Simplifying the Welfare Quality® assessment protocol for broiler chicken welfare

Welfare Quality® (WQ) assessment protocols place the emphasis on animal-based measures as an indicator for animal welfare. Stakeholders, however, emphasize that a reduction in the time taken to complete the protocol is essential to improve practical applicability. We studied the potential for reduction in time to complete the WQ broiler assessment protocol and present some modifications to the protocol correcting a few errors in the original calculations. Data was used from 180 flocks assessed on-farm and 150 flocks assessed at the slaughter plant. Correlations between variables were calculated, and where correlation was moderate, meaningful and promising (in terms of time reduction), simplification was considered using one variable predicted from another variable. Correlation analysis revealed a promising correlation between severe hock burn and gait scores on-farm. Therefore, prediction of gait scores using hock burn scores was studied further as a possible simplification strategy (strategy 1). Measurements of footpad dermatitis, hock burn, cleanliness and gait score on-farm correlated moderately to highly with slaughter plant measurements of footpad dermatitis and/or hock burn, supporting substitution of on-farm measurements with slaughter plant data. A simplification analysis was performed using footpad dermatitis, hock burn, cleanliness and gait scores measured on-farm predicted from slaughter plant measurements of footpad dermatitis and hock burn (strategy 2). Simplification strategies were compared with the full assessment protocol. Close agreement was found between the full protocol and both simplification strategies although large confidence intervals were found for specificity of the simplified models. It is concluded that the proposed simplification strategies are encouraging; strategy 1 can reduce the time to complete the on-farm assessment by ~1 h (25% to 33% reduction) and strategy 2 can reduce on-farm assessment time by ~2 h (50% to 67% reduction). Both simplification strategies should, however, be validated further, and tested on farms with a wide distribution across the different welfare categories of WQ.     

Validating indicators of sheep welfare through a consensus of expert opinion

A consensus of expert opinion was used to provide both face and consensual validity to a list of potential indicators of sheep welfare. This approach was used as a first step in the identification of valid welfare indicators for sheep. The consensus methodology of the National Institute of Health, using pre-meeting consultation and focus group discussions, was used to ascertain the consensus opinion of a panel of sheep welfare experts. The Farm Animal Welfare Council's five freedoms were used as a framework to organise a list of current on-farm welfare issues for sheep. The five freedoms were also the welfare criterion used to identify potential on-farm welfare indicators for sheep. As a result, experts identified 193 welfare issues for sheep and lambs managed on farms across England and Wales. Subsequently, a combination of animal- (n = 26), resource- (n = 13) and management- (n = 22) based indicators was suggested for (i) adult rams, (ii) adult ewes (male and female sheep, over 1 year old), (iii) growing lambs (male and female sheep, over 6 weeks to 1 year old) and (iv) young lambs (male and female lambs, 6 weeks old and under). The results from this study could therefore be used to inform the further development of valid methods of assessing the on-farm welfare of sheep.     

Register-based predictors of violations of animal welfare legislation in dairy herds

The assessment of animal welfare can include resource-based or animal-based measures. Official animal welfare inspections in Denmark primarily control compliance with animal welfare legislation based on resource measures (e.g. housing system) and usually do not regard animal response parameters (e.g. clinical and behavioural observations). Herds selected for welfare inspections are sampled by a risk-based strategy based on existing register data. The aim of the present study was to evaluate register data variables as predictors of dairy herds with violations of the animal welfare legislation (VoAWL) defined as occurrence of at least one of the two most frequently violated measures found at recent inspections in Denmark, namely (a) presence of injured animals not separated from the rest of the group and/or (b) animals in a condition warranting euthanasia still being present in the herd. A total of 25 variables were extracted from the Danish Cattle Database and assessed as predictors using a multivariable logistic analysis of a data set including 73 Danish dairy herds, which all had more than 100 cows and cubicle loose-housing systems. Univariable screening was used to identify variables associated with VoAWL at a P-value<0.2 for the inclusion in a multivariable logistic regression analysis. Backward selection procedures identified the following variables for the final model predictive of VoAWL: increasing standard deviation of milk yield for first lactation cows, high bulk tank somatic cell count (⩾250 000 cells/ml) and suspiciously low number of recorded veterinary treatments (⩽25 treatments/100 cow years). The identified predictors may be explained by underlying management factors leading to impaired animal welfare in the herd, such as poor hygiene, feeding and management of dry or calving cows and sick animals. However, further investigations are required for causal inferences to be established.     

Can pre-collected register data be used to identify dairy herds with good cattle welfare?

Background

Pre-recorded register data from dairy herds are available in almost all Nordic countries. These databases can be used for research purposes, and one of the research areas is animal welfare. The aim of this study was to investigate if pre-recorded register data could be used to identify herds with good welfare, and to investigate if a combination of register data sets could be used to be able to more correctly distinguish between herds with good welfare and herds with welfare deficiencies.

Methods

As a first step, nine animal-based measurements on calves, young stock and cows in 55 randomly selected herds were performed on-farm as the basis for a classification of welfare at the herd level. The definition for being a case herd with “good welfare” was no score lying among the 10% worst in any of the nine welfare measurements. Twenty-eight of the 55 herds were cases according to this definition. As a second step, 65 potential welfare indicators, based on register data in a national dairy database, were identified by expert opinion. In the final step, the extent to which the suggested welfare indicators predicted farms’ as having good welfare according to the stated definition was assessed. Moreover, the effect of combining in sequence a previously developed model that identified herds with poor welfare with the present model identifying herds with good welfare was investigated.

Results

The final set of welfare indicators used to identify herds with good animal welfare included two fertility measures, cow mortality, stillbirth rate, mastitis incidence and incidence of feed-related diseases (including gastrointestinal disturbances but excluding paralyses and cramps). This set had a test sensitivity of correctly classifying herds with no score lying among the 10% worst of the nine welfare measurements of 96 %. However, the specificity of the test was only 56% indicating difficulties for the test to correctly classifying herds with one or more scores lying among the 10% worst. Combining the previously developed model with the present model, improved the welfare classification.

Conclusions

This study shows that pre-collected register data may be used to give approval to dairy farms with “good welfare” and that combining different sets of register data can improve the classification of herd welfare.

     

Effect of grazing on the cow welfare of dairy herds evaluated by a multidimensional welfare index

Structural development in the prime sector has led to increasing herd sizes and new barn systems, followed by less summer grazing for dairy cows in Denmark. Effects of grazing on single welfare measures in dairy cows – for example, the presence of integument alterations or mortality – have been studied under different conditions. However, the effect of grazing on welfare, conceptualised as the multidimensional physical and mental state of the animal, has not yet been studied in contemporary cubicle loose-housing systems. The aim of our study was to investigate, based on a Welfare Quality® inspired multidimensional dairy cow welfare assessment protocol, the within-herd effect of summer grazing compared with winter barn housing in Danish dairy herds with cubicle free-stall systems for the lactating cows. Our hypothesis was that cow welfare in dairy herds was better during summer grazing than during full-time winter housing. Furthermore, we expected improved welfare with an increase in daily summer grazing hours. In total, 41 herds have been visited once in the winter and once in the summer of 2010 to assess their welfare status with 17 different animal- and resource-based welfare measures. A panel of 20 experts on cattle welfare and husbandry evaluated the relative weight of the 17 welfare measures in a multidimensional assessment scheme. They estimated exact weights for a priori constituted severe compared with moderate scores of welfare impairment concerning each measure, as well as relevance of the measures in relation to each other. A welfare index (WI; possible range 0 to 5400) was calculated for each herd and season with a higher index indicating poorer welfare. The within-herd comparison of summer grazing v. winter housing considered all the 17 measures. The mean WI in summer was significantly lower (better) than in winter (mean 2926 v. 3330; paired t-test P = 0.0001) based on a better state of the integument, claw conformation and better access to water and food. Body condition and faeces consistence were worse in summer. Many daily grazing hours (range average above 3 to 9 h) turned out to be more beneficial than few daily grazing hours (range average above 9 to 21 h) for the welfare of the dairy herds. In conclusion, this study reports a positive within-herd effect of summer grazing on dairy cow welfare, where many daily grazing hours were more beneficial than few daily grazing hours.     

Public Attitudes toward the Use of Animals in Research: Effects of Invasiveness,Genetic Modification and Regulation

ABSTRACT

This study describes an online public engagement experiment aimed at investigating how acceptance of animal-based research is affected by: (a) the presence of regulations that govern the use of nonhuman animals in laboratories, (b) the invasiveness of procedures, and (c) the use of genetically modified (GM) animals. To meet these aims, participants were asked if they were willing to accept the use of pigs in different scenarios involving agricultural research. Two-thirds of the 681 participants were female and the majority (58%) were young (19–29 years old) with college or university level education (62%). Participants came from 26 different countries, with the United States, Canada, and the United Kingdom being the top three countries represented. Participants who self-identified as being vegetarians, familiar with animal welfare, animal advocates, environmental advocates, and familiar with animal research were significantly more likely to be opposed to animal-based research. Older participants were significantly less likely to oppose animal-based research. Support significantly decreased when animal-based research involved an invasive procedure or GM animals. Support for invasive research significantly increased when regulation was in place, but regulation had less effect on acceptance of GM animal use. Comments provided by participants illustrated different decision-making strategies regarding different types of animal-based research. Given the increasing use of GM animals in research, more effort is required to understand people's concerns regarding this type of animal use and to determine how these concerns should be reflected in policy.     

Aggregation of measures to produce an overall assessment of animal welfare. Part 1: a review of existing methods

Several systems have been proposed for the overall assessment of animal welfare at the farm level for the purpose of advising farmers or assisting public decision-making. They are generally based on several measures compounded into a single evaluation, using different rules to assemble the information. Here we discuss the different methods used to aggregate welfare measures and their applicability to certification schemes involving welfare. Data obtained on a farm can be (i) analysed by an expert who draws an overall conclusion; (ii) compared with minimal requirements set for each measure; (iii) converted into ranks, which are then summed; or (iv) converted into values or scores compounded in a weighted sum (e.g. TGI35L) or using ad hoc rules. Existing methods used at present (at least when used exclusively) may be insufficiently sensitive or not routinely applicable, or may not reflect the multidimensional nature of welfare and the relative importance of various welfare measures. It is concluded that different methods may be used at different stages of the construction of an overall assessment of animal welfare, depending on the constraints imposed on the aggregation process.     

Assessment of the multi-criteria evaluation system of the Welfare Quality® protocol for growing pigs

Animal welfare has become an important subject of public and political debate, leading to the necessity of an objective evaluation system for on-farm use. As welfare is a multi-dimensional concept, it makes sense to use a multi-criteria aggregation system to obtain an overall welfare score. Such an aggregation system is provided by the Welfare Quality® Network. The present paper focusses on the assessment of the multi-criteria evaluation model included in the Welfare Quality® protocol for growing pigs in order to aggregate the animal-based indicators first to criteria, then to principles and finally to an overall welfare score. Specifically, the importance of the indicators on the overall assessment of growing pig farms is analysed in a given population which consisted of a total of 198 protocol assessments carried out on a sample of 24 farms in Germany. By means of partial least squares modelling, the influence of measures in the calculation procedure is estimated by calculation and interpretation of Variable Importance for Projection (VIP) scores. Variable Importance for Projection scores revealed some meaningful, unexpected influences as the multi-criteria evaluation model of Welfare Quality® aimed at avoiding interferences and double-counting. Some of these influences led to the assumption that some measures might have potential as iceberg indicators, whereas others showed lesser importance. Thus, feasibility can be gained by the deletion and special weighting of indicators according to their importance. Altogether, the study is an essential contribution to the further development of the Welfare Quality® protocols as well as the application of multi-criteria decision systems in the field of animal welfare science in general.     

Aggregation of measures to produce an overall assessment of animal welfare. Part 2: analysis of constraints

The overall assessment of animal welfare is a multicriterion evaluation problem that needs a constructive strategy to compound information produced by many measures. The construction depends on specific features such as the concept of welfare, the measures used and the way data are collected. Welfare is multidimensional and one dimension probably cannot fully compensate for another one (e.g. good health cannot fully compensate for behavioural deprivation). Welfare measures may vary in precision, relevance and their relative contribution to an overall welfare assessment. The data collected are often expressed on ordinal scales, which limits the use of weighted sums to aggregate them. A sequential aggregation is proposed in the Welfare Quality® project, first from measures to welfare criteria (corresponding to dimensions with pre-set objectives) and then to an overall welfare assessment, using rules determined at each level depending on the nature and number of variables to be considered and the level of compensation to be permitted. Scientific evidence and expert opinion are used to refine the model, and stakeholders’ approval of general principles is sought. This approach could potentially be extended to other problems in agriculture such as the overall assessment of the sustainability of production systems.     

Inter-observer agreement,diagnostic sensitivity and specificity of animal-based indicators of young lamb welfare

A scientific literature review and consensus of expert opinion used the welfare definitions provided by the Farm Animal Welfare Council (FAWC) Five Freedoms as the framework for selecting a set of animal-based indicators that were sensitive to the current on-farm welfare issues of young lambs (aged ⩽6 weeks). Ten animal-based indicators assessed by observation – demeanour, response to stimulation, shivering, standing ability, posture, abdominal fill, body condition, lameness, eye condition and salivation were tested as part of the objective of developing valid, reliable and feasible animal-based measures of lamb welfare The indicators were independently tested on 966 young lambs from 17 sheep flocks across Northwest England and Wales during December 2008 to April 2009 by four trained observers. Inter-observer reliability was assessed using Fleiss's kappa (κ), and the pair-wise agreement with an experienced, observer designated as the ‘test standard observer’ (TSO) was examined using Cohen's κ. Latent class analysis (LCA) estimated the sensitivity (Se) and specificity (Sp) of each observer without assuming a gold standard and predicted the Se and Sp of randomly selected observers who may apply the indicators in the future. Overall, good levels of inter-observer reliability, and high levels of Sp were identified for demeanour (κ = 0.54, Se ⩾ 0.70, Sp ⩾ 0.98), stimulation (κ = 0.57, Se = 0.30 to 0.77, Sp ⩾ 0.98), shivering (κ = 0.55, Se = 0.37 to 0.85, Sp ⩾ 0.99), standing ability (0.54, Se ⩾ 0.80, Sp ⩾ 0.99), posture (κ = 0.45, Se ⩾ 0.56, Sp = 0.99), abdominal fill (κ = 0.44, Se = 0.39 to 0.98, Sp = 0.99), body condition (κ = 0.72, Se ⩾ 0.38 to 0.90, Sp = 0.99), lameness (κ = 0.68, Se > 0.73, Sp = 1.00), and eye condition (κ = 0.72, Se ⩾ 0.86, Sp = 0.99). LCA predicted that randomly selected observers had Se > 0.77 (acceptable), and Sp ⩾ 0.98 (high) for assessments of demeanour, lameness, abdominal fill posture, body condition and eye condition. The diagnostic performance of some indicators was influenced by the composition of the study population, and it would be useful to test the indicators on lambs with a greater level of outcomes associated with poor welfare. The findings presented in this paper could be applied in the selection of valid, reliable and feasible indicators used for the purposes of on-farm assessments of lamb welfare.     

Developing a HACCP-like system for improving animal health and welfare in organic egg production – based on an expert panel analysis

In the process of developing a generic Hazard Analysis and Critical Control Point (HACCP)-like system for securing animal health and welfare in organic egg production, an expert panel analysis was used to perform the initial hazard analysis. Eighteen advisers and researchers in organic egg production were included in the expert panel. In a series of four questionnaires, the expert panel first scored 34 health and welfare problems seen in Danish organic egg production. Based on scorings of severity and occurrence, 10 problems were selected for further analysis. The experts subsequently suggested and scored risk factors for those problems and finally suggested control points, alarm values indicating the need for corrective actions in order to control the risk factors and monitoring frequencies of these. The 10 selected problems were hunger, thirst, piling, crop impaction, blackhead, pasteurellosis, bone fractures, cannibalism, predators and red mites. A total of 154 different risk factors were suggested for these problems. The 41 risk factors which rated highest in a combined scoring of importance and occurrence were selected for further analysis. There was a high degree of consensus between experts when scoring both problems and risk factors. The level of consensus, as defined by an interquartile range ⩽1, was 79% to 100% when scoring the health and welfare problems (scale 1–5) and 77% to 95% when scoring the risk factors (scale 1–4). On average, 5.8 control points were suggested for every risk factor. Alarm values were often not detailed enough to be of practical significance and further analysis is needed in order to define these. The experts were highly diverse in their suggested monitoring frequencies and establishment of monitoring schemes should be part of developing the farm specific systems. An expert panel analysis based on questionnaires was a useful tool during the first steps of developing a HACCP plan, conducting a hazard analysis and suggesting control points. However, care should be taken regarding the panel’s size and fields of expertise in order to assure that the panel fully covers the field of interest throughout the study. A further development of the hazard analysis into a farm-specific HACCP system would include assembling an on-farm HACCP team consisting of farmers and advisors for the practical application of control points, alarm values and monitoring schemes. The results from the fourth questionnaire would be useful as input for this work.     

Welfare effects of a disease eradication programme for dairy goats

The Norwegian dairy goat industry has largely succeeded in controlling caprine arthritis encephalitis (CAE), caseous lymphadenitis (CLA) and paratuberculosis through a voluntary disease eradication programme called Healthier Goats (HG). The aim of this study was to apply an on-farm welfare assessment protocol to assess the effects of HG on goat welfare. A total of 30 dairy goat farms were visited, of which 15 had completed disease eradication and 15 had not yet started. Three trained observers assessed the welfare on 10 farms each. The welfare assessment protocol comprised both resource-based and animal-based welfare measures, including a preliminary version of qualitative behavioural assessments with five prefixed terms. A total of 20 goats in each herd were randomly selected for observations of human–animal interactions and physical health. The latter included registering abnormalities of eyes, nostrils, ears, skin, lymph nodes, joints, udder, claws and body condition score. For individual-level data, robust clustered logistic regression analyses with farm as cluster variable were conducted to assess the association with disease eradication. Wilcoxon rank-sum tests were used for comparisons of herd-level data between the two groups. Goats with swollen joints (indicative of CAE) and enlarged lymph nodes (indicative of CLA) were registered on 53% and 93% of the non-HG farms, respectively, but on none of the HG farms. The only other health variables with significantly lower levels in HG herds were skin lesions (P=0.008) and damaged ears due to torn out ear tags (P<0.001). Goats on HG farms showed less fear of unknown humans (P=0.013), and the qualitative behavioural assessments indicated that the animals in these herds were calmer than in non-HG herds. Significantly more space and lower gas concentrations reflected the upgrading of buildings usually done on HG farms. In conclusion, HG has resulted in some welfare improvements beyond the elimination of infectious diseases. The protocol was considered a useful tool to evaluate the welfare consequences of a disease eradication programme. However, larger sample sizes would increase the reliability of prevalence estimates for less common conditions and increase the power to detect differences between the groups. Despite the obvious link between disease and suffering, this aspect is rarely taken into account in the evaluation of disease control programmes. We therefore propose that welfare assessment protocols should be applied to evaluate the merits of disease control or eradication programmes in terms of animal welfare.     

An epidemiological analysis of equine welfare data from regulatory inspections by the official competent authorities

Determining welfare status in a population is the first step in efforts to improve welfare. The primary objective of this study was to explore a new epidemiological approach for analysis of data from official competent authorities that pertain to compliance with animal welfare legislation. We reviewed data already routinely collected as part of Swedish official animal welfare inspections for 2010–13, using a checklist containing 45 checkpoints (CPs). These covered animal-, resource- and management-based measures of equine welfare. The animal-based CPs were measures that directly related to the animal and included social contact, body condition, hoof condition and cleanliness. Non-compliance with one or more of the animal-based CPs was used as a binary outcome of poor equine welfare; 95% confidence intervals (CI) were estimated using the exact binomial distribution. Associations were determined using multivariable logistic regression, adjusting for clustering on premises. Resource- and management-based CPs (model inputs) were reduced by principal component analysis. Other input factors included premises characteristics (e.g. size, location) and inspection characteristics (e.g. type of inspection). There were 30 053 premises with horses from 21 counties registered by the Swedish Board of Agriculture. In total 13 321 inspections of premises were conducted at 28.4% (n=8532) of all registered premises. For random inspections, the premises-prevalence of poor equine welfare was 9.5% (95% CI 7.5, 11.9). Factors associated with poor equine welfare were non-compliance with requirements for supervision, care or feeding of horses, facility design, personnel, stable hygiene, pasture and exercise area maintenance, as well as the owner not being notified of the inspection, a previous complaint or deficiency, spring compared with autumn, and not operating as a professional equine business. Horses at premises compliant with stabling and shelter requirements had significantly better welfare if they also complied with documentation requirements. We present a novel approach for analysis of equine welfare data from regulatory inspections by the official competent authorities, and propose on-going analyses and benchmarking of trends in animal-based measures over time. We also suggest how such a database could be further improved to facilitate future epidemiological analyses of risk factors associated with poor equine welfare. The study has implications for other competent authorities and researchers collaborating in the area of animal welfare epidemiology.     

Inter-observer reliability of animal-based welfare indicators included in the Animal Welfare Indicators welfare assessment protocol for dairy goats

This study was conducted within the context of the Animal Welfare Indicators (AWIN) project and the underlying scientific motivation for the development of the study was the scarcity of data regarding inter-observer reliability (IOR) of welfare indicators, particularly given the importance of reliability as a further step for developing on-farm welfare assessment protocols. The objective of this study is therefore to evaluate IOR of animal-based indicators (at group and individual-level) of the AWIN welfare assessment protocol (prototype) for dairy goats. In the design of the study, two pairs of observers, one in Portugal and another in Italy, visited 10 farms each and applied the AWIN prototype protocol. Farms in both countries were visited between January and March 2014, and all the observers received the same training before the farm visits were initiated. Data collected during farm visits, and analysed in this study, include group-level and individual-level observations. The results of our study allow us to conclude that most of the group-level indicators presented the highest IOR level (‘substantial’, 0.85 to 0.99) in both field studies, pointing to a usable set of animal-based welfare indicators that were therefore included in the first level of the final AWIN welfare assessment protocol for dairy goats. Inter-observer reliability of individual-level indicators was lower, but the majority of them still reached ‘fair to good’ (0.41 to 0.75) and ‘excellent’ (0.76 to 1) levels. In the paper we explore reasons for the differences found in IOR between the group and individual-level indicators, including how the number of individual-level indicators to be assessed on each animal and the restraining method may have affected the results. Furthermore, we discuss the differences found in the IOR of individual-level indicators in both countries: the Portuguese pair of observers reached a higher level of IOR, when compared with the Italian observers. We argue how the reasons behind these differences may stem from the restraining method applied, or the different background and experience of the observers. Finally, the discussion of the results emphasizes the importance of considering that reliability is not an absolute attribute of an indicator, but derives from an interaction between the indicators, the observers and the situation in which the assessment is taking place. This highlights the importance of further considering the indicators’ reliability while developing welfare assessment protocols.     

Short communication: Evaluation of the sample size of individual indicators in gestating sows concerning the Welfare Quality® protocol applied to sows and piglets

Sample sizes of welfare assessment protocols must warrant to reflect prevalences on-farm properly – regardless of farm size. Still, solely a fixed sample size was specified for the Welfare Quality® protocol for sows and piglets. The present study investigated whether animals may be assessed from only one body side as applied in the protocol and whether the pre-set sample size of 30 animals mirrors the prevalences of the animal-based indicators on-farm in the gestation unit considering different farm sizes. All indicators were assessed for both sides of an animal’s body by one observer on 13 farms in Germany, which were visited five times within 10 months. The farm visits were treated as independent since different animals were housed in the gestation units. The number of sows in the gestation units varied between 18 and 549 animals. The comparison of sides was carried out calculating exact agreement between animals’ sides and a Wilcoxon signed-rank test (W). The results signified that it is sufficient to assess the animal from one side (exact agreement: 88.3% to 99.5%, except for bursitis (70.0%); W: P-values 0.14 to 0.92). However, if side preferences existed in the indicator bursitis a potential bias must be considered. In the following, the sample size was evaluated by comparing samples’ prevalences against true prevalence, that is, the prevalence of all observed animals in the gestation unit in each farm visit. Therefore, subsets of data were generated by applying simple random sampling without replacement. The samples randomly included the animals’ right or left sides. Linear regression was rated as appropriate provided: coefficient of determination R² ≥ 0.90, slope = 1 and intercept = 0 signifying exact agreement. The results revealed that the sample size required by the protocol and the application of calculation formulas are solely appropriate to mirror the prevalences of frequent indicators in the gestation unit, for example, bursitis (mean prevalence 34.4%). Using a proportion of animals, for example, a sample of 30% of all observed animals in a farm visit, pointed out that proportions must increase with indicators’ underlying prevalence narrowing 0.00%. Local infections (mean prevalence 13.3%) needed samples including 60% of all observed animals in each farm visit, whereas vulva lesions (mean prevalence 7.28%) only reached accuracy with the inclusion of 70% of the animals. Indicators with a mean prevalence of <1% were not analysed but can most likely only be ascertained by the assessment of all animals.     

Using conjoint analysis to weight broiler welfare variables based on slaughterhouse data

The Council of the European Union adopted the welfare directive for broiler chickens in 2007 (Commission of the European Communities, 2007). The directive defines minimum demands and objectives for broiler production ranging from stocking density to welfare. This study found that the level of nonhuman animal welfare can be determined, for example, with welfare indexes that have different weight values for welfare variables. A total of 20 poultry experts from slaughterhouses, the feed industry, administration, and research received simulated data on 24 flocks. This included data for 5 welfare variables based on postmortem meat inspection information on commercial flocks and based on literature: mortality during rearing, foot-pad score, and the incidence of ascites, dermatitis, and cachexia in routine meat inspection. The experts ranked these flocks from the worst to the best according to animal welfare. Conjoint analysis weighted the relative importance of the welfare variables for broiler welfare. The study based relative importance for broiler welfare on 20 expert opinions: 24.6% for mortality, 35.9% for foot-pad score, 19.7% for the incidence of ascites, 15.7% for the incidence of dermatitis, and 4.1% for the incidence of cachexia. In the future, an index for broiler welfare evaluation could be developed based on the results of this study.     

Using Conjoint Analysis to Weight Broiler Welfare Variables Based on Slaughterhouse Data

The Council of the European Union adopted the welfare directive for broiler chickens in 2007 (Commission of the European Communities, 2007). The directive defines minimum demands and objectives for broiler production ranging from stocking density to welfare. This study found that the level of nonhuman animal welfare can be determined, for example, with welfare indexes that have different weight values for welfare variables. A total of 20 poultry experts from slaughterhouses, the feed industry, administration, and research received simulated data on 24 flocks. This included data for 5 welfare variables based on postmortem meat inspection information on commercial flocks and based on literature: mortality during rearing, foot-pad score, and the incidence of ascites, dermatitis, and cachexia in routine meat inspection. The experts ranked these flocks from the worst to the best according to animal welfare. Conjoint analysis weighted the relative importance of the welfare variables for broiler welfare. The study based relative importance for broiler welfare on 20 expert opinions: 24.6% for mortality, 35.9% for foot-pad score, 19.7% for the incidence of ascites, 15.7% for the incidence of dermatitis, and 4.1% for the incidence of cachexia. In the future, an index for broiler welfare evaluation could be developed based on the results of this study.     

Using the Herd Status Index to remotely assess the welfare status of dairy herds based on prerecorded data

The use of prerecorded data to remotely assess the herd welfare status is a promising approach to reduce the need for costly and time-consuming on-farm welfare assessments. Therefore, the objective of this study was to validate the Herd Status Index, an index developed based on Dairy Herd Improvement data from Canada, to remotely evaluate the welfare status of dairy herds. Herd-level prevalence of five animal-based welfare outcomes, measured once on 2 986 Quebec – Canada dairy herds between 2016 and 2019, were used to generate clusters with different welfare status using the algorithm partitioning around medoids. Dairy Herd Improvement data from 12 months prior to the welfare assessment were extracted and used to calculate the Herd Status Index. A linear model was used to carry out comparisons between clusters. Three stable clusters were found to best describe the data. Cluster two had the best overall welfare status since it had the lowest prevalence of all welfare issues while cluster three had the highest prevalence of most welfare issues, with the exception for the prevalence of neck lesions that was not different than cluster one. Cluster one had an overall intermediate welfare status. The Herd Status Index was higher (i.e., indicating a good welfare status) on cluster two compared to cluster three, but neither cluster three nor two differed to cluster one. In its current format, the Herd Status Index has a weak potential to identify herds with varying prevalence of welfare issues and it requires further improvements before it could be used to accurately assess the welfare status of the herds.     

Inter- and intra-observer reliability of animal welfare indicators for the on-farm self-assessment of fattening pigs

In Germany all keepers of livestock are legally required to record animal welfare indicators as part of their on-farm self-assessment. The Association for Technology and Structures in Agriculture (Kuratorium für Technik und Bauwesen in der Landwirtschaft e.V. (KTBL)) has suggested the use of a particular set of animal welfare indicators in their publication Animal welfare indicators: Practical guide – Pigs. The aim of the present study was to evaluate the inter-observer reliability (Inter-OR) and intra-observer reliability (Intra-OR) of these indicators with respect to the welfare of fattening pigs. For the assessment of Inter-OR, three observers evaluated six KTBL animal welfare indicators. The Inter-OR of the indicators was calculated from the results using intra-class correlation coefficients (ICC). ‘Excellent’ Inter-OR results were found for the indicators tail length (ICC 0.89), skin lesions (ICC 0.77) and ear lesions (ICC 0.80). In contrast, the Inter-OR of the indicators tail lesions (ICC 0.46) and faecal soiling (ICC 0.47) were considered to be only ‘fair’ and that of the indicator lameness (ICC 0.36) as ‘poor’. For the evaluation of the Intra-OR, the same three observers assessed the welfare of 162 to 200 fattening pigs using the same welfare indicators in total eight times. Again ICCs, here per indicator and observer, were used to calculate the Intra-OR. The Intra-OR of the indicators faecal soiling (ICC 0.81) and ear lesions (ICC 0.97) lay in the ‘excellent’ range on average. While the Intra-OR of the indicators skin lesions (ICC 0.67), tail length (ICC 0.74) and lameness (ICC 0.60) could still be considered as being ‘good’, the Intra-OR of the indicator tail lesions (ICC 0.52) could only be assessed as being ‘fair’. From these results the significance of the KTBL indicators could be judged as follows: it is possible to use all the chosen indicators apart from the indicator tail lesions as an internal controlling instrument or as part of an internal weak-point analysis as long as the indicators are evaluated by the same person. A comparison of the indicators tail lesions, lameness and faecal soiling when assessed by different observers should be considered critically because the Inter-OR of these three indicators could only be considered as being ‘poor’ to ‘fair’.     

Behaviour as a tool in the assessment of animal welfare

A central issue in animal welfare research is how to assess the welfare state of animals objectively and scientifically. I argue that this issue can be approached by asking two key questions: 1) is the animal physically healthy and 2) does the animal have what it wants? Behaviour is used to answer both of these questions. In the assessment of physical health, it can be used for clinical and pre-clinical diagnosis. In the assessment of what animals want, it has a major role through choice and preference testing. It is particularly important that applied ethologists develop methods for assessing welfare in situ--in the places where concern for animal welfare is greatest such as on farms and in zoos.