Abstract
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.This 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.
Highlights
Qualitative behaviour assessment (QBA) is a scientific method that relies on the ability of human observers to integrate perceived details of behaviour, posture, and context into the summarization of animals’ style of behaving, using descriptors such as “relaxed”, “tense”, “frustrated”, or “content” [1].The innovation in this approach stems from translating the emotion of animals judged by the observers into figures that a formal statistical methodology can analyse [2]
Observers give a score on a visual analogue scale (VAS) for each QBA descriptor [3]
Our study revealed the interesting effect that workload can have on goats’ emotions, confirming the importance of spending time with animals and at the same time highlights some of the biggest problems reported by farmers in commercial farms: the lack of time and the excessive workload to have a good quality of work
Summary
Qualitative behaviour assessment (QBA) is a scientific method that relies on the ability of human observers to integrate perceived details of behaviour, posture, and context into the summarization of animals’ style of behaving, using descriptors such as “relaxed”, “tense”, “frustrated”, or “content” [1]. The innovation in this approach stems from translating the emotion of animals judged by the observers into figures that a formal statistical methodology can analyse [2]. QBA has been used for a wide range of species in different contexts, but only a limited number of these studies applied QBA in on-farm conditions using a fixed list of terms (e.g., layers and broilers [5]; cattle [4,6]; pigs [7]; buffaloes [8]; veal calves [9]; horses [10]; dairy goats [11]; donkeys [12]; and sheep [13])
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