Farm Surveys
The Farm Surveys Research Department has 25 staff members and is responsible for the National Farm Survey (NFS), which is the longest running research project in Teagasc, having first been undertaken in the mid-1960’s. The Surveys Department is also responsible for delivering Ireland’s statutory data on farm output, costs and incomes on an annual basis to the EU-Farm Accountancy Data Network (FADN) in Brussels. Additional surveys are also carried out on the NFS sample in Summer/Autumn of each year. The main aim of the National Farm Survey is to determine the financial situation across the broad spectrum of Irish farms by system and size.
Recent Submissions
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Afforestation: Replacing livestock emissions with carbon sequestrationIn Ireland, agriculture accounts for 33% of national greenhouse gas (GHG) emissions. Ireland faces significant challenges in terms of emissions reduction and is well off course in terms of meeting binding European Union targets. Flexibility mechanisms will allow Ireland to offset 5.6% of its commitment via sequestration in biomass and soils and land use change. Agricultural emissions in Ireland are largely driven by livestock production. As such, the purpose of this research is to estimate the net GHG emission benefit resulting from a land use change with forest replacing livestock systems (dairy, beef cattle and sheep). We estimate the total carbon sequestration in biomass and harvested wood products, along with the total emissions avoided from each livestock system on a per hectare basis. In addition, the paper compares the social cost of carbon to the average income per hectare of each livestock system. Finally, a hypothetical national planting scenario is modelled using plausible planting rates. Results indicate that the greatest carbon benefit is achieved when forest replaces dairy production. This is due to high emissions per hectare from dairy systems, and greater sequestration potential in higher-yielding forests planted on better quality soils associated with dairy production. The inclusion of harvested wood products in subsequent rotations has the potential to enhance GHG mitigation and offset terrestrial carbon loss. A hypothetical national planting scenario, afforesting 100,000 ha substituting dairy, beef cattle and sheep livestock systems could abate 13.91 Mt CO2e after 10 years, and 150.14 Mt CO2e (unthinned plantations) or 125.89 Mt CO2e (thinned plantations) over the course of the rotation. These results highlight the critical role for forest land use change in meeting the urgent need to tackle rising agricultural emissions.
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Analysis of the effect of alternative agri-environmental policy instruments on production performance and nitrogen surplus of representative dairy farmsNitrogen (N) surplus is an important environmental problem on the island of Ireland (Northern Ireland and the Republic of Ireland), and the dairy sector has been identified as contributing more to this problem compared to other agricultural sectors. As a result, there has been increased demand for efficient policy measures to improve the economic and environmental performance of dairy farms in the region. In this study, we employed the positive mathematical programming (PMP) optimization modelling framework to simulate the economic and environmental impact of two alternative agri-environmental policy instruments on different dairy farm types. Specifically, the study considers the effects of an N surplus tax and an agri-environmental nutrient application standard on the production performance and N surplus of representative dairy farms using scenario analyses. The results of the analyses showed that the effects of the agri-environmental policy instruments vary across the two countries and clusters of dairy farms, resulting in clear differential effects on farm structure and N surpluses. The study concluded that in situations where the nutrient surplus is already high, as with the large farms clusters in this study, the use of manure application standards will be more effective in limiting nutrient surplus to soils compared to the use of nutrient surplus tax.
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More than two decades of Agri-Environment schemes: Has the profile of participating farms changed?The agri-food sector is under increased pressure from consumers to improve on the sustainability of production processes. Policies that incentivise farmers to improve environmental performance, such as agri-environment schemes (AES), are increasingly important. Understanding the choice to participate in these programmes aids policymakers in designing schemes that meet participation and environmental goals. While a number of studies have investigated the decision using cross-sectional data on one or multiple locations, very few have used longitudinal data to investigate the impact of institutional changes over time. Using Ireland as a case study, this paper uses a nationally representative panel of data spanning 23 years to model the impact of scheme and policy changes on the type of farms participating in AES. This paper argues that environmental issues surrounding intensive farms (such as the loss of nutrients and sediment to water and greenhouse gas emissions) are not being optimally addressed in scheme design and further development of such programmes is needed to reduce negative environmental impacts.
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The spatial impact of rural economic change on river water qualityThis paper, using Ireland as a case study, examines the relationship between rural economic activities and river water quality. The stipulation from the EU water framework directive (WFD) that all surface waters in the EU must be of ‘good ecological status’ necessitates a quantitative understanding of the major determinants of water quality. Within this context, this paper combines a number of spatial datasets relating to agricultural, land use, residential and industrial activities, to examine the major economic influences on the ecological quality of water resources. It is hoped that providing a comprehensive understanding of the effect of a variety of economic activities that influence the ecological quality of water will be an important tool in the management of risk and will allow for more appropriate land use planning aimed at restoring and maintaining water quality as required by the WFD. Results indicate that the level of forestry, industrial activity, the intensity and type of agricultural activity and the type of wastewater treatment in an area are all critical factors affecting the quality of water resources. The model finds that relationship between agriculture and water quality improved over time during a period where there was substantial legislative measures and financial support to facilitate improved water quality.
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Comparing economic performance with greenhouse gas emissions and nitrogen surplus on Irish FarmsThe need to reduce the environmental footprint of agricultural production is widely recognised. At the same time, agricultural production must be sufficient to feed the expanding human population. It has been argued that this production can be achieved through sustainable intensification, with efficient intensive farms optimal for both environmental and economic performance. This paper explores this concept by comparing farm financial performance (gross margins per hectare and family farm income per labour unit) with two key environmental metrics, agricultural greenhouse gas emissions and nitrogen surpluses, on Irish farms from the 2015 Teagasc National Farm Survey. Overall, farms with better economic performance tend to have lower emissions per unit agricultural output, and obtain more agricultural output per kg surplus nitrogen applied. However, the intensive production on these economically better performing farms is also associated with greater emissions and nitrogen surpluses per hectare farmed. These results are discussed in the context of current debate surrounding agricultural policy in Ireland, where ambitions to increase agricultural production will be challenged to meet environmental targets, and in relation to wider debates around the best path for sustainable agricultural production.
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Establishing nationally representative benchmarks of farm-gate nitrogen and phosphorus balances and use efficiencies on Irish farms to encourage improvementsAgriculture faces considerable challenges of achieving more sustainable production that minimises nitrogen (N) and phosphorus (P) losses and meets international obligations for water quality and greenhouse gas emissions. This must involve reducing nutrient balance (NB) surpluses and increasing nutrient use efficiencies (NUEs), which could also improve farm profitability (a win-win). To set targets and motivate improvements in Ireland, nationally representative benchmarks were established for different farm categories (sector, soil group and production intensity). Annual farm-gate NBs (kg ha−1) and NUEs (%) for N and P were calculated for 1446 nationally representative farms from 2008 to 2015 using import and export data collected by the Teagasc National Farm Survey (part of the EU Farm Accountancy Data Network). Benchmarks for each category were established using quantile regression analysis and percentile rankings to identify farms with the lowest NB surplus per production intensity and highest gross margins (€ ha−1). Within all categories, large ranges in NBs and NUEs between benchmark farms and poorer performers show considerable room for nutrient management improvements. Results show that as agriculture intensifies, nutrient surpluses, use efficiencies and gross margins increase, but benchmark farms minimise surpluses to relatively low levels (i.e. are more sustainable). This is due to, per ha, lower fertiliser and feed imports, greater exports of agricultural products, and for dairy, sheep and suckler cattle, relatively high stocking rates. For the ambitious scenario of all non-benchmark farms reaching the optimal benchmark zone, moderate reductions in farm nutrient surpluses were found with great improvements in profitability, leading to a 31% and 9% decrease in N and P surplus nationally, predominantly from dairy and non-suckler cattle. The study also identifies excessive surpluses for each level of production intensity, which could be used by policy in setting upper limits to improve sustainability.
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Can technology help achieve sustainable intensification? Evidence from milk recording on Irish dairy farmsThis article explores the potential of a farm technology to simultaneously improve farm efficiency and provide wider environmental and social benefits. Identifying these ‘win-win-win’ strategies and encouraging their widespread adoption is critical to achieve sustainable intensification. Using a nationally representative sample of 296 Irish dairy farms from 2015, propensity score matching is applied to measure the impact of milk recording on a broad set of farm sustainability indicators. The findings reveal that the technology enhances economic sustainability by increasing dairy gross margin and milk yield per cow. Furthermore, social sustainability is improved through a reduction in milk bulk tank somatic cell count (an indicator of animal health and welfare status). Conversely, milk recording (as it is currently implemented) does not impact farm environmental sustainability, represented by greenhouse gas emission efficiency. While the study shows that milk recording is a ‘win-win’ strategy, ways of improving current levels of utilisation are discussed so that milk recording achieves its ‘win-win-win’ potential in the future.
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AGMEMOD Outlook for Agricultural and Food Markets in EU Member States 2018-2030Policy, administration and industry need medium-term projections of the expected developments in the agri-food markets for their decision-making processes. The EU Commission presents such projections for the EU as a whole in December of each year. Those projections and their assumptions regarding policy and macroeconomic developments are depicted to the level of individual EU Member States with the exception of Luxembourg, which is included in the figures of Belgium, by applying the partial equilibrium model AGMEMOD. The working paper briefly describes the approach to establish projections for the EU Member States. The projections cover the markets of main agricultural products, in particular for cereals and oilseeds (rapeseed and sunflower seed), livestock (cattle, pigs, goats and sheep), meat (beef, pork, and poultry), milk and dairy products (drinking milk, butter, cheese, skimmed milk powder, whole milk and semiskimmed milk powder). The outcomes comprise items like areas, livestock numbers, yields, production, trade and use, as well as prices. The individual projection results are displayed in tables.
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Crop Costs and Returns 1994The Teagasc Crops Costs & Returns are intended as an indicative guide to crop margins; however land suitability, rotation, risk avoidance and husbandry skills must also be considered.
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Crop Costs and Returns 1996The Teagasc Crops Costs & Returns are intended as an indicative guide to crop margins; however land suitability, rotation, risk avoidance and husbandry skills must also be considered.
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Crop Costs and Returns 1997The Teagasc Crops Costs & Returns are intended as an indicative guide to crop margins; however land suitability, rotation, risk avoidance and husbandry skills must also be considered
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Crop Costs and Returns 1999The Teagasc Crops Costs & Returns are intended as an indicative guide to crop margins; however land suitability, rotation, risk avoidance and husbandry skills must also be considered.
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Crop Costs and Returns 2000The Teagasc Crops Costs & Returns are intended as an indicative guide to crop margins; however land suitability, rotation, risk avoidance and husbandry skills must also be considered
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Teagasc National Farm Survey 2016 EstimatesBackground Notes: The National Farm Survey (NFS) has been conducted by Teagasc on an annual basis since 1972. The survey is operated as part of the Farm Accountancy Data Network of the EU and fulfils Ireland’s statutory obligation to provide data on farm output, costs and income to the European Commission. A random, nationally representative sample is selected annually in conjunction with the Central Statistics Office (CSO). Each farm is assigned a weighting factor so that the results of the survey are representative of the national population of farms. These preliminary estimates are based on a sub sample of 805 farms which represents 83,377 farms nationally. Farms are assigned to six farm systems on the basis of farm gross output, as calculated on a standard output basis. Standard output measures are applied to each animal and crop output on the farm and only farms with a standard output of €8,000 or more, the equivalent of 6 dairy cows, 6 hectares of wheat or 14 suckler cows, are included in the sample. Farms are then classified as one of the six farm systems on the basis of the main outputs of the farm. Farms falling into the Pigs and Poultry System are not included in the survey, due to the inability to obtain a representative sample of these systems. Due to the small number of farms falling into the Mixed Livestock system these farms are not reported here.
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Teagasc National Farm Survey Preliminary Estimates 2016This presentation provides an overview of the preliminary results of the National Farm Survey for 2016
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A national methodology to quantify the diet of grazing dairy cowsThe unique rumen of dairy cows allows them to digest fibrous forages and feedstuffs. Surprisingly, to date few attempts have been made to develop national methods to gain an understanding on the make-up of a dairy cow's diet, despite the importance of milk production. Consumer interest is growing in purchasing milk based on the composition of the cows' diet and the time they spend grazing. The goal of this research was to develop such a methodology using the national farm survey of Ireland as a data source. The analysis was completed for a 3-yr period from 2013 to 2015 on a nationally representative sample of 275 to 318 dairy farms. Trained auditors carried out economic surveys on farms 3 to 4 times per annum. The auditors collected important additional information necessary to estimate the diet of cows including the length of the grazing season, monthly concentrate feeding, type of forage(s) conserved, and milk production. Annual cow intakes were calculated to meet net energy requirements for production, maintenance, activity, pregnancy, growth, and live weight change using survey data and published literature. Our analysis showed that the average annual cow feed intake on a fresh matter basis ranged from 22.7 t in 2013 to 24.8 t in 2015 and from 4.8 to 5 t on a dry matter basis for the same period. Forage, particularly pasture, was the largest component of the Irish cow diet, typically accounting for 96% of the diet on a fresh matter basis and 82% of dry matter intake over the 3 yr. Within the cows' forage diet, grazed pasture was the dominant component and on average contributed 74 to 77% to the average annual cow fresh matter diet over the period. The proportion of pasture in the annual cow diet as fed was also identified as a good indicator of the time cows spend grazing (e.g., coefficient of determination = 0.85). Monthly, forage was typically the main component of the cow diet, but the average contribution of concentrate was substantial for the early spring months of January and February (30 to 35% of dry matter intake). Grazed pasture was the dominant source of forage from March to October and usually contributed 95 to 97% of the diet as fed in the summer period. Overall, the national farm survey from 2013 to 2015 shows that Irish dairy farms are very reliant on forage, particularly pasture, regardless of whether it is reported on a dry matter basis or as fed. There is potential to replicate this methodology in any regions or nations where representative farm surveys are conducted.
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GENEDECGENEDEC was a European project funded under the 6th Framework. It was co-ordinated by INRA Grignon with ten European partners and a time frame of 42 months. The purpose of the project was to conduct a quantitative and qualitative assessment of the socio-economic and environmental impacts of the decoupling of direct payments on agricultural production, markets and land use in the EU. It was envisaged that the pan-EU nature of the project would facilitate an international comparison of the effects of decoupling and would provide policy makers with sufficient information to identify the key winners and losers from decoupling throughout the EU. The project aimed to provide insights into the workability of decoupling and its impacts, and to analyse alternative policy options to improve the agricultural support system. Specifically, through the use of farm level models, this project estimated the effects of existing and proposed decoupled support schemes on production, land use and land prices and the implications for farm incomes and the future structural development of farms. The project was divided into 9 Work Packages depending on objectives and time frame of the project. The main role of RERC Teagasc was in Work Package 2 which aimed to develop farm level mathematical models and used the models developed to determine the impact of decoupling on Irish farms. The work in RERC started in November 2004 and ended in May 2006. A brief description of the models developed and results generated by RERC is provided here.
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Work-related musculoskeletal disorders among Irish farm operatorsBackground- To establish prevalence, risk factors and impact of work-related musculoskeletal disorders (WMSDs) among farmers in Ireland. Methods- In summer 2009, a questionnaire was appended to the Teagasc (Irish Agricultural and Food Development Authority) National Farm Survey (n=1110) to obtain data on the prevalence, risk factors and impact of WMSDs amongst farm operators in Ireland. Data were collected by trained recorders and analyzed using chi-square tests, t-tests, Mann-Whitney tests and binary logistic regression. Results- The prevalence of WMSDs in the previous year was 9.4% (n=103), with the most commonly affected body region being the low back 31% (n=32). Nearly 60% (n=57) of farmers reported missing at least a full day’s work as a consequence of their WMSD. Personal factors evaluated using bivariate regression analysis, were found not to influence whether or not a farmer experienced a WMSD. However, work-related factors such as larger European Size Units (ESUs) (OR=1.007, CI=1.002-1.012), greater number of hectares farmed (OR=2.50, CI=1.208-4.920), higher income (OR=1.859, CI=1.088-3.177), dairy enterprise (OR=1.734, CI=1.081-2.781), and working on a fulltime farm (OR=2.156, CI=1.399-3.321) increased the likelihood of experiencing a WMSD. The variable ‘fulltime farm’ which was associated with a higher labour unit requirement to operate the farm, was the only factor found to independently predict WMSDs in the multivariate regression analyses. Conclusions- This study suggests that the prevalence of WMSDs can be reduced by the application of improved farm management practices. A more detailed examination of the risk factors associated with WMSDs is required to establish causality and hence, effective interventions.
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Situation and Outlook in Agriculture 2008/09CONTENTS: (1)Farm Incomes 2007; (2) Investment in Agriculture 2008/09: Dairying, Cattle, Sheep, Pigs, Tillage, Forestry