Several studies have shown that finishing bulls kept in housing systems with fully slatted concrete floors are impaired in their lying behaviour and locomotion due to the hardness and slipperiness of the ground. The aim of this study was to investigate the effects of floor quality (straw-bedded lying area, rubber-coated slats, concrete slats) on the lying behaviour of finishing bulls. The floor type did not influence the total lying duration, but the number of lying bouts and the number of short standing periods decreased with increasing hardness of the floor in the lying area. In addition, bulls showed more interrupted lying-down and standing-up movements on concrete and rubber-coated slats than on straw bedding. On the other hand, atypical lying-down and standing-up instances, slipping and falling were reduced on rubber-coated slats and on straw bedding compared to concrete slats. Displacements of lying animals were observed more often on rubber-coated slats than on concrete slats or straw bedding. In conclusion, rubber-coated slats improve traction on the ground but are not able to provide as soft a lying area as straw bedding. Rubber coating can thus serve to improve welfare for finishing bulls kept on concrete slats but cannot be considered equivalent to straw bedding.

A preliminary investigation was undertaken to evaluate a series of animal-based welfare measures for the assessment of finishing pigs in units that were members of the RSPCA Freedom Food farm assurance scheme. A total of 20 finishing pig units were visited in the summer of 2002 and 14 of these were revisited in late winter 2003. Behavioural observations of the pigs, both undisturbed and disturbed by the observer, were made in 128 pens containing 9,444 pigs and the physical condition of 650 individuals was examined. A range of event behaviours were observed including social interactions. Play behaviour was observed in 66% of pens during ten-minute observation periods. The prevalence of physical conditions varied greatly between units. The most prevalent skin lesion was on the flank (40.8%) however, only 4.5% of pigs had both fresh and healed flank lesions suggestive of persistent fighting.

A welfare indicator protocol integrating a total of 38 measures from 4 information sources: housing system, management, animal behaviour and clinical health has been developed for decision support in Automatic Milking System (AMS) herds. Two expert opinion studies focusing on the relevance of the welfare indicator protocol as basis for on-farm welfare assessment have been carried out; one study focused on the opinion of 21 AMS researchers; the other on that of 14 AMS production advisors and 15 veterinary practitioners. The researchers were asked to score the individual welfare relevance of the 38 measures. Furthermore, both the panels were asked to prioritise the 10 most important measures. The 21 researchers generally appreciated the listed protocol measures as highly relevant. The researcher and advisor panels agreed on prioritised measures from all 4 information sources among the 10 most important welfare indicators. In summary, researchers as well as production advisors and veterinarians supported the suggested measures for inclusion in a welfare assessment system. This has demonstrated that integration of different information is considered decisive for operational welfare assessment at herd level.

The aim of this study was a comparison of Animal Needs Index (ANI) data, derived from annual inspections by a control agency, with data collected from 164 selected on-farm flocks concerning feather damage, injuries, egg production, mortality, bodyweight, foot pad dermatitis, keel bone deviations and reactions towards humans (eg flock showed marked avoidance when the observer walked through the hen-house [yes/no]).

Analysis of data showed a low number of significant correlations with total ANI scores and category scores: 1) Locomotion, 2) Social interaction, 3) Flooring, 4) Light, air and noise and 5) Stockmanship. Correlations found were low and total ANI score showed only a positive correlation with egg production at week 52. Category 3 scores correlated positively with egg production at week 70 and negatively with the percentage of hens with featherless areas and total pecking injuries. Category 5 scores showed positive correlations with egg production at week 52 as well as week 70 and negative correlations with mortality at week 52, the percentage of hens with featherless areas, pecking injuries < 0.5 cm and total pecking injuries.

Flocks showing marked avoidance had a lower total ANI score and lower category 3 and category 5 scores.

In conclusion, welfare-related animal-based parameters are poorly reflected by the ANI-35-L/2001. To assess animal welfare more adequately, animal-based parameters have to be considered additionally in a welfare assessment scheme.

The Animal Needs Index (ANI) is used for on-farm assessment of welfare in Austria. However, no synthetic welfare assessment system exists in Japan. We performed a welfare assessment of Japanese dairy farms using the ANI scoring system. On 25 farms, 36 dairy herds were assessed using the ANI35L/2000-cattle survey. On 10 dairy farms, 16 herds were housed in free-stall barns. The other 20 herds of 15 dairy farms were housed in tie-stall barns. This study was conducted between December 2004 and January 2005. The ANI scores ranged from 6.0 to 40.0 points (mean 17.8 points). The four high ranking herds on ANI value were housed in free-stalls and allowed the use of outside areas. The 13 low ranking herds were housed in tie-stalls and were not allowed the use of outside areas. The free-stall herds had significantly higher ANI scores than tie-stall herds. The ANI scores of herds having access to outside areas were significantly higher than those of herds having no outside access. This scoring system might be useful for Japanese dairy farms. However, some assessment parameters contain subjective criteria such as cleanliness, floor slipperiness, and animal health. Further studies are necessary to improve the scoring system, in particular clarifying criteria related to those parameters.

Welfare is multidimensional, comprising good health, comfort, expression of behaviour, and so on. Its overall assessment therefore requires a multicriteria evaluation. The set of criteria shall be exhaustive (no missing item), minimal (only necessary items), agreed by stakeholders, and legible (a limited number of criteria). Furthermore, the interpretation from one criterion shall not depend on that from another. We propose a set of 12 subcriteria grouped into four criteria: feeding, housing, health and optimised emotional states. This work will assist in developing measures to be used on-farm to form a European standard for overall assessment of animal welfare.

On-farm monitoring of animal welfare is an important, present-day objective in animal welfare science. Scientists tend to focus exclusively on animal-based parameters, possibly because using environment-based parameters could be begging the question why welfare has been affected and because animal-based parameters would be better indicators of welfare. However, selection of even the best animal-based parameters that have conventionally been used in experiments could have unacceptable consequences. Systems that are generally considered to be poor welfare systems may generate unacceptably high welfare scores. The monitoring systems could fail to match basic intuitions in society and the scientific community. In order to avoid this problem, available knowledge, eg about animal motivation derived from consumer demand studies and knowledge about the natural behaviour of the animals, should be used explicitly in welfare assessment. This requires making welfare inferences from knowledge about the relationships between environment-based and animal-based parameters using standard operating procedures. The on-farm measurement of animal-based parameters may be regarded as the measurement of critical control points, which must be compared and reconciled with predictions based on available scientific knowledge. For this purpose the formalisation of welfare assessment should be developed further.

Providing assurance of improvement in welfare outcomes is the desire of some UK certification schemes. However, this is only likely to be achieved if such schemes monitor welfare outcomes rather than rely on defining welfare resources that should be provided. The University of Bristol has developed protocols for the on-farm evaluation of animal-based welfare parameters for incorporation into certification schemes. The assessment system is designed to provide credible (repeatable, valid and feasible) evidence for assessment of compliance with welfare standards in organic and conventional farming systems. For issues identified as causing potential concern the assessor is encouraged to conduct further investigations of the relevant resource standards and, where appropriate, management requirements. Furthermore the assessment tool enables certification bodies and relevant third parties to monitor the ability of schemes to deliver good welfare outcomes. Finally, it provides a mechanism for farmers to review their own health and welfare performance. The practical application of these systems is now being pursued by some UK certification bodies.

To illustrate that different approaches lead to different costs a cost calculation on four different welfare assessment systems for four different animal species has been carried out; an integrated pig herd (450 sows), a dairy cattle herd with automatic milking (90 cows), an organic egg production system (3000 layers) and a mink farm (1000 mink). We calculated the cost to be: €375 per annum for the mink farm and €2205, €2430 and €2435 for the egg production system, the AMS dairy herd and the integrated pig farm, respectively. The costs can be reduced by: reducing the number of indicators and/or the recording frequency, reducing sample sizes, more intensive use of existing data and by exchanging external for internal recordings.

Globally, veterinarians and professionals in animal-related industries are faced with growing public concern for the welfare of animals, particularly those in production. To prepare professionals, courses in animal welfare should be created to provide consistent education on a global scale in an efficient and cost-effective manner. However, a creative approach to welfare education is needed to reduce the disparity between supply and demand for instruction in animal welfare. Michigan State University (MSU) is piloting a graduate-level, online interactive course in animal welfare assessment to provide students with high-quality science-based education from renowned international animal welfare experts at numerous institutions. Innovative use of technology enables students to interact with material, each other and instructors. Students actively apply their accumulated skills to hypothetical scenarios, enhancing learning effectiveness. Student performance and opinion were examined to determine whether the course meets the stated objectives. Twenty-three students from four institutions enrolled in the pilot course. In the first month, the majority of students found the online course easy to use and material appropriate for a graduate-level course. The students agreed that scenarios helped them integrate lecture material. The MSU course will serve as a model for collaboration in content assembly and course delivery, using technology to leverage global expertise to create educational equity.

It is not sufficient to merely publish regulations and strictly control them to improve the living conditions of farm animals. The farmer must receive precise information, understand the individual measures and be able to act with personal responsibility. A new animal welfare law has been in force in Austria since the 1st of January 2005. A system of self-evaluation is being developed for putting these new legal requirements into practice. The aim of this self-evaluation system is to enable every farmer to personally check his animal housing system against the given standards. This independent work motivates the farmer and makes him aware of animal welfare issues. This new strategy for the implementation of animal welfare law was originally developed, tested and found to be successful by the Federal Administration of the Austrian Province of Vorarlberg. Self-evaluation is to be carried out by means of specific checklists and manuals. Checklists and manuals are currently being drawn up for cattle, pigs, poultry, sheep and goats. The checklists and manuals will include all of the requirements of Austrian animal welfare legislation and will be formulated in easily understandable questions with ‘yes’ or ‘no’ answers. The manuals will describe the methods for assessing legal requirements on the farm as well as the conditions for compliance with legislation, and give advice on how to improve the state of animal welfare on the farm. This paper gives an example of the self-evaluation system for cattle farming.

The present study aims to assess the relationship between consumer perception and on-farm assessment of animal welfare performed using the Animal Needs Index 35L (ANI). Two tie-stall, 2 straw yard and 2 cubicle farms were scored by trained assessors using the ANI and filmed to produce six 3.5 min videos. Each of them contained 4 clips: barn overall view, feeding, milking and individual animals. Ten untrained observers were asked to elicit terms describing how they perceived the observed farming systems to affect animal welfare using Free Choice Profiling (FCP). Data from FCP were subjected to Generalised Procrustes Analysis (GPA). GPA showed a significant consensus among observers. Observers characterised the first dimension with terms ranging from constrictive to comfortable conditions and the second one in terms of cleanliness/dirtiness. Principal Component Analysis (PCA) was conducted using the scores of the farms on the first two dimensions of GPA and the data gathered through the ANI. The first dimension of GPA (Comfortable), ANI's sheet 1 (Locomotion), sheet 2 (Social interaction) and sheet 6 (Total score) showed high loadings on the first component of PCA, whereas the second dimension of GPA (Clean), sheet 3 (Flooring) and sheet 4 (Stockmanship) were correlated with the second component of PCA. We concluded that FCP may be used to elicit lay person perception of welfare-related characteristics of dairy cattle farming systems, thus providing a tool to study the relationships between consumer perception and on-farm assessment of animal welfare.

The present study covers rank correlated use of soft flooring during partial replacement (45% of the total floor space) of concrete slatted floor by rubber covering. For this purpose, the rank position of 19 cows within a 50 Brown Swiss dairy cattle herd was evaluated by calculating the individual dominance index. A clear rank affiliation could be found for 16 cows (eight cows with a rank index 0.67 – 1.0 (ie high ranking) and eight cows with a rank index 0.0 – 0.25 (ie low ranking). Using focal sampling, the 16 cows were observed with time-lapse video recording before and after floor replacement (8.5 hours per day for 10 days with each floor kind). After replacing 45% of the concrete floor surface with soft flooring in a test area far from the milking parlour, high ranking cows used this area significantly longer ie 105.5 ± 36.2 min more than before compared with lower ranking herd members, who did so 17.6 ± 24.6 min less. Before replacement, low ranking cows spent significantly more time on the concrete slatted floor of the test area (147.6 ± 13.2 min) than high ranking cows (80.9 ± 17.3 min). The results of the observation demonstrate that the extent of use of soft rubber flooring correlates to rank-order and illustrates the importance of barn designs in terms of meeting their specific needs in spite of an existing rank order.