Abstract. Animal welfare is increasingly important for the Australian livestock industries, to maintain social licence to practice as well as ensuring market share overseas. Improvement of animal welfare in the livestock industries requires several important key steps. Paramount among these, objective measures are needed for welfare assessment that will enable comparison and contrast of welfare implications of husbandry procedures or housing options. Such measures need to be versatile (can be applied under a wide range of on-and off-farm situations), relevant (reveal aspects of the animal's affective or physiological state that is relevant to their welfare), reliable (can be repeated with confidence in the results), relatively economic to apply, and they need to have broad acceptance by all stakeholders. Qualitative Behavioural Assessment (QBA) is an integrated measure that characterises behaviour as a dynamic, expressive body language. QBA is a versatile tool requiring little specialist equipment suiting application to in situ assessments that enables comparative, hypothesis-driven evaluation of various industry-relevant practices. QBA is being increasingly used as part of animal welfare assessments in Europe, and although most other welfare assessment methods record 'problems' (e.g. lameness, injury scores, and so on), QBA can capture positive aspects of animal welfare (e.g. positively engaged with their environment, playfulness). In this viewpoint, we review the outcomes of recent QBA studies and discuss the potential application of QBA, in combination with other methods, as a welfare assessment tool for the Australian livestock industries.
Tel: +61 8 93606577Running head: comparing two methods of rater scales for behaviour assessment Word count: 5,300 words Highlights: Reliability of rater assessments depends on understanding how observers apply descriptive terms. We compared two methodologies, Fixed List (FL) and Free Choice Profiling. Observers reached consensus using either FL or FCP methods. There were correlations in scores attributed to groups of sows between FL and FCP. Training is an important aspect of reliability of rater assessments.Abstract. Qualitative methods of behavioural assessment use observer rating scales to score the overall demeanour or body language of animals. Establishing the reliability of such holistic approaches requires test and validation of the methods used. Here, we compare two methodologies used in Qualitative Behavioural Assessment (QBA): Fixed-Lists (FL) and Free-Choice Profiling (FCP). A laboratory class of 27 students was separated into two groups of 17 and 10 students (FL and FCP respectively). The FL group were given a list of 20 descriptive terms (used by the European Union's Welfare Quality ® program), shown videos of group-housed sows, and as a group discussed how they would apply the descriptive terms in an assessment. The FCP group were shown the same footage but individually generated their own descriptive terms to describe body language of the animals. Both groups were then shown 18 video clips of group-housed sows and scored each clip using a visual analogue scale (VAS) system. We analysed the VAS scores using Generalised Procrustes Analysis (GPA) for each observer group separately, which indicated high inter-observer reliability for both groups (FL: 71.1% of scoring variation explained, and FCP: 63.5%). There were significant correlations between FL and FCP scores (GPA dimension 1: r 16 =0.946, P<0.001, GPA dimension 2: r 16 =0.477, P=0.045). Additional analysis of the raw VAS scores for the FL group by Principal Component Analysis (PCA) produced four factors; PC1 scores were correlated with GPA1 (r 16 =0.984, P<0.001) and PC3 scores correlated with GPA2 (r 16 =0.880, P<0.001).Kendall's coefficient of concordance (a measure of observer agreement) of the VAS scores indicated statistically significant agreement in use of the 20 descriptive terms (W range 0.37-0.64; all significant at P<0.001, although a value of W >0.7 is usually accepted to show strong agreement). This study demonstrates that, regardless of whether they are given their terms or are allowed to generate their own, observers score sow body language in a similar way. Strengths and weaknesses within the two methods were identified, which highlight the importance of providing thorough and consistent training of observers, including providing good quality training footage so that the full repertoire of demeanours can be identified.
The behaviour of intensively managed sows is influenced by the design of their housing, with the physical structure of the pen affecting how sows spend their time. The first hour after unfamiliar sows are mixed into group housing is considered important in terms of their welfare due to high levels of aggression as they develop a hierarchy and investigate their new surroundings and pen-mates. This study compared the behaviour of sows on a commercial piggery at the point of mixing into 20 group pens (n = 15–18 sows each group), where half the group pens had a concrete partition (a short wall, 2 m long and 1.6 m high) running through the middle of the pen, and half did not have the partition. We predicted that the partition would improve the expression of behaviours during the first hour after mixing. Sows were filmed for 70 min post-mixing and the footage was analysed using quantitative behavioural profile for eight behavioural categories (i.e. time budgets). We found no significant differences in the incidence of aggression, but found less investigative behaviour for sows in pens with the partition; these sows also lay down sooner compared with sows in no-partition pens, and stopped eating/searching for food sooner. The difference between pen designs was most evident at 50–60 min post-mixing, and therefore we compared the behavioural expression of the sows using qualitative behavioural assessment for this time point. There was significant inter-observer reliability among the 17 observers, with 60.02% (P < 0.001) of the variation in their scoring using the Free Choice Profiling methodology explained by the consensus profile. Sows in partition pens were scored as more ‘calm/relaxed’ compared with sows in no-partition pens, which were scored as more ‘aggressive/tense’. There were also significant correlations between the time budgets and behavioural expression scores, with groups of animals described as more ‘aggressive/tense’ also showing more walking, aggression, and avoidance, but less lying. The sows described as more ‘sleepy/bored’ showed more lying and sitting. This study shows that even a subtle difference in housing design (in this case, retention of a concrete partition) can make a significant positive difference to the demeanour and activity patterns of sows. Identifying housing designs that have positive welfare outcomes can inform pen design and construction, and is particularly relevant where housing is being converted (e.g. from single pens to group housing) and decisions must be made around whether or not to keep existing structures.
Across the globe, producers are moving from individual housing to group housing for sows during gestation. Producers typically group sows of a range of parities together, although the impacts are largely unknown. This study examined the behavioral expression at mixing for young, midparity, and older sows. Ten mixed-parity groups were filmed at mixing on a commercial piggery. One-minute clips were edited from continuous footage where focal sows of known parity could be identified, and scored for qualitative behavioral expression. Parity 2 and 6 sows were more calm/tired than Parity 4 sows, who were more active/energetic. Parity 2 sows were more curious/inquisitive than Parity 4 and 6 sows, who were more anxious/frustrated. Correlations between qualitative behavioral expression and activity indicated sows scored as more calm/tired spent a greater proportion of time standing, while sows scored as more active/energetic spent more time performing avoidance behavior. Different body language is likely to reflect physical or affective differences in how sows cope with mixing.
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