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There is a trend toward increasing intensification in dairy farming in the United Kingdom. In particular, there is concern over systems in which cows are housed throughout the year, as the behavioural restriction implicit in these systems is associated with poor welfare in other species. The aim of this on-going project is to determine how this affects the behaviour and welfare of dairy cattle. A range of behavioural, physical and health measures are being used to assess cow welfare on about 40 commercial British dairy farms. Initially, five farm types were identified from analysis of returns from a farmer questionnaire. Milk production level and housing type were the principal factors explaining variation in farm type. The sample groups are: high-, mid- and low-production cubicle-housing units, mid-production straw-court units, and cubicle-housing high-production zero-grazing units. Observations will take place over three winter housing periods (2000/01 to 2002/03), with recording on each unit taking five days. Our main hypothesis is that the behavioural and physical responses of ‘at-risk’ younger cows provide a sensitive indication of farm-level ‘stress’. Cows are marked according to age, and the feed-face videotaped continuously to record feeding time and social interactions. Temporal organisation of behaviour will be analysed using fractal mathematics and qualitative assessment approaches used in a human interaction test. Cow cleanliness, condition score, response to a novel object and the incidences of lameness and leg injury are recorded, and building quality is assessed. Ultimately, multivariate methods will be used to test our underlying hypothesis and to assess effects of housing and production type on behaviour and welfare. This analysis may identify key objective measures of welfare for use in farm assurance schemes.

The welfare consequences of long-distance transportation of animals remain a controversial topic. Animals that stand for most of the long journey (especially if additional muscular activity is required to deal with postural instability) are at risk of developing fatigue. Previous observational studies of behaviour and physiology suggested either that sheep do not become markedly fatigued by long journeys or that previous methods did not adequately identify fatigue. A range of behavioural and physiological measures were made on eight pairs of sheep during and after treadmill exercise. Within each pair of sheep, a treatment sheep was walked on a treadmill at 0.5 m/s for up to 5 h or until the sheep voluntarily stopped exercising or showed other signs of reduced performance, and a control sheep was exercised for two 10-min periods on either side of the exercise period for the treatment sheep. With the exception of one sheep that only walked for 4.5 h, all treatment sheep walked for 5 h without apparent difficulty. After exercise, the plasma cortisol concentration of treatment sheep was significantly greater than that of control sheep. However, there were no significant treatment effects on plasma creatine kinase activity or blood lactate concentration. After 5 h of exercise, there was a proportionate decrease in the median frequency of the electromyogram recorded over the m. semitendinosus ,a nd this was significantly different from control sheep. There was no evidence that treatment sheep lay down sooner or for longer after treadmill exercise than controls. In sheep tested in a maze to examine whether there was increased motivation to rest after exercise, there was no significant difference between the times taken by treatment and control sheep to obtain a food reward. Qualitative behavioural assessment of the sheep by a panel of observers identified two main dimensions of sheep demeanour, but among descriptors elicited from observers only one person used a term associated with fatigue. No significant difference was found between the scores of treatment and control sheep on these two demeanour dimensions. Thus, there was little evidence that prolonged gentle walking exercise fatigues sheep. Further development of methods to both repeatedly induce and to identify fatigue in sheep is required.

This study explores the use of Free Choice Profiling (FCP) methodology for the qualitative behaviour assessment of emotional expression in the domestic dog(Canis familiaris). Qualitative behaviour assessment is based upon the integration of many pieces of information that in conventional quantitative approaches are recorded separately or not at all. Observers are asked to focus on an animal's interaction with its surrounding environment, and to describe the animal's expressive demeanor, or ‘body language’. A specific characteristic of FCP methodology is that it allows observers the freedom to devise their own descriptive terms, and then to use these personal terms to quantitatively score observed subjects. Application of FCP to qualitative behaviour assessment in animals was originally tested for pigs, and more recently for dairy cows, horses, and ponies. The goal of this study was to apply FCP to the domestic dog, and to investigate the inter-observer reliability of assessments of emotional expression in 10 individual Beagles by a group of 18 untrained observers. The data was analysed using Generalised Procrustes Analysis (GPA), a multivariate statistical technique associated with FCP. The observers achieved highly-significant agreement in their assessments of the dogs’ expressions, thereby establishing the applicability of this methodology for the first time in the domestic dog.

The responsiveness of 10 horses and 10 ponies to environmental challenge (represented by an open field test) was assessed using a qualitative approach based on free choice profiling methodology (FCP), which gives observers complete freedom to choose their own descriptive terms. Data were analysed with generalised Procrustes analysis (GPA), a multivariate statistical technique associated with FCP. A cross-validation of the outcomes of this approach to data recorded through quantitative behaviour analysis, and through a questionnaire given to the animals’ owner/riding instructor, was also performed using principal component analysis (PCA). Twelve undergraduate students generated their own descriptive vocabularies, by watching 20 horse/pony video clips lasting 2.5 min each. GPA showed that the consensus profile explained a high percentage of variation among the 12 observers, and differed significantly from the mean randomised profile ( p < 0.001). Two main dimensions of the consensus profile were identified, explaining 60% and 5.2% of the variation between animals, respectively. The 12 observer word charts interpreting these dimensions were semantically consistent, as they all converged towards the same meaning, albeit using different terms. The most used term to describe the positive end of axis 1 was ‘‘quiet’’, whereas ‘‘attentive’’ was the best positive descriptor of axis 2. The most frequently used descriptors for the negative ends of axes 1 and 2 were ‘‘nervous’’ and ‘‘bored’’, respectively. Thus, axis 1 was labelled as ‘‘quiet/nervous’’ and axis 2 was named as ‘‘attentive/bored’’. A marked effect of animal category was observed on the scores of the animals on the first dimension ( p < 0.001). Horses received significantly higher scores, and were thus assessed as more quiet and calm, than ponies. Conversely, ponies tended to receive lower scores on the second dimension ( p < 0.12), therefore they appeared less curious and attentive. The results of the PCA showed that the variables from different types of measurement clearly had meaningful relationships. For instance, the variables with the highest loading on the positive end of axis 1 were all indicative of tractable and docile animals, whereas axis 2 showed high loadings on the positive end for variables indicating attentive animals. Qualitative behaviour assessment proved to be an appropriate methodology for the study of horse behavioural responsiveness, in that it provided a multifaceted characterisation of horse behavioural expression that was in agreement with other quantitative and subjective assessments of the animals’ behaviour.

This study applies qualitative behaviour assessment (QBA) for the first time to dairy buffaloes, using three groups of observers with different cultural backgrounds and different levels of experience in animal behaviour observation and buffalo farming. Eight buffalo heifers aged 16–18 months were subjected to two isolation tests, one performed in the indoor part of their home environment, and one in a novel outdoor paddock. Animals were filmed individually for 2.5 min, and the resulting 16 video clips were shown to three observer panels, consisting of 11 applied animal behaviour scientists from 6 European countries, 11 Italian animal scientists with a background in buffalo farming but no experience in behavioural observation, and 14 Italian undergraduate animal science students with no particular experience. A free choice profiling method was used to instruct observers in QBA, and data for the three panels were analysed separately using Generalised Procrustes Analysis. All three panels showed significant inter-observer agreement (p < 0.001) and generated two main consensus dimensions characterised as ‘calm-agitated’ and ‘curious-shy’. There were significant correlations between buffalo scores provided by each of the three observer panels on both these dimensions (dim1: Kendall W = 0.96, n = 3, χ2 = 43.28, p < 0.001; dim2: W = 0.68, n = 3, χ2 = 30.73, p < 0.01). Buffaloes viewed in the familiar indoor pen were assessed by all three panels as more calm and less agitated (dimension 1) than animals viewed in the novel outdoor pen (Wilcoxon z = −2.52, p < 0.01, z = −2.52, p < 0.01, z = −2.38, p < 0.01 for Panels 1, 2, and 3, respectively). Scores on dimension 1 for the same animals viewed in either indoor or outdoor pen were correlated at r = 0.60 (p < 0.10), 0.74 (p < 0.05) and 0.71 (p < 0.05) for Panels 1, 2, and 3, respectively. Quantitatively, buffalo in the outdoor pen displayed longer bouts of running and higher frequencies of sniffing (both p < 0.05) than those in the indoor pen. Principal component analysis showed meaningful associations between qualitative and quantitative assessments, allowing qualitative dimensions to play a valuable role in interpreting the animals’ state. The main outcomes of this study are that QBA can be usefully applied to scientific studies of dairy buffalo, and that substantial differences in observer background do not appear to diminish the reliability of QBA.

Given the absence of a ‘Golden Standard’ for the objective determination of welfare, the collection and interpretation of data involving different parameters is essential for assessing the well-being of farm animals. The choice of parameters and the relative weights assigned to each of them are crucial for the outcome of the assessment. Both elements involve a certain degree of subjectivity. In this paper we discuss the basics of different methods used to integrate welfare parameters, focussing on the issue of scientific objectivity. We begin by addressing parameter selection, the assignment of parameter weightings or rankings and the qualifications necessary for ‘experts’ designing and applying the methodology. Five different approaches to integrating parameters are then discussed. The paper does not state a preference for any method, but aims to encourage discussion of key elements involved with the on-farm assessment of welfare.