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This paper estimates the effects of potential post-Brexit UK trade and domestic agricultural policy scenarios on the economic welfare (real income) of farm households, at both regional (devolved ad...

Well-managed legume-based food systems are uniquely positioned to curtail theexistential challenge posed by climatechangethrough the significant contributionthat legumes can make toward limiting Green House Gas (GHG) emissions. Thispotential is enabled by the specific functional attributes offered only by legumes,which deliver multiple co-benefits through improved ecosystem functions, includingreduced farmland biodiversity loss, and better human-health and -nutrition provisioning.These three critical societal challenges are referred to collectively here as the“climate-biodiversity-nutrition nexus.” Despite the unparalleled potential of the provisionsoffered by legumes, this diverse crop group remains characterized as underutilizedthroughout Europe, and in many regions world-wide. This commentary highlightsthat integrated, diverse, legume-based, regenerative agricultural practices shouldbe allied with more-concerted action on ex-farm gate factors at appropriatebioregional scales.Also,thatthiscanbeachievedwhilstoptimizing production, safeguarding food-security, and minimizing additional land-use requirements. To helpavoid forfeiting the benefits of legume cultivation for system function, a specificand practical methodological and decision-aid framework is offered. This is basedupon the identification and management of sustainable-development indicators forlegume-based value chains, to help manage the key facilitative capacities anddependencies. Solving the wicked problems of the climate-biodiversity-nutrition nexus demands complex solutions and multiple benefits and this legume-focus must beallied with more-concerted policy action, including improved facilitation of the catalyticprovisions provided by collaborative capacity builders—to ensure that the knowledgenetworks are established, that there is unhindered information flow, and that newtransformative value-chain capacities and business models are established.

Intensive agriculture and meat-based westernized diets have brought a heavy environmental burden to the planet. Legumes, or pulses, are members of the large Fabaceae (Leguminosae) family, which comprise about 5% of all plant species. They are ancient crops whose popularity both for farmers and consumers has gonethrough several stages of acceptance, and in recent years, legumes have regained their luster. This is due to a global understanding that: (1) farming systems need to promote biodiversity, (2) biological nitrogen fixation is an important tool to reduce the application of external chemical inputs, namely in the form of nitrogen fertil- izers, and that (3) plant-based foods have fewer adverse environmental effects per unit weight, per serving, per unit of energy, or per protein weight than do animal source foods, across various environmental indicators. Legumes play a key role in answering these three global challenges and are pivotal actors in the diversification and sustainable intensification of agriculture, particularly in light of new and urgent challenges such as climate change. In this chapter, we showcase the importance of legumes as contemporary agents of change, whose impacts start in the field, but then branch out into competitive global economies, modernized societies, and ultimately, improved food security and human health.

This Deliverable describes the Project Legacy Plan (version I) of the TRUE-Project. It formally details how the various products developed from TRUE-Projectactivities will be manged and coordinated to ensure project impact legacy beyond the funded project term. To improve this aim the bulk of this document present a highly detailed series of vignettes that capturea wide range of perspectives from the exercise of, 'considering legumes in context'. Going forward, the TRUE-Project’s implementation plans will be developed based on these insights. Also, delivered collectively, they are expected to encourage transition from current conventional food- and feed-networks, to those which are legume-based and more sustainable.

This plan formalises specific operations (meetings and agendas), at Work Package (WP) and sub-WP level for the following 12 months. The output will be formalised via the private workspace, and associated project management software. The plan will identify and facilitate the necessary Coordination to help ensure the timely delivery and success of linked project activities and meetings or workshops. This plan will also help inform the framework of the Data Management Plan.&nbsp

This Deliverable report presents the impact of key factors influencing decision making of farmers and consumers to uptake legume cultivation and, respectively, the choice to include legumes into diets. Results provide guidance on determinants of positive behavioural change towards legume inclusion. Farmer and consumer analyses are based on survey data for the UK farmers and consumers, and findings are discussed comparatively in the context of European production and consumption and main factors potentially influencing behaviours and trends. The report informs how we may operate more effectively to affect behavioural change positively towards legume inclusion.

The series of decision models produced in this Deliverable (D8.2) will be integrated into a model for the assessment of overall sustainability of legume systems, with respect to the identification of key legume-based system indicators for the three pillars of sustainability. The decision model will be then used for evaluation of the relative sustainability of transition pathways to more effective scenarios.&nbsp

Impact Plan: this Deliverable report (D9.8, D56) is directed by feedback from TRUE’s Stakeholder Advisory Board (SAB, the commercial partners), and also from other multi-actors engaged via the ISAB (Intercontinental Science Advisory Board), and including operatives of the European Legume Innovation Network (or ‘E-LIN’) workshops, existing relevant H2020 research projects, and successful RUR (rural renaissance) projects. This direction will help ensure research complementarity, synergy and science excellence. The aim of this report is to define the best routes to impact. &nbsp

Intensive agriculture and meat-based westernized diets have brought a heavy environmental burden to the planet. Legumes, or pulses, are members of the large Fabaceae (Leguminosae) family, which comprise about 5% of all plant species. They are ancient crops whose popularity both for farmers and consumers has gone through several stages of acceptance, and in recent years, legumes have regained their luster. This is due to a global understanding that: (1) farming systems need to promote biodiversity, (2) biological nitrogen fixation is an important tool to reduce the application of external chemical inputs, namely in the form of nitrogen fertilizers, and that (3) plant-based foods have fewer adverse environmental effects per unit weight, per serving, per unit of energy, or per protein weight than do animal source foods, across various environmental indicators. Legumes play a key role in answering these three global challenges and are pivotal actors in the diversification and sustainable intensification of agriculture, particularly in light of new and urgent challenges such as climate change. In this chapter, we showcase the importance of legumes as contemporary agents of change, whose impacts start in the field, but then branch out into competitive global economies, modernized societies, and ultimately, improved food security and human health.

This Deliverable describes the Project Legacy Plan (version I) of the TRUE-Project. It formally details how the various products developed from TRUE-Project activities will be manged and coordinated to ensure project impact legacy beyond the funded project term. To improve this aim the bulk of this document present a highly detailed series of vignettes that capture a wide range of perspectives from the exercise of, 'considering legumes in context'. Going forward, the TRUE-Project’s implementation plans will be developed based on these insights. Also, delivered collectively, they are expected to encourage transition from current conventional food- and feed-networks, to those which are legume-based and more sustainable.

This paper investigates farm gross margin effects of management measures aimed at enhancing soil organic carbon (SOC) stocks to maintain soil fertility while providing important ecosystem services. An optimising farm level model, ScotFarm, is used to investigate the farm gross margin effects of selected SOC management measures for arable farms in Scotland (UK) and Aragon (Spain). The sensitivity of model results to effects on crop yields and costs of production is tested for each measure. The results suggest that considerable regional differences in the financial viability of SOC measures exist. Tillage management is the only measure with positive effects on farm gross margins of Scottish farms at baseline levels of yield effects and input costs. In the case of farms in Aragon, Spain, fertiliser management, crop rotations (with legumes) and tillage management (in later years) show improvements in gross margins. Residue management is estimated to have a negative effect on farm gross margins for both Scottish and Spanish crop farms. Results of the sensitivity analysis indicate that effects of SOC management on farm gross margins are more sensitive to a change in crop yields than to changes in input costs. The findings point to further research needs with respect to the trade-offs between yield effects and changes in input costs arising from the adoption of SOC management measures, and have implications for agricultural policy design aimed at enhancing SOC stocks under a changing climate.

Modelling is key to adapting agriculture to climate change (CC), facilitating evaluation of the impacts and efficacy of adaptation measures, and the design of optimal strategies. Although there are many challenges to modelling agricultural CC adaptation, it is unclear whether these are novel or, whether adaptation merely adds new motivations to old challenges. Here, qualitative analysis of modellers’ views revealed three categories of challenge: Content, Use, and Capacity. Triangulation of findings with reviews of agricultural modelling and Climate Change Risk Assessment was then used to highlight challenges specific to modelling adaptation. These were refined through literature review, focussing attention on how the progressive nature of CC affects the role and impact of modelling. Specific challenges identified were: Scope of adaptations modelled, Information on future adaptation, Collaboration to tackle novel challenges, Optimisation under progressive change with thresholds, and Responsibility given the sensitivity of future outcomes to initial choices under progressive change., Graphical abstract Image 1, Highlights • Modelling plays a key role in adapting agriculture to climate change. • Modellers' views and literature were analysed to identify adaptation-specific issues. • Novel challenges to modelling climate change adaptation were explored. • Challenges related to Responsibility, Scope, Optimisation, Information, Collaboration. • Adaptation to progressive climate change highlights social impacts of model use.

Johne's disease is an endemic contagious bacterial infection of ruminants which is prevalent in the United Kingdom and elsewhere. It can lower financial returns on infected farms by reducing farm productivity through output losses and control expenditures. A farm-level analysis of the economics of the disease was conducted taking account of farm variability and different disease prevalence levels. The aim was to assess the financial impacts of a livestock disease on farms and determine their financial vulnerability if farm support payments were to be removed under future policy reforms. A farm-level optimization model, ScotFarm, was used on 50 Scottish dairy farms taken from the Farm Business Survey to determine the impacts of the disease. A counterfactual comparison of five alternative "disease" scenarios with a "no-disease" scenario was carried out to evaluate economic impact of the disease. The extent of a farm's reliance on direct support payments was considered to be an indicator of their financial vulnerability. Under this definition, farms were grouped into three financial vulnerability risk categories; "low risk," "medium risk," and "high risk" farms. Results show that farms are estimated to incur a loss of 32% on average of their net profit under a standard disease prevalence level. Farms in the "low risk" and "medium risk" categories were estimated to have a lower financial impact of the disease (22 and 28% reduction on farm net profit, respectively) which, along with their lower reliance on farm direct support payments, indicate they would be more resilient to the disease under future changes in farm payment support. On the contrary, farms in the "high risk" category were estimated to have a reduction of 50% on their farm net profit. A majority of these farms (61%) in the "high risk" category move from being profitable to loss making under the standard disease scenario when farm support payments are removed. Of these, 15% do so because of the impact of the disease. These farms will be more vulnerable if changes were to be made in farm support payments under future agricultural policy reforms.

Climate change has the potential to impair livestock health, with consequences for animal welfare, productivity, greenhouse gas emissions, and human livelihoods and health. Modelling has an important role in assessing the impacts of climate change on livestock systems and the efficacy of potential adaptation strategies, to support decision making for more efficient, resilient and sustainable production. However, a coherent set of challenges and research priorities for modelling livestock health and pathogens under climate change has not previously been available. To identify such challenges and priorities, researchers from across Europe were engaged in a horizon-scanning study, involving workshop and questionnaire based exercises and focussed literature reviews. Eighteen key challenges were identified and grouped into six categories based on subject-specific and capacity building requirements. Across a number of challenges, the need for inventories relating model types to different applications (e.g. the pathogen species, region, scale of focus and purpose to which they can be applied) was identified, in order to identify gaps in capability in relation to the impacts of climate change on animal health. The need for collaboration and learning across disciplines was highlighted in several challenges, e.g. to better understand and model complex ecological interactions between pathogens, vectors, wildlife hosts and livestock in the context of climate change. Collaboration between socio-economic and biophysical disciplines was seen as important for better engagement with stakeholders and for improved modelling of the costs and benefits of poor livestock health. The need for more comprehensive validation of empirical relationships, for harmonising terminology and measurements, and for building capacity for under-researched nations, systems and health problems indicated the importance of joined up approaches across nations. The challenges and priorities identified can help focus the development of modelling capacity and future research structures in this vital field. Well-funded networks capable of managing the long-term development of shared resources are required in order to create a cohesive modelling community equipped to tackle the complex challenges of climate change.

A simple method is developed to determine the light trapping properties of arbitrarily textured solar cells with high accuracy. The method allows for determining the quantum efficiency and short circuit current density of thin film solar cells prepared on randomly nanotextured surfaces. The light trapping of the randomly textured solar cell is described by the area weighted superposition of periodically textured solar cells. The necessary input parameters for the calculations are determined by analyzing the randomly textured surfaces of the solar cells using atomic force microscopy and image processing. The analysis of the atomic force microscope images and the calculation of the quantum efficiency and short circuit current can be determined from current maps, without complex and time-consuming calculations. The calculated solar cell parameters exhibit excellent agreement with experimentally measured quantum efficiencies and short circuit current densities for amorphous and microcrystalline silicon thin film solar cells prepared on randomly textured substrates. Finally, the work contributes to a comparison of random and periodic light trapping structures.

We estimate the impact of diversification on the performance of farm businesses using measures of economic viability among farms in Scotland and Sweden. We derive indicators of viability using national level accounting surveys for the period 2000–2012 and account for short-term and long-term effects within our estimates of viability. A higher proportion of Scottish farms emerge as being more short-term and long-term viable than Swedish farms. This could, we propose, be due to emphasis on enhancing farm viability within Scottish planning for rural development, compared to Sweden which emphasized productivity and environmental enhancement. Moreover, for both countries the trend in viability is relatively stable until 2007, when both panels begin to display the impact of policy and market change. Findings based on a multinomial logistic regression indicate that farms which run additional ventures outside traditional agriculture, and are diversified in the sense that they obtain revenue from two or more agricultural enterprises, are more viable compared to specialized agricultural units. Other factors which affect viability were found to be structural, biophysical and institutional, specifically the reform of the Common Agricultural Policy (CAP) in 2003. However the significance and magnitude of these effects differ across the two countries. Consequently, these results seem to imply the importance of emphasizing non-specialized agricultural activities within rural development policy and, moreover, informs the rationale behind proposed redistributions of CAP payments.

This repository contains a series of brochures promoting the work of the Land Economy, Environment and Society research group.

SUMMARYThe latest Common Agricultural Policy (CAP) reforms could bring substantial changes to Scottish farming communities. Two major components of this reform package, an introduction of environmental measures into the Pillar 1 payments and a move away from historical farm payments towards regionalized area payments, would have a significant effect on altering existing support structures for Scottish farmers, as it would for similar farm types elsewhere in Europe where historic payments are used. An optimizing farm-level model was developed to explore how Scottish beef and sheep farms might be affected by the greening and flat rate payments under the current CAP reforms. Nine different types of beef and sheep farms were identified and detailed biophysical and financial farm-level data for these farm types were used to parameterize the model. Results showed that the greening measures of the CAP did not have much impact on net margins of most of the beef and sheep farm businesses, except for ‘Beef Finisher’ farm types where the net margins decreased by 3%. However, all farm types were better off adopting the greening measures than not qualifying for the greening payments through non-compliance with the measures. The move to regionalized farm payments increased the negative financial impact of greening on most of the farms but it was still substantially lower than the financial sacrifice of not adopting greening measures. Results of maximizing farm net margin, under a hypothetical assumption of excluding farm payments, showed that in most of the mixed (sheep and cattle) and beef suckler cattle farms the optimum stock numbers predicted by the model were lower than actual figures on farm. When the regionalized support payments were allocated to each farm, the proportion of the mixed farms that would increase their stock numbers increased whereas this proportion decreased for beef suckler farms and no impact was predicted in sheep farms. Also under the regionalized support payments, improvements in profitability were found in mixed farms and sheep farms. Some of the specialized beef suckler farms also returned a profit when CAP support was added.

SUMMARYThe current paper aims to determine regional impacts of climate change on Irish farms examining the variation in farm responses. A set of crop growth models were used to determine crop and grass yields under a baseline scenario and a future climate scenario. These crop and grass yields were used along with farm-level data taken from the Irish National Farm Survey in an optimizing farm-level (farm-level linear programming) model, which maximizes farm profits under limiting resources. A change in farm net margins under the climate change scenario compared to the baseline scenario was taken as a measure to determine the effect of climate change on farms. The growth models suggested a decrease in cereal crop yields (up to 9%) but substantial increase in yields of forage maize (up to 97%) and grass (up to 56%) in all regions. Farms in the border, midlands and south-east regions suffered, whereas farms in all other regions generally fared better under the climate change scenario used in the current study. The results suggest that there is a regional variability between farms in their responses to the climate change scenario. Although substituting concentrate feed with grass feeds is the main adaptation on all livestock farms, the extent of such substitution differs between farms in different regions. For example, large dairy farms in the south-east region adopted total substitution of concentrate feed while similar dairy farms in the south-west region opted to replace only 0·30 of concentrate feed. Farms in most of the regions benefitted from increasing stocking rate, except for sheep farms in the border and dairy farms in the south-east regions. The tillage farms in the mid-east region responded to the climate change scenario by shifting arable production to beef production on farms.

The current paper investigates the medium term economic impact of climate changes on the EU agriculture. The yield change data under climate change scenarios are taken from the BIOMA (Biophysical Models Application) simulation environment. We employ CAPRI modelling framework to identify the EU aggregate economic effects as well as regional impacts. We take into account supply and market price adjustments of the EU agricultural sector as well as technical adaptation of crops to climate change. Overall results indicate an increase in yields and production level in the EU agricultural sector due to the climate change. In general, there are relatively small effects at the EU aggregate. For example, the value of land use and welfare change by approximately between -2% and 0.2%. However, there is a stronger impact at regional level with some stronger effects prevailing particularly in the Central and Northern EU and smaller impacts are observed in Southern Europe. Regional impacts of climate change vary by a factor higher up to 10 relative to the aggregate EU impacts. The price adjustments reduce the response of agricultural sector to climate change in particular with respect to production and income changes. The technical adaption of crops to climate change may result in a change production and land use by a factor between 1.4 and 6 relative to no-adaptation situation.

The influence of the interface morphologies on amorphous silicon thin-film solar cells prepared on randomly textured substrates was studied. A simple three-dimensional geometrical model was developed to describe the surface morphology of amorphous silicon films and thin-film solar cells. The simulated surface morphologies are confirmed by experimental measurements. A detailed understanding of the interface morphologies is required to gain insights in the light-trapping of silicon thin-film solar cells on randomly textured substrates and derive strategies to improve the light-trapping properties. The morphology of amorphous silicon solar cell layers is calculated by using atomic force microscope scans of the randomly textured substrates and the thickness of layers as input data. The influence of the interface morphologies on the surface roughness, average film thickness and size of surface textures is investigated. Finally the influence of these parameters on the light-trapping and optical losses is discussed.

A mechanical device has been developed as an ophthalmic ultrasonic scanning probe. The device is composed of an oscillating probe where the ultrasound transducer is mounted, part of which is flexible so the probe can oscillate when energized. Electric current is supplied to two electromagnetic coils acting on two permanent magnets mounted on both sides of the probe. A controller is employed to control the angular position of the probe during operation. Computer simulation, including the mechanical device and the controller, shows promising performance over the entire operation frequency.

This paper estimates the inefficiencies associated with the regionalisation of the milk quota trade. An optimisation model is developed to estimate the economic value of quota. Quota values are aggregated to derive quota sale and purchase curves under two scenarios: first, where quotas can be traded nationally and second, where the trade of quota is regionally restricted. Quota trade is simulated and the consequent effects on supplier structure estimated. Through the derivation of sectoral cumulative cost curves it is possible to estimate the impact of regionalising quota trade on sector efficiency. The model is solved using National Farm Survey data from Ireland and the inefficiencies of regionalised quota trade in Ireland are estimated at €27 million. The paper concludes by discussing the implications of restricted quota trade, especially in the context of eventual quota removal.

Irish agriculture has undergone fundamental transformations in the last two decades. A growing divergence between farming and non-farming incomes and a significant increase in part-time farming have led to intense debates surrounding the future viability of the Irish farmer. Irrespective of such deliberations, agriculture still remains an important employer and contributor to the regional economies of Ireland, a factor that is discussed in this paper. An analysis of the financial performance of farms shows that the regions that rely most on agriculture as an employer have the most economically and physically disadvantaged farms. The paper examines the role of agricultural policy in addressing this regional imbalance. In particular, the recent decoupling policy is examined. The results of economic models suggest that the decoupling reform increases the viability of farming in Ireland across all regions. However, the decision to implement the historical decoupled payment scheme has served to perpet...

A three-dimensional model that predicts the interface morphologies of silicon thin-film solar cells prepared on randomly textured substrates was developed and compared to experimental data. The surface morphologies of silicon solar cells were calculated by using atomic force microscope scans of the textured substrates and the film thickness as input data. Calculated surface morphologies of silicon solar cells are in good agreement with experimentally measured morphologies. A detailed description of the solar cell interface morphologies is necessary to understand light-trapping in silicon single junction and micromorph tandem thin-film solar cells and derive optimal light-trapping structures.

This report is based on the outcome of a study carried out by the European Commission's Joint Research Centre - Institute for Prospective Technological Studies (JRC-IPTS, Spain) in cooperation with EuroCARE (Bonn, Germany). The report provides a detailed description of the methodology developed to assess the implications of the European Renewable Energy Directive on the agricultural sector, with an explicit focus on regional effects of biofuel targets in the EU. For the analysis, the spatial agricultural sector model CAPRI has been extended to include a global representation of biofuel markets (with endogenous supply, demand and trade flows for biofuels and biofuel feedstocks) while keeping the focus on regional impacts in the EU. The model is capable to simulate the impacts of EU biofuel policies on food production and prices, the potential use of by-products in the feed chain, the increasing pressure on marginal and idle land and the share of imported biofuels (self-sufficiency indicators). CAPRI is now able to jointly assess biofuel and agricultural policies, including policy instruments defined at the Member State level. The CAPRI biofuel module allows for a detailed analysis of most relevant biofuel support instruments like consumer tax exemptions, quota obligations, import tariffs and other trade measures. Additionally, the model allows for analysing scenarios regarding technical progress in 2nd generation technologies for biofuels.

The transfer of knowledge from research community to specialized remote sensing software has been extremely slow hindering the application of ANN techniques in remote sensing field. There are many variants of ANN depending upon its topology and its learning paradigms but Multilayer perception (MLP) with back propagation (BP) is widely used in remote sensing despite its limitation such as fine tuning of numbers of input parameters such as learning rate, momentum, number of hidden layers and number of hidden nodes. In this paper, recently proposed Extreme Learning Machine (ELM) version of ANN which is extremely fast and does not require any iterative learning is introduced. In ELM classifier, only number of neurons required has to be fine-tuned unlike numerous parameters in MLP. To disseminate, its use to wider audience in remote sensing field, its implementation in MATLAB in a Graphical User Interface (GUI) is described. The developed GUI is capable of handling large image files by employing a smarter technique of supplying rectangular chunk of image data through object oriented image adapter class and provides a simple and effective computation environment for performing ELM classification with accuracy assessment.

This paper provides insights into the feasibility of clean energy sources for light utility vehicles (LUVs). First, energy analysis for the fleet of LUVs for a small college are presented. Secondly, the energy implications for a larger (>100) fleet of LUVs, and finally for the whole of the United States are presented. The technologies discussed include producing pure hydrogen, leaving no carbon footprint and replacing the internal combustion engine or the battery powered drive system with fuel-cell engines. Except for the clean production of usable amounts of hydrogen, all other processes are developing, but proven technologies. The possibilities of the transition from fossil fuel to hydrogen powered LUVs is limited by hydrogen production technology and fuel cell costs. These limitations will be addressed. The paper will conclude by analyzing the fossil fuel savings associated with a transition to hydrogen fuel for small, intermediate and large scale fleets of LUVs.

This paper estimates the inefficiencies associated with the regionalisation of milk quota trade. An optimisation model is developed to estimate the economic value of quota. Quota values are aggregated to derive supply and demand curves under two scenarios; first where quotas can trade nationally and second where the trade of quota is regionally restricted. Quota trade is simulated and the consequent effects on supplier structure are estimated. Through the derivation of sectoral cumulative cost curves it is possible to estimate the impact of regionalising quota trade on sector efficiency. The model is solved using National Farm Survey data from Ireland and the inefficiencies of regionalised quota trade in Ireland is estimated at €20 million. The model is also used to quantify the effect of policy uncertainty on quota trade. The implications of an early abolition or expansion of the EU milk quota on quota trade is quantified. The paper concludes by discussing the implications of restricted quota trade, especially in the context of eventual quota removal.

In Ireland, all direct payments made to farmers were completely decoupled from production in January 2005. A single payment is paid to the farmers based on payments they received in a historical reference period. There have been earlier studies on possible impacts of decoupling on Irish farms (Breen et al., 2005; Breen and Hennessy 2003). The results from these studies showed that decoupling was likely to accelerate the pace of structural change in Irish farming for instance, thirtytwo percent of dairy farms were projected to exist the sector and ten percent of cattle farms are likely to become entitlement farmers that is using their land to claim the decoupled payment but not actually produce any tangible products. However, these studies took a generalized view of farms in Ireland and didn’t address the regional differentiation that may arise as a result of decoupling. It is fair to say that the impact of a policy change may be different at different regional levels. Any possible changes especially land use and milk quota structures are highly depended on geographical location of farms. For example, milk quota trade in Ireland is restricted within a region or a co-operative. This paper describes a methodology that was used in a study to determine impacts of decoupling of farm payments at the regional level in Ireland and provides an example with the results from one of the regions.

This paper uses National Farm Survey data to simulate a market for milk quota in Ireland. Price and cost projections are used to estimate the maximum affordable price farmers could pay for milk quota and the minimum price they should accept to sell quota under different policy scenarios assuming that all farmers are profit maximisers. By aggregating these prices, national demand and supply curves for milk quota are estimated. The results show that the demand for milk quota is highly dependent on individual farmer’s ability to expand and that the first 10 percent of milk quota would be traded at a very high price. The results show that in the absence of any trade liberalising policy reforms that the national equilibrium price for milk quota would be approximately 15 cent per litre assuming that the national milk quota remains binding until 2014. It should be noted that the result is normative and therefore is highly sensitive to the profit maximisation assumption.

The influence of film formation on light-trapping properties of silicon thin-film solar cells prepared on randomly textured substrates was studied. Realistic interface morphologies were calculated with a three-dimensional (3D) surface coverage algorithm using the measured substrate morphology and nominal film thicknesses of the individual layers as input parameters. Calculated interface morphologies were used in finite-difference time-domain simulations to determine the quantum efficiency and absorption in the individual layers of the thin-film solar cells. The investigation shows that a realistic description of interface morphologies is required to accurately predict the light-trapping properties of randomly textured silicon thin-film solar cells.

SUMMARYEight canopy heights, maintained by weekly cutting, were compared during summer and early autumn on a perennial ryegrass (Lolium perenne L.)-white clover (Trifolium repens L.) sward.Perennial ryegrass adapted to a taller canopy by increasing the length of its leaf blades much more than it increased the length of its leaf sheaths, and by increasing the length of its blades proportionately more than their width. White clover adapted by increasing the length of its petioles much more than it increased the length of its leaflets. Canopy height did not affect the number of ryegrass leaves emerging or dying per tiller or the number of live, emerged leaves maintained by a tiller. The amount of herbage harvested at the weekly cuts was largely unaffected by canopy height once the swards had adapted to the particular management. Leaf blades in the taller canopies, therefore, lost a much lower proportion of their length to defoliation than those in the shorter canopies. Consequently, the length of blade dying per tiller per week was more strikingly affected by canopy height than was the rate of leaf extension. The increasing amount of material lost by death with increasing canopy height was confirmed by the weights of senescent and dead tissue collected weekly from a fixed area in each plot. Herbage in the lower compared with the upper layers of the taller canopies was much less digestible and lower in N content.

This is the final report on this deliverable. It presents a methodological description of the sector model, CAPRI, and the scenarios used to examine legume production under three different pathways which were assumed to be the conditions which would lead to increase legume production in the EU27+UK. Three alternative legume production scenarios have been identified and described including changes in legume support payment (policy), dietary change (consumer demand) and soya import ban (trade). The scenario results were compared with a baseline scenario, analysed and presented in this report.