To ensure that farm animal welfare issues are identified and addressed appropriately, there is a need for robust on-farm welfare assessment protocols. This paper describes the development of a comprehensive welfare assessment protocol for dairy goats (Capra hircus) and its testing on 30 commercial dairy goat farms in Norway. The protocol combines animal-based welfare indicators with measures of husbandry provisions to enable the identification of welfare problems and challenges inherent to the production system. The study also includes a first report of group level qualitative behavioural assessments (QBA) of goats. Due to reliability and validity issues related to behavioural assessments of human-animal interactions, indices of stockperson attitudes were incorporated as a complementary assessment of stockmanship. The most prevalent physical conditions observed were ocular discharge, skin lesions, udder asymmetry, calluses on knees and hocks, and overgrown claws. Moreover, fear levels appeared to be of particular concern in some herds. Significant associations were found between qualitative behavioural assessments and measures of health and stockmanship. Floor type was associated with four animal-based welfare outcomes. Reliability and validity of goat welfare indicators need to be further tested, and intervention plans and thresholds need to be determined so that advice can be tailored to the specific problems identified on each farm. We conclude that the protocol can work as a tool to identify welfare issues in dairy goat herds, and that this study may be a valuable contribution to the development of a much-needed welfare assessment protocol for dairy goats.

No abstract

No abstract

No abstract

No abstract

No abstract

No abstract

Qualitative Behavioural Assessment (QBA) is a whole-animal approach used to quantify the expressive style of animals’ behaviour. The aim of this study was to evaluate the inter-observer reliability of principal components and individual descriptors from QBA of housed sheep in Norway using a fixed list of descriptors. In part 1, eight animal welfare inspectors from the Norwegian Food Safety Authority scored 12 two-minute video clips, using 12 pre-defined terms. In the second part, three of these observers visited ten sheep farms and scored the behaviour using a modified list of eight terms. The scores for all assessors within each part were analysed using Principal Component Analysis (PCA). The level of agreement for the first two components and for individual terms was assessed using Kendall's coefficient of concordance (W). In part 1, only seven observers were assessed for reliability of principal components due to missing data, and for these observers the agreement was high for PC1 and moderate for PC2. For the sub-group of three inspectors that also participated in part 2, the reliability was high for both components. In the on-farm assessments in part 2, these three observers obtained only moderate agreement for PC1 and low agreement for PC2. Results illustrate that good reliability can be achieved with QBA for housed sheep using videos, but that equally satisfactory reliability is more difficult to obtain using the method on-farm. The result in part 2 may be related to less-controlled circumstances concerning exactly what the observers see when sheep are kept indoors with high stocking densities, observer drift, and limited between-farm variation, which is a challenge for many types of reliability studies in field conditions.