Score 1Presence of residual horns (scurs) on the head of adult goats that have been disbudded when kids.The total number of goats in the pen presenting these conditions is recorded. Queuing (AWIN, 2015)At feeding A goat is queuing if it is standing within 0.5 m behind another goat that is feeding/ drinking, with the head oriented towards the feed barrier/ water place. At drinkingHair coat condition (AWIN, 2015; Battini et al., 2015a) Poor hair coatThe hair coat is matted, rough, scurfy, uneven, shaggy hair coat, frequently longer than normal. Oblivion (AWIN, 2015)An oblivious goat seems physically or/and mentally isolated compared to the rest of the group, frequently facing the wall or other parts of the housing structure, sometimes with ears down. Abnormal lying (Mattiello et al., 2015)

Simple SummaryThe use of feasible indicators to evaluate animals’ emotional states in farm animals is strongly encouraged for welfare assessment. The inclusion of qualitative behaviour assessment (QBA) in on-farm protocols has been constantly increasing during the last few years; but its association with other welfare measures has been scarcely investigated so far. In the present study; we investigated whether QBA shows a meaningful coherence with other measures included in the AWIN (Animal Welfare Indicators) welfare assessment protocol for dairy goats. We confirmed that QBA can clearly discern mood (from Agitated/Alert to Content/Relaxed) and the level of activity (from Bored to Lively) in goats. Furthermore; goats with a shiny hair coat seem more relaxed and sociable than goats with a poor hair coat condition. In contrast; farms where the workload for the stockperson is high have goats that were observed as more bored and suffering; probably because farmers do not invest enough time in taking care of their animals. Even though we found only few relations between QBA and the other measures of the AWIN welfare assessment protocol; the holistic approach of QBA can be useful to integrate the assessment and give a different perspective on the complexity of animals’ emotions and overall welfare state.AbstractThis research investigated whether using qualitative behaviour assessment (QBA) with a fixed list of descriptors may be related to quantitative animal- (ABM) and resource-based (RBM) measures included in the AWIN (Animal Welfare Indicators) welfare assessment prototype protocol for goats, tested in 60 farms. A principal component analysis (PCA) was conducted on QBA descriptors; then PCs were correlated to some ABMs and RBMs. Subsequently, a combined PCA merged QBA scores, ABMs and RBMs. The study confirms that QBA can identify the differences in goats’ emotions, but only few significant correlations were found with ABMs and RBMs. In addition, the combined PCA revealed that goats with a normal hair coat were scored as more relaxed and sociable. A high farm workload was related to bored and suffering goats, probably because farmers that can devote less time to animals may fail to recognise important signals from them. Goats were scored as sociable, but also alert, in response to the presence of an outdoor run, probably because when outdoors they received more stimuli than indoors and were more attentive to the surroundings. Notwithstanding these results, the holistic approach of QBA may allow to register animals’ welfare from a different perspective and be complementary to other measures.

Consistency over time (COT) of animal-based indicators is key to a reliable and feasible welfare protocol, indicating that results are representative over long-term situations. High levels of consistency ensure fairness for the farmer and credibility of the system. In addition, indicator COT reduces recording costs, as having indicators that do not change over a long period of time will require less farm visits to achieve reliable estimates. To date, COT of animal-based indicators included in the welfare assessment of dairy goats has never been tested. Therefore, our aim was to investigate COT of animal-based indicators included in the Animal Welfare Indicators (AWIN) welfare assessment prototype protocol for dairy goats. To meet this goal, a study was designed where an average of 3 mo elapsed between 2 sets of visits to the same 20 dairy goat farms (10 in Portugal and 10 in Italy), with no major changes in management routines or housing conditions occurring during this period. Initially, we performed a Wilcoxon signed rank test to investigate whether the results obtained during the 2 visits were significantly different. After this preliminary screening, the indicators presenting nonsignificant differences between visits were submitted to a second step analysis, where discriminative and evaluative analyses were conducted to reach a final indicator lineup. The discriminative approach helped distinguishing among farms, whereas the agreement analysis showed us the range of differences between repeated assessments. Some particular conclusions could be drawn from this combined analysis, helping to the development of the final AWIN welfare assessment protocol for dairy goats and as a further step to develop a welfare assessment monitoring scheme for this and other species. In this sense, the AWIN welfare assessment protocol allows for the quick differentiation between farms based on the identification of persistent welfare problems, by recording highly consistent and feasible indicators. In a second step, a more comprehensive protocol, consisting of indicators more likely to be subject to variations along time, was applied. Repeated assessments and long-term studies of indicator consistency are needed to help determine the frequency of visits required to obtain a consistent and feasible welfare assessment scheme. This paper adds to the literature by providing guidance on the variability of animal-based indicators over time.