Development of agri-environmental indicators to assess dairy farm sustainability in Quebec,Eastern Canada

Agri-environmental indicators are commonly used to assess agricultural sustainability. In North America, few are designed to be easily used by dairy farmers. As farmers assume more responsibility for managing natural resources, they play an increasingly important role in assessing sustainable agriculture. This paper describes the development of an indicator-based self-assessment tool for use at the farm level to evaluate dairy farm sustainability from an environmental standpoint. The agri-environmental indicator set was selected by using two participatory processes: the Delphi method and a focus group. The framework for developing the assessment tool consisted of six steps: (1) Defining the concept of environmental sustainability at the farm level; (2) setting up goals and principles for the assessment; (3) identifying potential indicators and selecting candidate indicators; (4) defining reference values, aggregating indicators into components, and establishing relative weights for indicators; (5) testing the candidate indicators on dairy farms, and (6) selecting the final indicator set. Six criteria were used to evaluate either the practicality or usefulness of indicators. Thirteen indicators were chosen, one of which was divided into four sub-indicators. These indicators were aggregated into four components: soil quality, cropping practices, fertilization management, and farmland management. Expert participation was the first validation of the indicator set. A compromise between feasibility, practicality, and relevance of measurement was found among indicators. When applied to 40 farms over two contrasting regions, the indicator set identified scores that differed according to production context. The tool is user-friendly and well-adapted to dairy farming systems.     

Development of a nature value index for pastoral farmland—A rapid farm-level assessment

Sustainable agriculture is important for the safeguarding of natural resources (e.g. semi-natural habitats, clean water and energy), food production and for the survival of rural communities. As part of the EU strategy towards sustainability Member States are committed to identifying and protecting areas of agrobiodiversity. Identification of the extent and support of High Nature Value (HNV) farmland across the EU was an important policy requirement of Member States Rural Development Programmes (RDP) (2007–2013) but problems defining the extent of HNV farmland have delayed progress to date. Following a five step statistical process, we developed a simple 10 point nature value index based on percentage improved agricultural grassland, stocking density (LU/ha Utilisable Agricultural Area) and length of linear habitats per hectare on a farm. We propose an index that can be used to highlight farms with low biodiversity allowing targeting of sustainability measures such as increasing field boundary area or reducing inorganic Nitrogen inputs, farms that are already sustainable from a biodiversity perspective, and could be labelled as such through national programs or even farms that are High Nature Value (HNV) and should be targeted through results-based agri-environment schemes. This nature value index has potential to be applied to a range of farmed pastoral landscapes in North West Europe's Atlantic biogeographic region. The methodology used in the development of the index has the potential to be used in other biogeographic zones to develop similar indices of nature value at farm level. This index is a simple to use, easily accessible identification tool based on farm-level data which can be utilised in sustainability indices and HNV farmland identification.     

Empirical evaluation of sustainability of divergent farms in the dryland farming systems of India

The present study argues that there are heterogeneous farm systems within the drylands and each farm system is unique in terms of its livelihood asset and agricultural practice, and therefore in sustainability. Our method is based on household survey data collected from 500 farmers in Anantapur and Kurnool Districts, in Andhra Pradesh State of India, in 2013. We carried out principal component analysis (PCA) with subsequent hierarchical clustering methods to build farm typologies. To evaluate sustainability across these farm typologies, we adopted a framework consisting of economic, social and environmental sustainability pillars and associated indicators. We normalized values of target indicators and employed normative approach to assign different weights to these indicators. Composite sustainability indices (CSI) were then estimated by means of weighted sum of indicators, aggregated and integrated into farm typologies. The results suggested that there were five distinct farm typologies representing farming systems in the study area. The majority of farms (>70%) in the study area are small and extensive (typology 1); marginal and off farm based (typology 2). About 20% of the farms are irrigation based and intensive (typology 3); small and medium and off farm based (typology 4) and irrigation based semi-intensive (typology 5). There was apparent variability among farm typologies in terms of farm structure and functions and composite sustainability indices. Farm typologies 3 and 5 showed significantly higher performances for the social and economic indices, while typologies 2 and 4 had relatively stronger values for environment. These discrepancies support the relevance of integrated farm typology- and CSI approaches in assessing system sustainability and targeting technologies. Universally, for all farm typologies, composite sustainability indices for economic pillar was significantly lower than the social and environment pillars. More than 90% of farmers were in economically less-sustainable class. The correlations between sustainability indices for economic and environment were typology specific. It was strong and positive when aggregated for the whole study systems [all samples (r = 0.183; P < 0.001)] and for agriculture dependent farm typologies (e.g. typologies 1 and 3). This suggests the need to elevate farms economic performance and capacitate them to invest in the environment. These results provide information for policy makers to plan farm typology–context technological interventions and also create baseline information to evaluate sustainability performance in terms of progress made over time.     

An indicator-based method for quantifying farm multifunctionality

Production of food and fibres has traditionally been the main function of agriculture. In the last decades an increased focus on the importance of other functions has been discussed within the framework of agricultural and general land use multifunctionality. To a large extent farmers’ decisions and actions determine which functions their farming practices support. The extent of the production function is straightforward to identify and quantify but problems persist in rating functions such as ecosystem maintenance, housing, and amenity values.This paper presents a method to quantify and compare multifunctionality at farm level. Four main farm functions–production, residence, provision of wildlife habitats, and recreation–are selected to describe multifunctionality. In the quantification process indicators are identified to produce four aggregated function scores based on farm characteristics and activities. The farm data that support the indicators is derived from an interview survey conducted in 2008.The aggregated function scores vary with farm size as well as farm type; smaller, hobby-based farms in general score highest in the residence function whereas bigger, full-time farms score highest in the production, wildlife habitat, and recreation functions. This suggests that trade-offs between production development on the one side and environmental and recreational concerns on the other side may not be as high as expected. Farm of sizes 50–100 ha showed the highest multifunctionality–in this paper described as balance among functions–whilst smaller and bigger farms were biased towards mainly residence and production concerns, respectively.Challenges in quantifying functions still persist, but the suggested approach offer a method by which functionality can be compared among farms and among functions. Knowledge on the functional focus at farm level may assist both farmers and spatial planners in decision making regarding future management of agricultural landscapes.     

Assessment of sustainable development in the EU 27 using aggregated SD index

In the European Union the sustainable development is a fundamental and overarchingobjective enshrined in the Treaty and measuring progress towards sustainable development is an integral part of the EU Sustainable Development Strategy. Eurostat produce a monitoring report every two years based on the EU set of sustainable development indicators (SDIs). The main objective of this paper is to create an aggregated index of the sustainable development from EU set of SDIs for each 27 EU country based on the PCA. The headline indicator economic growth was not involved because its increase is not expressly followed by positive change in other SDIs from social, economic and environmental fields. The aggregated SD index enables to get an overall picture about the position of each of the 27 EU countries and its development in terms of the sustainability over time as assumed in the EU Sustainable Development Strategy. Sweden, Denmark, Netherland, and Great Britain have repeatedly reached the highest value of aggregated SD index. The highest positive change in the aggregated SD index has occurred in countries with the lowest value of aggregated SD index. Moreover, we put this new aggregated index in relation with economic growth and found that there is a negative correlation between aggregated SD index and the economic growth for most of the 27 EU countries.     

Integrated assessment of agricultural production practices to enhance sustainable development in agricultural landscapes

This study presents an integrated assessment approach for the sustainable development of agricultural landscapes. The approach evaluates single agricultural production practices by means of environmental, economic and social indicators. To implement the approach, a mixed method was employed that combines modelling techniques and survey methods. The economic and environmental indicators were implemented within the bio-economic modelling system MODAM (Multi-Objective Decision support system for Agro-ecosystem Management) in order to assess economic performance and the effects on the abiotic and biotic environments. The modelling approach was applied to a case study in a region of north-eastern Germany, within the state of Brandenburg. In addition, the acceptance by farmers of different production alternatives that are known to have environmental benefits was examined in the case study. To allow for a direct comparison between different indicators, the results of the assessment are dimensionless index values that indicate the suitability of certain agricultural production practices with respect to an indicator. The indicator-related indices are then aggregated into an overall index of sustainability differentiating between ‘strong’ and ‘weak’ sustainability. Results are presented for exemplarily chosen production practices for sugar beet, potato and winter rape production and set aside. Depending on the underlying concept of sustainability (‘weak’ vs. ‘strong’), different production practices were identified as the most suitable ones in a given situation. This integrated assessment enables determination of positive and negative correlations between indicators. The approach allows for the identification of production alternatives that are assessed to be economically and environmentally beneficial as well as socially accepted, although at different levels.     

Co-construction of an assessment method of the environmental sustainability for cattle farms involved in a Protected Designation of Origin (PDO) cheese value chain,Cantal PDO

In France, numerous Protected Designation of Origin (PDO) cheese value chains have revised their specifications to address environmental protection, particularly at the farm level. In this stage, it is nevertheless impossible to state whether the proposed modifications may ensure the sustainability of environmental protection as no environmental sustainability diagnostic has been conducted. The aim of this study is to construct an assessment method for the Cantal PDO farms.A multi-criteria assessment approach was implemented in the following 5 steps: definition of the framework of the study, determination of the principles and criteria, definition of the indicators, aggregation of all elements of the assessment, and finally, test of the assessment method on farms. Focus groups meetings were organised for the first four steps. The panel discussions were based on data obtained from both the literature and surveys of stakeholders operating in the value chain and within the territory.The obtained assessment method comprises 4 principles characterised by 33 indicators. The most important principle (45%), management of grassland resources, is a key economic and environmental point of the studied farms. It reflects the necessary intensive use of grass by the animals in the PDO farms. Few existing methods addressed this principle that required the design of several new indicators. The second principle, impact of agricultural practices (25%), is often included in environmental sustainability assessment methods The adopted indicators are, thus, drawn from existing methods and adapted to the context of the farms studied. The management of the farm buildings and the landscape principle (18%) is often considered in social sustainability. Its role in environmental sustainability can be explained by its strong link with the image of PDO products. Primarily drawn from the literature, the used indicators have been extended to make the assessment method as objective as possible. Finally, the management of local, energy and water resources principle has the lowest weighting (12%). This can be explained by the limited number of indicators.This assessment method was constructed for the Cantal PDO farms by considering their environment and particularities. In consequence, the stakeholders have taken ownership of it. It could be used by other ruminant systems based on grassland. The development of numerous indicators enhanced the pool of existing indicators. This assessment method was sensitive and allowed for the discrimination between farms.     

An overview of sustainability assessment methodologies

Sustainability indicators and composite index are increasingly recognised as a useful tool for policy making and public communication in conveying information on countries and corporate performance in fields such as environment, economy, society, or technological improvement. By visualizing phenomena and highlighting trends, sustainability indicators simplify, quantify, analyse and communicate otherwise complex and complicated information.There are number of initiatives working on indicators and frameworks for sustainable development (SD). This article provides an overview various sustainability indices applied in policy practice. The paper also compiles the information related to sustainability indices formulation strategy, scaling, normalisation, weighting and aggregation methodology.     

Development and application of an integrated sustainability index for small-holder dairy farms in Rajasthan,India

In agrarian economy of developing nations like India, smallholder dairy production is an important enterprise and its sustainability is vital for ensuring livelihood and nutritional security to the masses. Studies on methodological aspects of farm sustainability at micro-level are limited, either confined to a particular dimension of sustainability or based on complex data requirement which is not feasible to obtain in the context of smallholder dairy farms. This study has developed a multi-attribute farm level sustainability assessment method encompassing economic, social and ecological dimensions of sustainability and has applied it to assess the sustainability of dairy farming in north-western part of India. Based on data from 120 dairy farms located in rural area of Jaipur district from the state of Rajasthan, the study computed the composite Sustainable Dairy Farming Index (SDFI). The overall substantiality status of the smallholder dairy farms in the study area was not encouraging, implying that it may not be viable for future generation to take up the enterprise. Among the three dimensions of sustainability, the average scores of ecological dimension were highest followed by the economic and social sustainability scores. Some of the core attributes like feed productivity, management of animal genetic potential and gender equality are particularly weak aspects of the dairy production system in India. The direct relationship of economic sustainability with herd size suggests for farmers with very small herds (one to two) animals, increasing the number of dairy animals to about five to six, would be a good strategy to economize on input costs and generate more marketed surplus of milk.     

Data strategy for environmental assessment of agricultural regions via LCA: case study of a French catchment

Purpose

Various approaches have been carried out to extrapolate environmental assessments of farms to the regional level, some of them oversimplified and thus leading to high uncertainty. Key challenges include selection of a representative sample, construction of a farm/land use typology, the extrapolation strategy and dealing with data limitations. This work proposes a method for addressing these issues by means of statistically supported approaches.

Methods

We applied a novel approach combining a sampling strategy, estimation of farm-level environmental impacts via life cycle assessment (LCA), a farm typology based on principal component analysis, a statistical method for extending the farm sample given data constraints and finally linear extrapolation based on regional production and land use, taking into account the regional import–export balance. The approach was applied to a French case study, the Lieue de Grève catchment in the dairy-intensive Brittany region. A decision flowchart was developed to generalise the approach for similar applications dealing with farm and LCA data constraints. Additionally, innovative farm practices were modelled and their impacts propagated to the regional level.

Results and discussion

The typology developed identified “dairy”, “beef”, “dairy + beef” and “swine” farms as the dominant farm types in the region. While swine farms had the highest mean impacts per hectare, dairy and dairy + beef farms had impacts two to five times as high as those of beef and swine farms, when extrapolated to the entire catchment. Multiple linear regressions based on an extended farm and LCA dataset were used to predict environmental impacts of dairy farms lacking LCA results, thus increasing their sample size before extrapolation. The inclusion of farm and LCA data from a neighbouring region did not contribute to the accuracy of predicted impacts, as determined by comparing them to those of the farm closest to the dairy cluster’s centre, but rather produced significantly larger coefficients of variation. Results of tests of including two extra-regional farm and LCA datasets helped determine decision rules for the decision flowchart. Modelling of innovative agricultural practices yielded regional impacts consistent with previous estimates.

Conclusions

This approach provides a generalisable approach for farm typologies, data handling and regional extrapolation of farm-level LCAs, applicable to estimate environmental impacts of any agricultural area if requirements of a representative farm sample are met. We demonstrate the utility of the method for estimating effects of innovative agricultural practices on a region’s impacts by modelling practices on virtual farms and extrapolating their results.

     

A methodological approach to assess and compare the sustainability level of agricultural plant production systems

A large number of indicators have been developed, in order to assess agricultural sustainability. However, there is no unified theoretical basis for the creation of a scientifically substantiated system of indicators and especially for data collection, analysis, scale and final goal. This paper proposes a methodological approach to assess and to compare the sustainability level of agricultural plant production systems on regional scale combining the three pillars of sustainability environment, economy and society. The combination of 21 individual indicators expressed a unique indicator was realized using the Multiattribute Value Theory (MAVT). The proposed methodology was testified on two geographical regions in Greece, through an empirical study, utilizing questionnaires completed during interviews with farm managers. The questionnaire was designed to gather data on current agricultural practices applied in each particular region and was separated into three broad groups of questions concerning (a) crop management practices, (b) economic performance and (c) social characteristics of each farm. The results of our study demonstrate the overall status of the studied regions, regarding their level of agricultural sustainability. Finally, findings related to the acceptability of the proposed methodological framework were discussed.     

Comparison of methods for calculation of sustainability indices for alternative sewerage systems—Theoretical and practical considerations

City planners need practical methods to assess and compare the sustainability of different alternatives for urban infrastructure. This article presents the consequences of selecting different methods to normalize the values of sustainability indicators, and the influence of selecting different indicators and different weighting techniques. Chosen indicators represent use of resources, environment, health and safety, psycho/sociological situation. Infrastructure costs are not included in the indicators, since it is more convenient to weigh them against the sustainability indices of the different systems. All indicators are aggregated into one system index. A nature-based sewerage system is compared to a conventional system. The article demonstrates that the method used to normalize the indicators, the choice of relevant indicators and the weighting technique have considerable influence on which system is found to be the more sustainable.     

Development of composite sustainability performance index for steel industry

The steel companies are becoming increasingly aware about the sustainability challenges. In order to become a responsible corporate citizen, the industry has responded to these challenges through adoption of pillars of sustainability. The industry has made the beginning with identification of sustainability indicators. The indicators have been developed specifically for steel industry. Generally, it is quite difficult to evaluate the performance of company on the basis of large number of sustainability indicators. Integration of key sustainability indicators is quite essential for decision-making. Composite indicators are an innovative approach to evaluate sustainable performance. This paper presents a method for development of composite sustainability performance index (CSPI) that addresses the sustainable performance of steel industries along all the three pillars of sustainability—economic, environmental and societal. Organizational governance and technical aspects have also been considered fourth and fifth dimensions of sustainability.The objective of this paper is to introduce sustainability and to present a conceptual decision model, using analytical hierarchy process (AHP) to assist in evaluating the impact of an organization's sustainability performance. AHP has been used to determine the weights at various levels. Sub-indices have been evaluated and aggregated to form CSPI. The effectiveness of the proposed model is evaluated in a case study for a major steel company in India.     

Meta-performance evaluation of sustainability indicators

There are many different kinds of frameworks for evaluating environmental and sustainability performance at the organizational level (profit or not-for-profit, private or public), sectoral level (e.g. industry, transport, agriculture and tourism), and local, regional or country levels. Despite the diversity of methods and tools to measure sustainable development, indicators are one of the approaches most used. However, these tools do not usually include evaluation of the performance measurement instrument itself. The main objective of this research is to develop a conceptual framework to design and assess the effectiveness of the sustainability indicators themselves. To put the proposed tool into practice, a set of key good-practice factors and meta-performance evaluation indicators is proposed for adoption in a national case study—the national sustainable development indicators system, SIDS Portugal, and the usefulness of this methodology is demonstrated. This approach aims to evaluate how appropriate a set of sustainability indicators is and allow an evaluation of overall performance-monitoring activities and results. Stakeholder involvement is an essential component of the proposed framework. The tool developed could support continuous improvement in the performance of ongoing sustainability indicator initiatives, allowing greater guidance, objectivity and transparency in sustainability assessment processes.     

Integration of mental health into primary care in Sri Lanka

Introduction Sri Lanka has one of the highest suicide rates in the world, with recent protracted conflict and the tsunami aggravating mental health needs. This paper describes a project to establish a systematic “train the trainers” programme to integrate mental health into primary care in Sri Lanka''s public health system and private sector.Methods A 40 hour training programme was delivered to curriculum and teaching materials were adapted for Sri Lanka, and delivered to 45 psychiatrists, 110 medical officers of mental health and 95 registered medical practitioners, through five courses, each in a different region (Colombo, Kandy, Jaffna, Galle and Batticola). Participants were selected by the senior psychiatrist of each region, on the basis of ability to conduct subsequent roll out of the training. The course was very interactive, with discussions, role plays and small group work, as well as brief theory sessions.Results Qualitative participant feedback was encouraging about the value of the course in improving patient assessments and treatments, and in providing a valuable package for roll out to others. Systematic improvement was achieved between pre- and post-test scores of participants at all training sites. The participants had not had prior experience in such interactive teaching methods, but were able to learn these new techniques relatively quickly.Conclusions The programme has been conducted in collaboration with the Sri Lankan National Institute of Mental Health and the Ministry of Health, and this partnership has helped to ensure that the training is tailored to Sri Lanka and has the chance of long term sustainability.     

Co-construction of a method for evaluating the intrinsic quality of bovine milk in relation to its fate

There are time-tested assessments for the environmental and economic aspects of sustainability. Its societal aspect has mainly been approached through the assessment of animal welfare. However, the intrinsic quality of milk is seldom taken into account. We developed a participatory construction method for the overall assessment of intrinsic milk quality in its different dimensions (sensory, technological, nutritional and health), according to the fate of the raw milk. Two assessment models were developed, for semi-skimmed standardized ultra-high temperature (UHT) milk and for pressed uncooked non-standardized raw milk cheese. They were constructed by a participatory approach involving experts in the dairy sector with the aim to obtain a diagnostic tool that could be used in the field to help farmers to manage the quality of their milk (by prioritizing improvements on major problems). They were shaped from prerequisite specifications (limited costs and time of application, desire to obtain a transparent tool with all the steps kept visible) and current technical and scientific knowledge. They were based on indicators obtained from raw bulk tank milk analyses (30 for UHT milk and 50 for cheese assessments), which were then aggregated into criteria, principles, dimensions and overall intrinsic quality at farm level. The assessment models had parts in common, for example, same four dimensions, common indicators for health and nutritional dimensions. They also had process-specific features: units chosen, criteria, indicators and weightings in relation to the final product specifications. For instance, sensory and technological dimensions are more complex and preponderant in the cheese assessment (three principles for cheese vs one for UHT milk in both dimensions). Another example is the lack of microbial pathogens (as potential health risk for consumer) in the UHT milk assessment because of pasteurization. The assessment models then underwent a sensitivity analysis and an application in 30 farms in indoor and grazing periods to finally obtain overall UHT milk and cheese quality scores at a 1-year level. The tool was found to be applicable at farm level. However, we observed low overall quality scores with a narrow dispersion, characteristic of a severe evaluation. Even so, the assessment models showed up seasonal differences of the UHT milk and cheese quality at both overall and dimensional levels. In the light of new scientific knowledge and future quality objectives, these are adaptable to other dairy products allowing for their specific features.     

A PCA-based method for construction of composite sustainability indicators

Purpose

Sustainable manufacturing is practiced globally as a comprehensive strategy for improving the sustainability performance of the manufacturing industry. While sustainability is characterized into such three dimensions as economic, environmental, and social, currently, there is no quantitative method yet to measure the so-called ??sustainability?? in the manufacturing industry. The objective of this research is to develop a comprehensive and effective quantitative method to measure the overall sustainability performance of manufacturing companies.

Methods

In this paper, an integrated methodology is presented for the development of composite sustainability indicators based on principal component analysis (PCA). In developing this integrated approach, both industry and academia surveys are conducted to identify what sustainability indicators are favored by the sustainable manufacturing community. A unique index is then generated to measure the overall sustainability performance of industrial practices. The methodology can be used for benchmarking the overall sustainability performance of various manufacturing companies.

Results

A case study is conducted on a total of 11 global electronic manufacturing companies. The overall sustainability performance of these companies are measured, benchmarked, and ranked. The results showed that PCA is an effective approach for constructing composite sustainability indicators across environmental, economic, and social dimensions.

Conclusions

From this research, it is found that industry and academia have different views on the sustainability measurement, evidenced by different weights put on the same indicator in industry and academia. The case study demonstrated that the methodology presented in this paper is an effective tool for comprehensive measurement of sustainability performance of manufacturing companies. Strengths and weaknesses of each company can be identified. Then, the recommended improvements can be suggested based on the study of each of the individual indicators.     

Comparison of farm-level greenhouse gas emissions in transhumance and semi-intensive sheep production systems in continental rangelands

Despite their predominance worldwide, few studies have been conducted to look at the impact of sheep production systems relying on transhumance practices in arid and continental conditions, on farm-level greenhouse gas (GHG) emissions. Using Turkey as an example, this paper examines on farm-level GHG emissions calculated for two contrasting sheep production systems under arid and continental climate conditions. Production and management data were obtained through face-to-face interviews carried out on 10 transhumance and 15 semi-intensive meat sheep farms in Turkey. A total of seven GHG emission estimates were then calculated for each farm with the Agricultural Resource Efficiency Calculator (AgRECalc©) tool; i) total Carbon Dioxide (CO2) from energy use (kg CO2e), ii) total Carbon Dioxide equivalent (CO2e) from methane (kg CO2e), iii) total CO₂e from nitrous oxide (kg CO₂e), iv) whole farm and enterprise CO₂e emissions (kg CO₂e), v) net emission from land use (kg CO₂e), vi) whole farm CO₂e emissions per kg of farm output (kg CO₂e/kg output), vii) product CO₂e emissions (meat): kg CO₂e / kg live weight, and viii) farm output (kg of sheep). Multivariate analyses (using R software) were carried out to compare both farm types and their respective carbon emissions. The total farm output per ewe was lower in the transhumance farms (7.4 kg/ewe) than in the semi-intensive farms (7.7 kg/ewe). The kg CO₂e per kg of output was also lower for the transhumance farms (46.2 kg CO₂e) than for the semi-intensive ones (56.5 kg CO₂e). This trend was similar for the amount of CO₂e per kg of live weight produced (20.8 kg and 25.4 kg for the transhumance and the semi-intensive farms, respectively). Despite overall net emissions from land use being greater on average for the transhumance farms, once measured per hectare, they were found to be lower than those for the semi-intensive farms. This study provides a reference point for different sheep production systems’ GHG emission impact in continental rangelands in Turkey.     

Benchmarking the Environmental Performances of Farms (4 pp)

Background, Aim and Scope The usual route for improvement of agricultural practice towards sustainability runs via labelling schemes for products or farm practices. In most approaches requirements are set in absolute terms, disregarding the variation in environmental performance of farms. Another approach for promoting sustainable farming concerns the concept of benchmarking, which takes into account competition among farmers. The individual agricultural performance is characterized by quantitative criteria and compared with scores of other relevant farms. Methods Therefore, a pilot study has been conducted in the Netherlands concerning benchmarking among arable farmers in the Internet involving crop protection. A voluntary Dutch benchmark initiative in the Internet is described including farmers' perception regarding the tool. Results The results show that the benchmark tool in the Internet allows farmers to compare their environmental and economic performance anonymously and securely in a large-scale open-access environment. The pilot group of farmers responded positively to the instrument. An important factor in success is the ease and speed with which data can be entered into the benchmark tool. Conclusions A benchmark tool for comparing the environmental performance among farmers can form the basis for agreements between farmers and their costumers. An application involving food industry and retailers is discussed.     

On-farm animal welfare assessment in beef bulls: consistency over time of single measures and aggregated Welfare Quality® scores

Consistency over time of (on-farm) animal welfare assessment systems forms part of reliability, meaning that results of the assessment should be representative of the longer-term welfare state of the farm as long as the housing and management conditions have not changed considerably. This is especially important if assessments are to be used for certification purposes. It was the aim of the present study to investigate consistency over time of the Welfare Quality® (WQ®) assessment system for fattening cattle at single measure level, aggregated criterion and principle scores, and overall classification across short-term (1 month) and longer-term periods (6 months). We hypothesized that consistency over time of aggregated criterion and principle scores is higher than that of single measures. Consistency was also expected to be lower with longer intervals between assessments. Data were obtained using the WQ® protocol for fattening cattle during three visits (months 0, 1 and 7) on 63 beef farms in Austria, Germany and Italy. Only data from farms where no major changes in housing and management had taken place were considered for analysis. At the single measure level, Spearman rank correlations between visits were >0.7 and variance was lower within farms than between farms for six and two of 19 measures after 1 month and 6 months, respectively. After aggregation of single measures into criterion and principle scores, five and two of 10 criteria and three and one of four principles were found reliable after 1 and 6 months, respectively. At the WQ® principle level, this was the case for three and one of four principles. Seventy-nine per cent and 75% of the farms were allocated to the same overall welfare category after 1 month and 6 months. Possible reasons for a lack of consistency are seasonal effects or short-term fluctuations that occur under normal farm conditions, low prevalence of clinical measures and probably insufficient sample size, whereas poor inter-observer agreement leading to inflation of correlation can be ruled out. At the criterion and principle level, aggregation of information into scores appears to partly smoothen undirected variation at the single measure level without losing sensitivity in terms of welfare evaluation. Reliable on-farm animal welfare assessments should therefore be based on repeated assessments. Further long-term studies are recommended to better understand the factors influencing consistency over time.