest fully expanded leaves, taken as the second leaf below the crown of the plant, were taken from five plants on plots that had received P fertiliser and from plots that had received no P fertiliser. Samples were taken during tuber initiation and snap frozen in liquid nitrogen. A total of 30 independent samples were taken, 15 from plots that had received P fertiliser and 15 from plots that had received no P fertiliser.

8.5.2.2 RNA extractionRNA was extracted from tissue samples using methods described by Hammond et al., (2006). To each sample, 1 mL of TRIzol reagent was added, and total RNA was subsequently extracted according to the manufacturer’s instructions (Invitrogen, Paisley, UK), with the following modifications: (i) after homogenisation with the TRIzol reagent, the samples were centrifuged to remove any remaining plant material, and the supernatant was then transferred to a clean Eppendorf tube and, (ii) to aid precipitation of RNA from the aqueous phase, 0.25 mL of isopropanol and 0.25 mL of 1.2 M NaCl solution containing 0.8 M sodium citrate were added. This procedure precipitated the RNA whilst maintaining the proteoglycans and polysaccharides in a soluble form. Extracted total RNA was then purified using the ‘RNA Cleanup’ protocol for RNeasy columns with on-column DNase digestion to remove residual chromosomal DNA (Qiagen, Crawley, West Sussex, UK).

8.5.2.3 Microarray DesignTo monitor the maximum number of transcripts from potato and determine transcriptional differences between the tissue types analysed, custom microarrays, representing over 19,000 unique tentative consensus (TC) sequences from the TIGR Potato Gene Index, were produced. Version 9.0 of the TIGR Potato Gene Index was downloaded and the 70-mer oligonucleotides were obtained. These oligonucleotide sequences were designed using the OligoPicker algorithm (TIGR, http://www.tigr.org/ ; Wang and Seed, 2003) using the following criteria (i) a primary 15-mer contiguous match filter (i.e. every 15-mer in the oligo is unique), (ii) an oligo blast score < 30 (this corresponds to a perfect 15-mer match), (iii) oligo Tm is within 5 °C of the median Tm (calculated based on the GC content of the 70-mers), (iv) oligo does not have a low-complexity region, (v) oligo does not cross-react with rRNA and snRNA filter sequences from the same and related organisms, (vi) oligo does not self-anneal to the cDNA complement, (vii) oligo should be readily accessible for hybridisation and should preferably be designed outside of the region that has a high propensity for secondary structure formation, a Gibb's free-energy threshold > -20 kcal mol-1 is chosen for this purpose, and (viii) the unique oligo is designed from the region that lies within 1000 residues from the 3' end. The 70-mer sequences were then trimmed to 60-mers to enable production of the microarrays using SurePrint technology (Agilent Technologies, Palo Alto, CA, USA). The identities of the potato sequences used to make the microarrays are available in Supplementary Table 1.

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Following the development of this array platform, this project enabled access to an international consortium, the Potato Oligo Chip Initiative (POCI) led by Wageningen University, which developed an Agilent oligonucleotide array representing 42,034 potato sequences (Kloosterman et al., 2008; http://pgrc.ipk-gatersleben.de/poci). This platform was used to identify potato genes that respond specifically to P deficiency and to monitor the expression of diagnostic markers to predict the P status of potato plants grown under field conditions and supplied with different amounts of P fertiliser.

8.5.2.4 Experimental design, hybridisation and scanning of microarraysA common reference model (Yang and Speed, 2002) was used to identify transcripts with significantly different profiles between the different tissue samples. A common reference was generated from bulked leaf tissue from the potato plants. The common reference was labelled with Cyanine 5 fluorescent dye and hybridised to each microarray. RNA samples from youngest fully expanded leaves, fruits, roots and tubers were labelled with Cyanine 3 fluorescent dye. A full dye swap model was used to determine the expression profiles of potato leaves following the withdrawal of P from the nutrient solution. All samples were independently labelled with Cyanine 3 and Cyanine 5 and combined in reciprocal combinations on the array. For test samples, a one-colour model was used with samples labelled with Cyanine 3.

Labelled cRNA samples were generated from RNA samples using the Low RNA Input Fluorescent Linear Amplification Kit according to the manufacturer’s instructions (Agilent Technologies). First, complementary DNA (cDNA) was generated from total RNA, using 3 µg of total RNA and 5 µL of T7 promoter primer. Then cRNA was synthesised from the double-stranded cDNA using T7 RNA polymerase, incorporating Cyanine 3- or Cyanine 5-labelled CTP fluorescent dyes (PerkinElemer Life and Analytical Sciences, Boston, MA, USA). Labelled cRNA samples were cleaned using the ‘RNA Cleanup’ protocol for RNeasy columns (Qiagen) performed at 4 °C and eluted using two 30 µL volumes of nuclease-free H2O. Four independent labelling reactions were performed for the common reference sample and combined into one tube following labelling with Cyanine 5 and sample clean up. Mean dye incorporation for labelled cRNA was 17.02 (± 0.43 SEM) pmol dye µg-1 cRNA.

Hybridisation cocktails were prepared using the In situ Hybridisation Kit according to the manufacturer’s instructions (Agilent Technologies). To each cocktail, between 0.5 and 3 µg of labelled cRNA per sample was used. Hybridisation cocktails were hybridised to the microarrays in a hybridisation oven (Agilent Technologies) at 65 °C for 17 hours. Microarrays were rotated at 4 rpm for the Potato Chip and 10 rpm for the POCI array during the hybridisation procedure to ensure even hybridisation of the sample across the microarray.

Following hybridisation, microarrays were transferred to a slide rack in a staining dish. The slides were washed in staining dishes with magnetic stirring bars to aid washing in (i) 6x SSPE solution containing 0.005 % N-Lauroylsarcosine for 1 min, (ii) 0.06x SSPE solution containing 0.005 % N-Lauroylsarcosine for 1 min, (iii) acetonitrile for 1 min, and (iv) a stabilisation and drying Solution (Agilent Technologies) for 30 s.

Microarrays were scanned on a DNA Microarray Scanner BA (Agilent Technologies). For the Potato Chips, microarrays were scanned with a PMT setting of 50 % and data extracted from the scanned images using the Feature Extraction software package (Agilent Technologies). For the POCI microarrays, the Extended Dynamic Range function was used to scan the microarrays, and data extracted from the scanned images using the Feature Extraction software package. Feature extraction was performed using spatial de-trend algorithm within the software package. The output files from the Feature Extraction software provide several estimates of signal intensities for each probe. For further analysis the ‘processed’ signal values were used. These values have been adjusted for spatial variation across individual arrays, and had been normalised using a global background subtraction and a Lowess normalisation. Microarray scans were checked for quality using data from the Feature Extraction software and distribution of data in GeneSpring GX analysis software (Agilent Technologies). Data not meeting these criteria were discarded and the hybridisations repeated.

8.5.2.5 Microarray data analysisThe processed signal values were imported into GeneSpring GX. Data from individual microarrays were subjected to a Lowess normalisation in which a Lowess curve was fitted to the log-intensity versus log-ratio plot. The Lowess fit at each point was calculated using 35% of the data. This curve was used to adjust the control value for each measurement. If the control channel was lower than 10 then 10 was used instead. Each gene was divided by the median of its measurements in all samples for an experiment. Data from the tissue samples were pre-filtered by removing genes with signal values less than 50, in one quarter of the samples. Data from the P response time course were pre-filtered by 1) removing genes whose raw signal value was less than 50 in five of the seven time points, 2) removing genes flagged as absent and 3) removing genes whose normalised signal value remained between 0.8 and 1.2 at all time points to leave 28,946 genes for further analysis.

To identify significantly differentially expressed genes between treatments an ANOVA with a Benjamini & Hochberg FDR multiple testing correction was used. Gene Ontology terms assigned to genes were analysed using the Gene Ontology Browser in GeneSpring GX. For class prediction, the support vector machine implemented in the Class Prediction tool of GeneSpring GX (Agilent Technologies) was used to classify the data.

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Sets of diagnostic genes were selected using the Golub method with the Polynomial Dot Product (Order 1) kernel function. Different kernel functions and sets of diagnostic genes were changed systematically to optimise the classification of samples.

8.5.3 Results and discussion

To identify genes from potato, which respond specifically to P deficiency (Objective 03), a custom potato microarray was designed and built (Objective 04). This enables the direct identification of potato genes that respond to P deficiency. The ‘Potato Chip’ was designed using available sequence information from the TIGR Potato Gene Index, and manufactured by Agilent Technologies. The Potato Chip contains probes representing 19,226 unique potato sequences and 1,880 control probes for quality control of array manufacture, sample preparation and hybridisation of samples to the Potato Chip.

8.5.3.1 Microarray testingTo test the Potato Chip and validate its ability to monitor changes in gene expression in potato, the arrays were challenged with labelled RNA taken from potato leaves, tubers, roots and fruits. The transcript profiles of these tissues provided distinct groups of genes, which are characteristic for individual tissues, enabling a validation of the Potato Chip array. A total of 3,177 genes were significantly (P<0.01) differentially expressed between the tissue types. Analysis of the replicated experiment identified distinct groups of genes whose expression patterns were characteristic of the individual tissues (Figure 4). For example, the groups of genes differentially expressed in leaf and fruit tissues compared to root and tuber tissues contained significantly (P<0.05) more genes involved in photosynthesis and chlorophyll metabolism than would be expected by chance when compared to the frequency of these genes on the Potato Chip. Similarly, genes differentially expressed in tubers compared to root, leaf and fruit tissues contained significantly more genes involved in carbohydrate metabolism and patatin metabolism (Patatin is a family of glycoproteins that accounts for up to 40% of the total soluble protein in potato tubers) than would be expected by chance when compared to the frequency of these genes on the Potato Chip.

Figure 4. Genes significantly differentially expressed in potato leaf, root, fruit and tuber tissues based on a one-way ANOVA using a Benjamini & Hochberg FDR of 0.01 to correct for multiple testing.

Following the release of the POCI array, the new platform was cross validated with the Potato Chip. Of the 19,226 probes on the Potato Chip, 12,338 shared common annotations and represent the same potato sequences as probes on the POCI array. The same labelled samples used to characterise potato tissue samples were hybridised to the POCI array. Data were first filtered to remove genes with raw signal values less than 50 and then the normalised signal values were compared (Figure 5). All comparisons showed significant correlations between signal values from the Potato Chip and the POCI array (r = 0.78 for root samples; r = 0.72 for fruit samples; r = 0.69 for leaf samples; r = 0.44 for tuber samples). Data were then analysed to identify genes that were significantly (P<0.01) differentially expressed between tissue types using the same criteria used for data obtained from the Potato Chip. A total of 2,936 genes were significantly (P<0.01) differentially expressed between the tissue types. A comparison of the two sets of genes, showed that a significant (P<0.001) number (872) were common to both. Differences between the lists are likely to arise from different oligonucleotides being used to measure the transcript abundance of the same gene and different global gene expression profiles across the microarray that could alter normalisation of the data.

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Figure 5. Comparison of normalised signal values generated from samples taken from potato fruits (A), roots (B), leaves (C) and tubers (D) using the Potato Chip and POCI microarrays. Data were pre-filtered to remove raw data with signal values less than 50. Solid line represents one-to-one relationship between the data.

8.5.3.2 Physiological response of potato plants to P deficiencyTo induce P deficiency symptoms, potato plants were grown under glasshouse conditions using a NFT hydroponic system to control the nutrient status of the plants accurately. The shoot dry weights of plants supplied with nutrient solution containing no P were not significantly different from the shoot dry weights of plants supplied with a full nutrient solution up to 13 days after the withdrawal of P (Figure 6A). The shoot dry weights of plants supplied with nutrient solution containing no P were significantly (P<0.05) lower compared with plants supplied with a full nutrient solution 15, 17 and 24 days after the withdrawal of P. The effect of P withdrawal on the shoot P concentration was rapid (Figure 6B). Shoot P concentrations of plants supplied with nutrient solution containing no P were significantly (P<0.05) less than plants supplied with a full nutrient solution one day after the withdrawal of P from the nutrient solution. This was maintained until three days after the re-supply of P to the nutrient solution, when shoot P concentration of plants supplied with nutrient solution containing no P increased back to a similar P concentration of plants supplied with a full nutrient solution. The shoot P concentration of plants supplied with nutrient solution containing no P continued to increase and was significantly (P<0.05) greater than plants supplied with a full nutrient solution seven days after the re-supply of P to the plants (Figure 6B). The effect of P withdrawal on concentration of other elements in the potato shoot tissue was also monitored (Figure 6D, C). Shoot N concentrations of plants supplied with nutrient solution containing no P were significantly (P<0.05) less than plants supplied with a full nutrient solution 13 days after the withdrawal of P from the nutrient solution and until the end of the experiment. Shoot K concentrations of plants supplied with nutrient solution containing no P were significantly (P<0.05) greater than plants supplied with a full nutrient solution 13 days after the withdrawal of P from the nutrient solution and until the end of the experiment.

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Figure 6. Mean shoot dry weights (A), leaf P concentrations (B), leaf N concentrations (C) and leaf K concentrations of potato plants supplied with a full nutrient solution (closed circles) or supplied with a nutrient solution containing no P (open circles). Plants were grown in an NFT hydroponic system under glass house conditions. P was withdrawn from the nutrient solution supplying half the plants for 28 days before being re-supplied. Data points represent mean ± 95% confidence interval (n=6).

8.5.3.3 Gene expression profiles of potato plants responding to P deficiencyTo identify genes that respond specifically and rapidly to P deficiency, total RNA was extracted from the diagnostic leaves of potato plants grown under glasshouse conditions using a NFT hydroponic system. Total RNA was labelled and hybridised to the POCI arrays to determine the expression levels of 42,034 potato genes. A pre-filtered gene list was used to identify genes whose expression was significantly up or down regulated in at least two of the seven time points. A total of 1,659 genes were significantly (P<0.01) differentially expressed, with 762 genes up regulated by more than 1.5 fold at two of the seven time points and 965 genes down regulated by more than 1.5 fold in two of the seven time points (Supplementary Table 2). Genes identified as being significantly differentially expressed during P deficiency were functionally annotated based on the Gene Ontology (GO) terms assigned to them (Kloosterman et al., 2008; http://pgrc.ipk-gatersleben.de/poci). Of the 1,659 genes, 924 genes had GO terms assigned to them, with the majority having Molecular Function GO terms of catalytic activity of binding (Figure 7). There were significant (P<0.05) over representations of Biological Process GO terms; GO:6793: phosphorus metabolism, GO:6020: myo-inositol metabolism, GO:6040: amino sugar metabolism, GO:272: polysaccharide catabolism, GO:6829: zinc ion transport, GO:42126: nitrate metabolism, GO:16052: carbohydrate catabolism, GO:46149: pigment catabolism, GO:30001: metal ion transport, GO:98: sulphur amino acid catabolism, GO:9693: ethylene biosynthesis, GO:6811: ion transport.

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Figure 7. Gene Ontology molecular function terms for genes identified as being significantly (P<0.01) differentially expressed in the diagnostic leaves of potato plants following the withdrawal of P from the nutrient solution. Of the 1,659 genes, 924 genes had GO terms assigned to them. Data were processed using the Gene Ontology Browser in GeneSpring GX (Agilent Technologies).

Of the 86 genes identified in Objective 02 from the meta-analysis of transcriptional studies of Arabidopsis responses to P deficiency, 34 have common annotations with those up regulated by more than 1.5 fold at two of the seven time points. These include gene encoding a phosphoenolpyruvate carboxylase and a phosphoenolpyruvate carboxylase kinase, which are involved in re-routeing C metabolism to employ reactions that do not require Pi, seven genes involved in alternative lipid metabolism and several genes with phosphatase activity that could release P from internal sources. These genes are good candidates for use as diagnostic markers to identify P deficient potato plants, since they are consistently and specifically expressed under P deficient conditions.

8.5.3.4 Diagnosing P deficiency in field grown potato plantsTo assign the physiological state of a diagnostic potato leaf as coming from a P deficient or P replete potato plant (Objective 05) we have used class prediction algorithms developed for the classification of cancer tumours (Furey et al., 2000). Class prediction is a supervised learning method where an algorithm uses gene expression profiles from samples of known classification to build a rule to predict class of new unknown samples. The process consists of two steps: Firstly, predictor genes are chosen from a training set of samples with known classification. Secondly, a cross-validation process tests the ability of the algorithm to correctly classify a set of test samples.

A support vector machine (SVM) algorithm was used to classify the data, since SVM based classification algorithms have been shown to outperform non-SVM algorithms (Statnikov et al., 2005). The SVM implemented in the Class Prediction tool of GeneSpring GX (Agilent Technologies) was used to classify the data. The training set used to predict diagnostic genes was a modified version of the P response of potato plants data set, in which the two-colour data were treated as one-colour data to allow samples to be classed as being P replete or P deficient, generating 84 samples. Sets of diagnostic genes were selected using the Golub method with the Polynomial Dot Product (Order 1) kernel function and the 84 samples from the P response of potato plants data set used as the training set and the test set. Sets of diagnostic genes containing 25, 50, 100, 200 and 250 genes were generated. The ability of these genes to classify unknown samples as being P deficient or P replete was then tested. Diagnostic leaves from field grown potatoes were sampled and the RNA extracted, labelled and hybridised to the POCI arrays. The samples were taken from either potatoes supplied with P fertiliser or from potatoes that received no P fertiliser as part of Objective 01. These data were then used as the test set and the kernel function and sets of diagnostic genes were changed systematically to optimise the classification of the field samples (Table 2). Using 200 genes as the diagnostic genes, with any kernel function, successfully characterised all samples correctly. The 200 genes contained 136 genes that were also identified as significantly differentially expressed in the leaves of hydroponically grown potatoes following the withdrawal of P from the nutrient solution (Supplementary Table 2).

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Table 2. Optimisation of support vector machine class prediction parameters

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Genes used

Actual Class +P -P +P -PKernel function Predicted Class -P +P +P -P % correctDot Product (Order 1) 25 5 7 10 8 60.0Dot Product (Order 2) 25 3 9 12 6 60.0Dot Product (Order 3) 25 2 7 13 8 70.0Radial basis 25 2 7 13 8 70.0

Dot Product (Order 1) 50 6 2 9 13 73.3Dot Product (Order 2) 50 0 3 15 12 90.0Dot Product (Order 3) 50 0 4 15 11 86.7Radial basis 50 0 4 15 11 86.7

Dot Product (Order 1) 100 7 0 8 15 76.7Dot Product (Order 2) 100 0 3 15 12 90.0Dot Product (Order 3) 100 0 3 15 12 90.0Radial basis 100 2 3 13 12 83.3

Dot Product (Order 1) 200 0 0 15 15 100.0Dot Product (Order 2) 200 0 0 15 15 100.0Dot Product (Order 3) 200 0 0 15 15 100.0Radial basis 200 0 0 15 15 100.0

Dot Product (Order 1) 250 2 0 13 15 93.3Dot Product (Order 2) 250 1 0 14 15 96.7Dot Product (Order 3) 250 1 0 14 15 96.7Radial basis 250 1 0 14 15 96.7

Dot Product (Order 1) 8,663 4 0 11 15 86.7Dot Product (Order 2) 8,663 2 1 13 14 90.0Dot Product (Order 3) 8,663 2 2 13 13 86.7Radial basis 8,663 2 2 13 13 86.7

Dot Product (Order 1) 28,946 2 2 13 13 86.7Dot Product (Order 2) 28,946 3 1 12 14 86.7Dot Product (Order 3) 28,946 5 2 10 13 76.7Radial basis 28,946 5 2 10 13 76.7The SVM implemented in the Class Prediction tool of GeneSpring GX was used to define groups of diagnostic genes and then to classify samples from potatoes grown in the field and supplied with P fertiliser or no P fertiliser.

8.5.4 Conclusions

Initially, a literature review and meta-analysis of transcriptional studies was undertaken to identify genes consistently and specifically up regulated in plants in response to P deficiency (Objective 02). A total of 86 genes were identified that were up regulated in transcriptional profiling studies of P deficient Arabidopsis plants (Table 1). To identify genes from potato, which respond specifically to P deficiency, a custom potato microarray was designed and built and used to monitor the expression of genes in the diagnostic leaves of potato plants subjected to P deficiency (Objective 03 and 04). A total of 1,659 genes were identified as being differentially expressed in potato leaves in response to P deficiency (Supplementary Table 2). The identities of these genes were consistent with those identified in Objective 02 that are involved in re-routeing C metabolism, alternative lipid metabolism and genes with phosphatase activity. These data were successfully used to predict the P status of diagnostic leaf samples taken from field grown potatoes (Objective 05). A SVM implemented in the Class Prediction tool of GeneSpring GX was used to define 200 diagnostic genes and then to classify samples as being P deficient or P replete.

This demonstrates the ability of genetic diagnostic markers for classifying the physiological status of crop plants. The ability to diagnose P deficiency, based on levels of gene expression, has the potential to more accurately define the P requirements of a crop plant, enabling more precise management of Pi fertiliser applications required to obtain optimal growth. This could ultimately optimise fertiliser applications, minimising the potential of excess fertilisers polluting surface waters. Further testing of these genetic diagnostic markers is now required in larger field trials and in crops compromised with different biotic and abiotic stresses.

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Wasaki J, Yonetani R, Kuroda S, Shinano T, Yazaki J, Fujii F, Shimbo K, Yamamoto K, Sakata K, Sasaki T, Kishimoto N, Kikuchi S, Yamagishi M, Osaki M (2003). Transcriptomic analysis of metabolic changes by phosphorus stress in rice plant roots. Plant, Cell and Environment 26, 1515-1523.

White PJ, Hammond JP (2006). Updating the estimate of the sources of phosphorus in UK waters. Final Report on Defra project WT0701CSF.

White PJ, Hammond JP (2008). Phosphorus nutrition of terrestrial plants. In: Hammond JP, White PJ (eds), The Ecophysiology of Plant-Phosphorus Interactions. Springer, Dordrecht, pp 51-81.

Whitfield WAD (1973). The soils of the National Vegetable Research Station, Wellesbourne. Report of the National Vegetable Research Station for 1973, pp.21-30.

Williamson LC, Ribrioux SPCP, Fitter AH, Leyser HMO (2001). Phosphate availability regulates root system architecture in Arabidopsis. Plant Physiology 126, 875-882.

Wissuwa M (2005). Combining a modeling with a genetic approach in establishing associations between genetic and physiological effects in relation to phosphorus uptake. Plant and Soil 269, 57-68.

Wu P, Ma L, Hou X, Wang M, Wu Y, Liu F, Deng XW (2003). Phosphate starvation triggers distinct alterations of genome expression in Arabidopsis roots and leaves. Plant Physiology 132, 1260-1271.

Yang YH, Speed, T (2002). Design issues for cDNA microarray experiments. Nature Reviews Genetics 3, 579-588.

8.7 Knowledge transfer and publications for HH3504SPO

8.7.1 Knowledge transfer activities

Knowledge transfer initiatives have been undertaken throughout the lifetime of this project and are ongoing.

In 2004/2005 the field trials and work related to this project were presented to the HRIA during a Growers Walk and at the Midland Regional Grower Show at HRI-Wellesbourne, and Philip White and Martin Broadley manned a BBSRC-sponsored stand at the Royal Show (Stoneleigh, Warwickshire). All involved speaking to the public, to growers, and to the press, about Defra project HH3504SPO in July 2004. A poster describing the Struvite component of the project was presented at an international conference on Struvite at Cranfield University. Aspects of this project were presented in lecture courses at the Universities of Coventry (PJ White), Nottingham (MR Broadley, JP Hammond, PJ White), Bratislava (PJ White) and in a lecture given by PJ White on "Plants that make the most of phosphate" at the University of Minia (Egypt) sponsored by The British Council. The work on diagnostic microarrays for mineral deficiencies featured in a press release from the SEB and subsequently on the web pages of Innovations Report (http://www.innovations-report.com/html/reports/agricultural_sciences/report-27403.html) and AgBiotechNet (http://www.agbiotechnet.com/news/Database/newsarticle). Our work on ‘smart plants’ was featured in a poster by Ruth Bastow on the GARNet consortium and in an article by Sarah Blackford on Microarray technology for the SEB Bulletin (October 2004, pp 8-9). Our work on the mineral nutrition of potatoes was presented at a meeting with a group of agronomists from Sweden, lead by Dr Hakan Sandin (Alnarp, Sweden). This meeting has resulted in collaborative research on the placement of fertilisers for potatoes (HH3509SFV).

In 2005/2006, the Mineral Nutrition Group led a field walk around their experiments at Wellesbourne, and aspects of this project were described by John Hammond at a Seed Industry Day at Warwick HRI and Philip White in lectures at FACTS Training Conferences hosted by Omex Ltd. Martin Broadley gave expert advice on a Coordinated Research Project on "Crop Nutritional Stress" to the FAO/IAEA, which included reference to this project. Descriptions of the diagnostic techniques being developed and the transcriptional profiling work were included in lecture courses at Nottingham University (MR Broadley, JP Hammond, PJ White) and at the Comenius University, Bratislava (PJ White), in invited seminars at Scottish Crop Research Institute (PJ White & JP Hammond), University of Warwick (JP Hammond), Rothamsted (PJ White), Nottingham University (PJ White), the Pontificia Universidad Catolica de Valparaiso and Universidad de Talca, Chile (PJ White) and at a CIMMYT Training Workshop in Santiago, Chile (PJ White). Visits to SCRI resulted in collaborative research on potato nutrition which has continued following the relocation of Philip White to SCRI. The Mineral Nutrition Group showed a poster on “Phosphorus fertiliser management @ Warwick HRI” to the Tetrapartite visit of Warwick HRI.

In 2006/2007 this project was presented at the 3rd International Symposium on Phosphorus Dynamics in the Soil-Plant Continuum, Uberlandia, Brazil, in addition it being discussed at meetings with the British Potato Council at Warwick, the Defra Phosphorus co-ordination meeting at Leicester and the Second Annual Meeting of the Solanaceae Research Community in the UK. Aspects of this project were also discussed, including the diagnostic techniques being developed and the transcriptional profiling work, in lecture courses at Nottingham University

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(MR Broadley, JP Hammond, PJ White) and at the Comenius University, Bratislava (PJ White) and in a departmental seminar at the University of Warwick (JP Hammond).

In 2007/2008, aspect of this project were discussed in presentations to a workshop on the Potato Oligo Chip Initiative (POCI) Workshop, a delegation from the Swedish Board of Agriculture, a delegation from Chinese Ministry of Agriculture, at Cambridge University Farm. Aspects of this project were also discussed, including the diagnostic techniques being developed and the transcriptional profiling work, in lecture courses at Nottingham University (MR Broadley, JP Hammond, PJ White) and at the Comenius University, Bratislava (PJ White) and in a departmental seminar at the University of Warwick (JP Hammond). The work from this project will also feature in a series of articles being written by the project team for the Grower on crop nutrition research.

8.7.2 Knowledge transfer to further projects:

“Genetic markers for water use-efficiency” Defra funded project (2004-2009) led by Andrew Thompson (Warwick).“Development and evaluation of low–phytate wheat germplasm to reduce diffuse phosphate pollution from pig

and poultry production units” Defra Sustainable Arable LINK Project (2005-2009) led by Steve Bentley (NIAB).

“Integrating phosphorous agronomy and genetics in Brassica”. Successful BBSRC Targeted Priority Studentship in Crop Science (2006-2010), by Philip White (Warwick). [N.B. Studentship subsequently reallocated by Warwick HRI following departure of Philip White in May 2006]

“Improving the zinc (Zn) composition of Brassica crops”. Successful BBSRC Targeted Priority Studentship in Crop Science (2006-2010), by Dr MR Broadley (Nottingham).

“Breeding oilseed rape with a low requirement for nitrogen fertiliser” Defra Sustainable Arable LINK Project (2006-2010) led by Peter Berry (ADAS).

“Updating the estimate of the sources of phosphorous in UK waters” Defra funded project (2006) led by Philip White (SCRI).

“Sustaining UK fresh onion supply by improving consumer acceptability, quality and availability” Defra Horticultural LINK project (2006-2009) led by David O’Connor (Allium and Brassica Centre Ltd).

“Quantifying the genetic diversity of phosphorus use efficiency in Brassica napus” Defra funded project (2007-2011) led by John Hammond (Warwick).

“Testing the hypothesis of neutral evolution of the brassicaceae leaf transcriptome” SCRI Innovation Fund (2007-2008) led by Philip White (SCRI).

“An electronic database for the curation of historic crop fertiliser response trials” Defra funded project (2007-2010) led by John Hammond (Warwick).

“Genetical genomics of the plant ionome to resolve phosphorus (P) acquisition and utilisation efficiency in Brassica.” Submitted to ERA-NET Plant Genomics 2008 Call, led by Graham King (RRes).

8.7.3 Future scientific opportunities related to HH3504SPO

The work conducted as part of HH3504SPO has identified areas for further research. Firstly, for struvite, research to address whether any potassium deficiency might be remedied, using alternative sources of struvite or different agronomic practices is required. There is also a need to confirm the effects of struvite are robust under different soil and climatic conditions.To ensure struvite can be used on a commercial scale additional research on the efficiency and scale with which struvite is recovered from sewage is required. More in depth assessments of struvite as a product are also required, including the chemical consistency of struvite recovered from sewage and the level of biological and chemical contaminants potentially present in struvite

Secondly, HH3504SPO has demonstrated it is possible to diagnose nutrient deficiencies in the potato crop, based on leaf gene expression profiles. To advance this work, further testing of these genetic diagnostic markers is now required in larger field trials and in crops compromised with different biotic and abiotic stresses. There are also possibilities to extend this approach to different nutrients or pest and diseases, in the potato crop or other crops.

8.7.4 Publications and knowledge transfer for Defra Project HH3504SPO

8.7.4.1 Refereed Publications

Primary outputs related to Defra project HH3504SPO

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White PJ, Bradshaw JE, Dale MFB, Ramsay G, Hammond JP, Broadley MR (2008). Relationships between yield and mineral concentrations in potato tubers. HortScience, in press

Hammond JP, White PJ (2008). Sucrose transport in the phloem: integrating root responses to phosphorus starvation. Journal of Experimental Botany 59, 93-109.

Hermans C, Hammond JP, White PJ, Verbruggen N (2007) Response to Andrews et al.: correlations and causality. Trends in Plant Science 12, 532-533.

Kloosterman B, De Koeyer D, Griffiths R, Flinn B, Steuernagel B, Scholz U, Sonnewald S, Sonnewald U, Bryan GJ, Prat S, Bánfalvi Z, Hammond JP, Geigenberger P, Nielsen KL, Visser RGF, Bachem CWB (2008). Genes driving potato tuber initiation and growth: identification based on transcriptional changes using the POCI array. Functional & Integrative Genomics doi 10.1007/s10142-008-0083-x

Hermans C, Hammond JP, White PJ, Verbruggen N (2006). How do plants respond to nutrient shortage by biomass allocation? Trends in Plant Science 11, 610-617.

Hammond JP, Broadley MR, Craigon DJ, Higgins J, Emmerson Z, Townsend H, White PJ, May ST (2005). Using genomic DNA-based probe-selection to improve the sensitivity of high-density oligonucleotide arrays when applied to heterologous species. Plant Methods 1, doi:10.1186/1746-4811-1-10.

Hammond JP, Broadley MR, White PJ (2004). Genetic responses to phosphorus deficiency. Annals of Botany 94, 323-332.

Peripheral outputs (e.g. techniques, concepts etc.) related to Defra project HH3504SPO

Broadley MR, White PJ, Hammond JP, Graham NS, Bowen HC, Emmerson ZF, Fray RG, Iannetta PPM, McNicol JW, May ST (2008) Evidence of neutral transcriptome evolution in plants. New Phytologist, Submitted.

Broadley MR, White PJ, Hammond JP, Zelko I, Lux A (2007). Zinc in plants. New Phytologist 173, 677-702.Zhang K, Greenwood DJ, White PJ and Burns IG (2007). A dynamic model for the combined effects of N, P and K

fertilizers on yield and mineral composition; description and experimental test. Plant and Soil 298, 81-98.Graham NS, Broadley MR, Hammond JP, White PJ, May ST (2007). Optimising the analysis of transcript data

using high density oligonucleotide arrays and genomic DNA-based probe selection. BMC Genomics 8, 344.

Hammond JP, Bowen HC, White PJ, Mills V, Pyke KA, Baker AJM, Whiting SN, May ST, Broadley MR (2006). A comparison of the Thlaspi caerulescens and Thlaspi arvense shoot transcriptomes. New Phytologist 170, 239-260.

Hampton CR, Bowen HC, Broadley MR, Hammond JP, Mead A, Payne KA, Pritchard J, White PJ (2004). Cesium toxicity in Arabidopsis. Plant Physiology 136, 3824-3837.

8.7.4.2 Edited Publications

Primary outputs related to Defra project HH3504SPO

Hammond JP, White PJ eds (2008) The Ecophysiology of Plant-Phosphorus Interactions. Springer, Dordrecht, The Netherlands.

Hammond JP, White PJ, Bennett MJ eds (2008) Special Issue: Transport of Plant Growth Regulators. Journal of Experimental Botany 59.

George T, Brown L, Wishart J, Wright G, Thompson A, Ramsay G, Bradshaw J, White PJ (2008). Phosphorus efficient potatoes. SCRI annual report 2007, pp 42-53.

Hammond JP, White PJ (2008). Diagnosing phosphorus deficiency in crops. In: White PJ, Hammond JP (eds), The Ecophysiology of Plant-Phosphorus Interactions. Springer, Dordrecht, The Netherlands, pp 225–246.

White PJ, Hammond JP (2008). Phosphorus nutrition of terrestrial plants. In: Hammond JP, White PJ (eds), The Ecophysiology of Plant-Phosphorus Interactions. Springer, Dordrecht, pp 51-81.

White PJ, Wheatley RE, Hammond JP, Zhang K (2007) Minerals, soils and roots. In: Potato Biology and Biotechnology: Advances and Perspectives, D Vreugdenhil et al. (eds.) Elsevier Science, pp. 739-752.

Amtmann A, Hammond JP, Armengaud P, White PJ (2006). Nutrient sensing and signalling in plants: potassium and phosphorus. Advances in Botanical Research, 43, 209-256.

White PJ, Broadley MR, Greenwood DJ, Hammond JP (2005). Genetic modifications to improve phosphorus acquisition by roots. Proceedings of International Fertiliser Society 568, IFS: York, UK.

White PJ, Broadley MR, Hammond JP, Thompson AJ (2005). Optimising the potato root system for phosphorus and water acquisition in low-input growing systems. In: Aspects of Applied Biology 73, Advances in Applied Biology: Roots and the soil environment, pp. 111-118. Association of Applied Biologists, Wellesbourne, UK.

Hammond JP, White PJ, Broadley MR (2004). Diagnosing phosphorus deficiency in plants. In: Aspects of Applied Biology 72, Advances in Applied Biology: Providing new opportunities for consumers and producers in the 21st Century, pp. 89-98. Association of Applied Biologists, Wellesbourne, UK.

Peripheral outputs (e.g. techniques, concepts etc.) related to Defra project HH3504SPO

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Broadley MR, White PJ eds (2005). Plant nutritional genomics. Oxford, UK: Blackwell, 321 pp. White PJ, Broadley MR, Greenwood DJ, Hammond JP, King GJ, Meacham MC, Stellacci AM (2005). Optimising

phosphorus fertilisation of Brassica. In: Plant Nutrition for Food Security, Human Health and Environmental Protection, CJ Li et al. (eds), p. 1052-1053. Tsinghua University Press, Beijing.

Donnelly SJ, Broadley MR, Black CR, Young SD, Pyke KA and McGrath SP (2004). Zinc tolerance and accumulation in Arabidopsis thaliana. In: Luo YM, Japenga J, Edelman T, Newman L, McGrath SP, Zhao FJ, Marschner B and Vanek T. Proceedings of the Second International Conference on Soil Pollution and Remediation (SOILREM 2004). pp 186-193.

May ST, Hammond JP, Broadley MR, White PJ (2004). A chip for all species. GARNish: The official GARNet newsletter. December 2004, pp. 10.

White PJ, Broadley MR (2004). Preface to genetics of plant mineral nutrition (Special Issue). Journal of Experimental Botany, 55. IV-IV.

8.7.4.3 Trade publications

Hammond JP, White PJ (2008). Reducing run-off for clean water. Horticulture Week (Grower), 26 June 2008, pp. 44-46.

Hammond JP, White PJ (2008). Sustainable future for fertilisers. Horticulture Week (Grower), 21 February 2008, pp. 33-34.

Hammond JP (2006). Halving the Fertiliser Burden. The Vegetable Farmer, February 2006, pp. 30.Hammond JP, Broadley MR, White PJ (2004). Interpreting signals from plants. European Business Report, XIII

2Q, pp. 55.White PJ, Broadley MR, Burns IG, Greenwood DJ, Hammond JP, Meacham MC, Rahn C, Stellacci A-M (2004).

Making the most of phosphate fertilisers. The Grower, 24th June 2004, pp. 14-15.

8.7.4.4 Oral and poster presentations

2004MR Broadley (2004). Nutrient use efficiency in Brassica. Presentation to UK Brassica Research Community

Meeting organised by GJ King, 9th March 2004. JP Hammond, PJ White, MR Broadley, MJ Bennett (2004). Taking the P out of plants. In: Young Scientists Prize

Awards Session, Society for Experimental Biology Annual Meeting, Heriot-Watt University, 29 Mar–2 April 2004. John was awarded third prize.

JP Hammond, MR Broadley, PJ White (2004). Is struvite a suitable alternative to inorganic phosphorus fertilisers in agriculture? International Conference – Struvite: Its role in Phosphorus Recovery and Reuse, Cranfield University, Cranfield, 17-18 June 2004.

PJ White, HC Bowen, MR Broadley, JP Hammond, CR Hampton, KA Payne (2004). The mechanisms of caesium uptake by plants. International Symposium on Radioecology and Environmental Dosimetry, Rokkasho, Aomori, Japan. October 22-24, 2003

JP Hammond, PJ White, MR Broadley (2004). Diagnosing phosphorus deficiency in plants. Association of Applied Biologists meeting. Providing new opportunities for consumers and producers in the 21st century, University of Oxford, 14-16 December 2005.

2005PJ White, MR Broadley, JP Hammond, AJ Thompson (2005). Optimising the potato root system for phosphorus

and water acquisition in low-input growing systems. Roots and the Soil Environment II: An International Conference of the Association of Applied Biologists, Nottingham University, 4-6th April 2005.

PJ White, MR Broadley, JP Hammond (2005) P1.12 Optimising the potato root system for phosphorus acquisition. In: Abstracts of the Annual Main Meeting of the Society for Experimental Biology, Barcelona, 11-15th July, 2005. Comparative Biochemistry and Physiology Part A 141, 222.

MR Broadley, PJ White (2005) Variation and the ionome. In: Proceedings of the First International Workshop on Plant Ionomics, Beijing, China, 12-14th September 2005, p. 7.

PJ White, MR Broadley, DJ Greenwood, JP Hammond, GJ King, MC Meacham, AM Stellacci (2005) #0-9-1. Optimising phosphorus fertilisation of Brassica. Fifteenth International Plant Nutrition Colloquium, Beijing, China, 14-19th September 2005.

PJ White (2005) Fertilisers and vegetables. Food & Climate Research Network Workshop on Fruit and Vegetables. Manchester, 1st December 2005.

PJ White (2005) Genetic modifications to improve nutrient uptake by roots. Efficient crop nutrition: Challenges and prospects, International Fertiliser Society-Dahlia Greidiger Foundation Joint Symposium, Cambridge, 14-16th December 2005.

2006JP Hammond, PJ White, MR Broadley (2006) P6.26 Developing transcriptional platforms for non-model plant

species. In: Abstracts of the Annual Main Meeting of the Society for Experimental Biology, Canterbury, 3-7th April 2006. Comparative Biochemistry and Physiology 143A, S179.

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PJ White (2006) C5.12 Ionomics of the Brassicaceae. In: Abstracts of the Annual Main Meeting of the Society for Experimental Biology, Canterbury, 3-7th April 2006. Comparative Biochemistry and Physiology 143A, S137.

JP Hammond, MR Broadley, PJ White (2006). Diagnosing phosphorus deficiency in crop plants by monitoring changes in gene expression. In: Proceedings of the 3rd International Symposium on Phosphorus Dynamics in the Soil-Plant Continuum, Uberlandia, MG, Brazil, 14th-19th May 2006, pp. 125-126.

MR Broadley, JP Hammond, PJ White (2006) Mineral nutrition. UK-Canada Brassica Genomics Workshop, Brocket Hall, Hertfordshire, 27th September 2006

2007JP Hammond, PJ White, Bowen HC, Hayden RM, Spracklen WP (2007). Preparing and analysing Agilent array

data. Potato Oligo Chip (POCI) Workshop, Wageningen, Netherlands, 27th - 28th March 2007.JP Hammond, PJ White (2007). Phloem sucrose: Integrating phosphorus starvation responses. Annual Main

Meeting of the Society for Experimental Biology, Glasgow, April 2007.S Ó Lochlainn, HC Bowen, R Fray, JP Hammond, GJ King, V Mills, PJ White, MR Broadley (2007) Natural

genetic variation in zinc (Zn) accumulation in Brassicaceae species. Annual Main Meeting of the Society for Experimental Biology, Glasgow, April 2007.

HC Bowen, RM Hayden, WP Spracklen, PJ White, Hammond JP (2007) Targeting phosphorus fertiliser applications to roots of wide row crops. Crop Science Seminar Series, Warwick HRI, 16th April 2007.

JP Hammond, PJ White (2007) Phloem sucrose: Integrating phosphorus starvation responses. Departmental Seminar Series, Warwick HRI, 5th March 2007.

MR Broadley (2007) Species wide genetic variation in the leaf mineral composition of Brassica oleracea. UK-BRC Annual meeting, Rothamsted Research, 23rd May 2007.

JP Hammond (2007) Quantifying the genetic diversity of phosphorus use efficiency in Brassica napus. UK-BRC Annual meeting, Rothamsted Research, 23rd May 2007.

PJ White (2007) The genetics of phosphorus use efficiency in Brassica oleracea. UK-BRC Annual meeting, Rothamsted Research, 23rd May 2007.

NS Graham, MR Broadley, JP Hammond, PJ White, ST May et al. (2007). Optimisation of high density oligonucleotide array data using genomic DNA based probe selection. GARNet 2007, John Innes Centre, Norwich, 10-11th September 2007.

S Ó Lochlainn, HC Bowen, R Fray, NS Graham, JP Hammond, GJ King, V Mills, PJ White, MR Broadley (2007). P11. Natural genetic variation in zinc (Zn) accumulation in Brassicaceae. In: Abstracts of GARNet 2007, John Innes Centre, Norwich, 10-11th September 2007.

JP Hammond (2007) Presentation to delegation from the Swedish Board of Agriculture on crop nutrition research at Warwick HRI. 12th November 2007.

JP Hammond (2007) Presentation to RB209 Vegetable sub-committee on fertiliser requirements of Brassicas. 7 th

November 2007.JP Hammond (2007) Presentation to delegation from Chinese Ministry of Agriculture. 25th October 2007.JP Hammond (2007) Presentation to Abacus Organic Associates on breeding crops with improved nutrient use

efficiency. 2nd October 2007JP Hammond (2007) Presentation to Defra delegation (Sue Popple and Sonia Phippard) on current research

activities in crop nutrition. 14th August 2007.JP Hammond (2007) Presentation at Warwick Institute for Sustainable Energy and Resources (WISER) on

energy and resource use in agriculture. 6th July 2007.JP Hammond (2007) Presentation at Cambridge University Farm to discuss work on crop nutrient management.

27th June 2007.

2008JP Hammond (2008) Presentation to Lord Rooker on Sustainable Agriculture at Warwick HRI, University of

Warwick, Wellesbourne, UK. 12th March 2008.PJ White (2008) The need to improve resource use by potatoes – Water and mineral elements. Improving

International Potato Production 8th August 2008.JP Hammond, White PJ, Broadley MR (2009). Assessing the suitability of struvite as a source of P for potato

production. International Conference on Nutrient Recovery from Wastewater Streams, May 10-13, 2009 - Vancouver, British Columbia, Canada. Abstract Submitted.

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 30 of 31

See section 8.7 of the main report.

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