Qualitative Behavioural Assessment Scores Research Articles

Qualitative Behavioural Assessment of bonobo emotional expressivity across observer groups and zoo housing environments.

Human evaluation of animal emotional expressivity can inform animal welfare. Qualitative Behavioural Assessment (QBA) has been applied to domesticated and some non-domesticated animals, but its use in primates is limited despite their emotional expressivity. We aimed to develop and apply a QBA for bonobos (Pan paniscus) through two consecutive studies. We applied Free Choice Profiling (FCP) and the Fixed List methodology, respectively, in Study 1 and 2, and invited students and bonobo experts to rate video clips of zoo-living bonobos of different sexes and age classes, and before and after moving to a new enclosure. In Study 1, students described dimension 1 as ranging from 'quiet/calm' to 'angry/active' and dimension 2 from 'sad/anxious' to 'happy/loving'. Experts described dimension 1 ranging from 'quiet/relaxed' to 'nervous/alert' and dimension 2 from 'nervous/bored' to 'playful/happy'. Using a fixed list of descriptors, informed by findings from Study 1, students in Study 2 described dimension 1 as ranging from 'quiet/calm' to 'agitated/frustrated', and dimension 2 from 'sad/stressed' to 'happy/positively engaged'. Experts described dimension 1 as ranging from 'quiet/calm' to 'active/excited', and dimension 2 from 'sad/bored' to 'happy/positively engaged'. Students scored adults as more 'calm/quiet' and experts scored subadults as more 'happy/positively engaged'. Additionally, experts in Study 2 rated bonobos as more 'active/excited' in their new enclosure. Reliability was moderate to good for the dimensions. Additionally, animal-directed empathy of observers influenced QBA scores. This is the first time, FCP has been successfully used as a method to study primate emotional expressivity. Our findings show the promise of employing QBA in primate studies and in industry, with validation of additional metrics to enable its use for welfare-monitoring purposes.

Qualitative Behavioural Assessment as a welfare indicator for farmed Atlantic salmon (Salmo salar) in response to a stressful challenge.

Animal welfare assessments have struggled to investigate the emotional states of animals while focusing solely on available empirical evidence. Qualitative Behavioural Assessment (QBA) may provide insights into an animal's subjective experiences without compromising scientific rigor. Rather than assessing explicit, physical behaviours (i.e., what animals are doing, such as swimming or feeding), QBA describes and quantifies the overall expressive manner in which animals execute those behaviours (i.e., how relaxed or agitated they appear). While QBA has been successfully applied to scientific welfare assessments in a variety of species, its application within aquaculture remains largely unexplored. This study aimed to assess QBA's effectiveness in capturing changes in the emotional behaviour of Atlantic salmon following exposure to a stressful challenge. Nine tanks of juvenile Atlantic salmon were video-recorded every morning for 15 min over a 7-day period, in the middle of which a stressful challenge (intrusive sampling) was conducted on the salmon. The resultant 1-min, 63 video clips were then semi-randomised to avoid predictability and treatment bias for QBA scorers. Twelve salmon-industry professionals generated a list of 16 qualitative descriptors (e.g., relaxed, agitated, stressed) after viewing unrelated video-recordings depicting varying expressive characteristics of salmon in different contexts. A different group of 5 observers, with varied experience of salmon farming, subsequently scored the 16 descriptors for each clip using a Visual Analogue Scale (VAS). Principal Components Analysis (correlation matrix, no rotation) was used to identify perceived patterns of expressive characteristics across the video-clips, which revealed 4 dimensions explaining 74.5% of the variation between clips. PC1, ranging from 'relaxed/content/positive active' to 'unsettled/stressed/spooked/skittish' explained the highest percentage of variation (37%). QBA scores for video-clips on PC1, PC2, and PC4 achieved good inter- and intra-observer reliability. Linear Mixed Effects Models, controlled for observer variation in PC1 scores, showed a significant difference between PC1 scores before and after sampling (p = 0.03), with salmon being perceived as more stressed afterwards. PC1 scores also correlated positively with darting behaviours (r = 0.42, p < 0.001). These results are the first to report QBA's sensitivity to changes in expressive characteristics of salmon following a putatively stressful challenge, demonstrating QBA's potential as a welfare indicator within aquaculture.

Qualitative Behaviour Assessment for zoo-housed polar bears (Ursus maritimus): Intra- and inter-day consistency and association to other indicators of welfare

Contemporary zoos house polar bears (Ursus maritimus) to serve the conservation efforts of these institutions. However, evidence of behavioural problems in captivity has highlighted the need for methods to assess polar bear welfare, why valid and feasible animal-based welfare indicators are a prerequisite. Qualitative Behaviour Assessment (QBA) has been used to assess emotional state in various species. This study therefore aimed to assess the ability of QBA to discern emotional state in zoo-housed polar bears, and further to investigate its validity through associations to behavioural and health-related indicators, as well as intra- and inter-day consistency of QBA scores. A list of 24 terms was developed by reviewing the literature and on-site assessments. Reliability of the list was tested through Kendall’s W between two assessors (Inter-OR), as well as over time (Intra-OR), based on videos. QBAs and behavioural observations were collected on 22 polar bears from nine zoos in four European countries, repeated within days (three times) and across days (four days). Behavioural observations were summarized as percentage of time spent in the respective categories, whereas behavioural diversity was expressed by the Shannon Index. Health-related indicators were expressed as an overall dichotomous value (presence/absence). Principal component analysis revealed two main components categorised as valence (PC1, 29.5%) and arousal (PC2, 15.1%). Reliability was met for both PCs, with a W of 0.82 for PC1 and 0.68 for PC2 for Inter-OR, and 0.92 for PC1 and 0.89 for PC2 for Intra-OR. PC1 was significantly positively associated with behavioural diversity (p = 0.006), environmental interaction (p = 0.006) and rest (p = 0.005), and inversely with stereotypic behaviour (p < 0.001) and general activity level (p = 0.003). PC2 was significantly positively associated with stereotypic behaviour (p < 0.001), environmental interaction (p = 0.040) and general activity level (p < 0.001), and inversely with awake inactivity (p = 0.002). Valence scores revealed no significant effect of time of day nor day, however a significant effect was found between early to mid-day on arousal scores (p = 0.015). The results provide evidence of sensitivity and some evidence of validity by associations of QBA with other welfare indicators. QBA may therefore potentially serve to assess emotional state in polar bears, needing only to be carried out once in the short term. Although the proposed list may benefit from additional validation and reliability testing, this study takes the first step towards a standardised QBA for polar bears.

V-QBA vs. QBA-How Do Video and Live Analysis Compare for Qualitative Behaviour Assessment?

Animal welfare is an inextricable part of livestock production and sustainability. Assessing welfare, beyond physical indicators of health, is challenging and often relies on qualitative techniques. Behaviour is a key component of welfare to consider and Qualitative Behaviour Assessment (QBA) aims to achieve this by systematically scoring behaviour across specific terms. In recent years, numerous studies have conducted QBA by using video footage, however, the method was not originally developed using video and video QBA (V-QBA) requires validation. Forty live QBAs were conducted, by two assessors, on housed beef cattle to help fill this validation gap. Video was recorded over the assessment period and a second video assessment was conducted. Live and video scores for each term were compared for both correlation and significant difference. Principle component analysis (PCA) was then conducted and correlations and differences between QBA and V-QBA for the first two components were calculated. Of the 20 terms, three were removed due to an overwhelming majority of scores of zero. Of the remaining 17 terms, 12 correlated significantly, and a significant pairwise difference was found for one (“Bored”). QBA and V-QBA results correlated across both PC1 (defined as “arousal”) and PC2 (defined as “mood”). Whilst there was no significant difference between the techniques for PC1, there was for PC2, with V-QBA generally yielding lower scores than QBA. Furthermore, based on PC1 and PC2, corresponding QBA and V-QBA scores were significantly closer than would be expected at random. Results found broad agreement between QBA and V-QBA at both univariate and multivariate levels. However, the lack of absolute agreement and muted V-QBA results for PC2 mean that caution should be taken when implementing V-QBA and that it should ideally be treated independently from live QBA until further evidence is published. Future research should focus on a greater variety of animals, environments, and assessors to address further validation of the method.

Qualitative behaviour assessment as part of a welfare assessment in flocks of laying hens

Animal welfare must be considered from a broad perspective, including positive emotional states. Qualitative behaviour assessment (QBA) is one of few scientific methods to assess positive emotional states of animals. QBA for poultry is included in the Welfare Quality® protocol, but has not been validated for laying hens. The aim of this study was to investigate the dimensionality of QBA for laying hens and the associations between the main principal components of QBA and selected animal-based welfare measures. A total of 22 flocks were visited between the age of 70–76 weeks. All flocks consisted of approximately 7500 white-strain hens (Dekalb White, n = 11; Lohman LSL, n = 11) with intact beaks, housed in indoor multi-tiered aviary systems. Each flock was assessed using a fixed list of QBA terms, in addition to scoring of plumage and fear, and collection of mortality data. QBA was analysed using principal component analysis (PCA), revealing three main dimensions that can be recognised from QBA in other species. These were labelled mood (PC1), alertness (PC2) and arousal (PC3), and explained 50.8%, 19.7%, and 12.0% of the variance, respectively (82.5% overall). There were no associations between the QBA scores and plumage score, fearfulness, or mortality in the flocks. The lack of significant associations might be due to a limited sample size, a homogenous study population or the inherent motivation in hens to suppress signs of weakness or sickness. QBA can nevertheless become an important tool for measuring emotional expressions in laying hens. However, the method needs further validation.

Behavioural assessment of sheep is sensitive to level of gastrointestinal parasite infection

Qualitative behavioural assessment (QBA) was applied to investigate the expressive behaviour of sheep with varying intestinal parasite burdens over two experiments. The expressive behaviour of sheep naturally infected with intestinal parasites was assessed from video footage collected in the paddock, and assessments were compared pre- and post-treatment with anthelmintic drench. The first experiment assessed sheep with a range of parasite burdens (n = 28), and the second compared sheep that expressed clinical symptoms of parasitism (Anaemic, n = 5) with those that did not (Non-anaemic, n = 5). Behavioural expression scores were validated against individual clinical evaluations (faecal egg counts – FEC, faecal consistency and anaemia scores), production parameters (body mass and body condition score), and quantitative locomotive measures (walking speed and return order to paddock). Twenty-two observers scored 28 video clips using QBA in experiment 1, and in the second experiment, 35 observers scored 20 video clips that depicted the 10 focal sheep pre- and post-treatment. QBA scores were analysed using Generalised Procrustes Analysis (GPA), and sheep scores on the main GPA dimensions were evaluated in relation to parasite burden using Spearman Rank correlations and repeated-measures ANOVA for experiment 1 and 2, respectively. In both experiments, observers reached significant (P < 0.001) consensus in their assessment of the behavioural expression of sheep. In experiment 1, sheep with higher FEC had lower anaemia scores (indicative of anaemia), poor body condition, lower body mass, walked slower, ranked lower in return order, and were scored by observers as more docile/at ease, and more assertive/motivated on GPA dimensions 1 and 3, respectively (P < 0.05). In experiment 2, observers scored Anaemic sheep as significantly more unsettled/apprehensive compared to Non-anaemic sheep on GPA dimension 1 (P < 0.05). In addition, observers consistently scored Non-anaemic sheep as more bright/observant following treatment on dimension 2 (P < 0.001). On dimension 3, all animals were scored by observers as less depressed/suspicious post-treatment (P < 0.05). An increase in average walking speed across all sheep was also identified post-treatment (P < 0.05). We conclude that under the conditions tested, QBA could provide information on the behavioural expression of sheep related to varying parasite burdens and the impact of treatment. The data presented herein offers proof of concept that assessments of behavioural expression could aid producers in the monitoring and management of parasitised sheep on-farm in terms of identification of individuals for treatment, and efficacy of anthelmintic treatment.

Intra- and Inter-Observer Reliability of Qualitative Behaviour Assessments of Housed Sheep in Norway.

Simple SummaryQualitative behaviour assessment (QBA) is a whole-animal approach to measuring animal welfare, based on observing the animal’s body language and behaviour. The method is used in different animal welfare protocols such as the Welfare Quality® (WQ®) protocols developed for poultry, cattle and swine and the AWIN protocols for sheep and goats. In Norway, farmed sheep are typically housed during the winter period for approximately six months and this presents specific risks for animal welfare, as well as specific opportunities for improvement. A welfare protocol for sheep managed under Norwegian housing conditions was developed for the Norwegian Sheep House (FåreBygg) project. In this study, we tested the reliability of QBA as developed for this protocol, when used by six trained observers with different professional background and experience, using video recordings. Intra-observer reliability was assessed by viewing the videos twice with a one-week interval between viewings. The statistical analyses revealed high agreement between all observers, and between scorings of the same observers at different time points. The results suggest that the tested protocol is reliable for assessing video recordings of sheep behaviour when applied by trained observers, regardless of their occupation with differing experiences of sheep health, welfare and production.This study tested the reliability of a Qualitative Behavioural Assessment (QBA) protocol developed for the Norwegian Sheep House (FåreBygg) project. The aim was to verify whether QBA scores were consistent between different observers, i.e., inter-observer reliability, and between scorings of the same observers on different time points, i.e., intra-observer reliability. Six trained observers, including two veterinary students, two animal welfare inspectors and two sheep farmers observed sheep in 16 videos, and independently scored 14 pre-defined behavioural descriptors on visual analogue scales (VAS). The procedure was repeated one week after the first scoring session. QBA scores were analysed using Principal Component Analysis. Inter- and intra-observer agreement was assessed using Kendall’s coefficient of concordance (W). Principal component 1 (PC 1) and 2 (PC 2) combined explained >60% of the total variation in the QBA scores in both scoring sessions. PC 1 (44.5% in sessions 1 and 2) ranged from the positive descriptors calm, content, relaxed and friendly to the negative descriptors uneasy, vigilant and fearful, and was therefore labelled mood. PC 2 (18% in session 1, 16.6% in session 2) ranged from bright to dejected and apathetic, and was therefore labelled arousal. Kendall’s coefficient of concordance of PC 1 for all observers was high in the two scoring sessions (W = 0.87 and 0.85, respectively), indicating good inter-observer reliability. For PC 2, the agreement for all observers was moderate in both video sessions (W = 0.45 and 0.65). The intra-observer agreement was very high for all observers for PC 1 (W > 0.9) except for one, where the agreement was considered to be high (W = 0.89). For PC 2, Kendall’s coefficient was very high for the veterinary students and interpreted as moderate for the two farmers and welfare inspectors. This study indicates that the QBA approach and the terms included in the Fårebygg protocol were reliable for assessing video recordings of sheep behaviour when applied by trained observers, regardless of whether they were a veterinary student, animal welfare inspector or sheep farmer. Further work is needed to examine the reliability of the QBA protocol when tested on-farms for sheep managed under Norwegian housing systems.

Using Qualitative Behaviour Assessment to Investigate Human-Animal Relationships in Zoo-Housed Giraffes (Giraffa camelopardalis).

Simple SummaryHuman-animal relationships can develop from repeated interactions between zoo animals and their keepers. Positive, neutral or negative interactions can result in positive, neutral or negative relationships. Qualitative behavior assessment (QBA) has been utilized as a method to assess emotional expression in animals, but this has yet to be applied to zoo-housed animals. This paper reports a small pilot study aimed at exploring the use of QBA to address human-animal relationships (HAR) in zoos. Three giraffes were video recorded during four different types of keeper-animal interaction producing 38 clips. Using QBA, 18 observers were instructed to describe and score the emotional expressions of the giraffes observed in the clips. In addition, keeper actions during the keeper-animal interactions were assigned positive and negative values by an independent marker, summarized into a final score characterizing their quality. Results indicate that positive keeper actions resulted in calm and confident giraffes with a willingness to interact, whereas negative interactions resulted in more anxious and startled giraffes who were more easily distracted. This suggests that the quality of interaction by keepers influenced the emotional expression of these giraffes, which may affect the giraffe-keeper relationship and have potential welfare implications.Human-Animal Relationships (HAR) in zoos develop from repeated interactions between animals and their caretakers. HAR have been shown to affect health and welfare in farm animals, but limited zoo-based studies exist. This study investigates the association between the qualitative behaviour assessment (QBA) of emotional expression in giraffes and keeper action score in four types of keeper-animal interaction (KAI). Three giraffes generating 38 clips. QBA, using a free-choice profiling methodology, was applied instructing 18 observers to assess giraffe expressions shown in these clips. QBA scores were analysed using Generalized Procrustes Analysis. Keeper actions during each KAI event were rated by an independent marker, resulting in cumulative scores for keeper action quality. The association between QBA and the keeper action was analyzed using Spearman’s rank correlations. Two main QBA dimensions were identified explaining 59% of the variation between clips. There were significant effects of giraffe and KAI type on QBA dimension 2 (inquisitive/impatient—calm/distracted), and significant positive associations between keeper action quality rating and QBA dimensions 1 and 2, indicating that positive keeper actions resulted in calm and confident giraffes with a willingness to interact. This is the first successful application of QBA for empirically addressing HARs in zoos, however given the small sample size of giraffes in this study, it can be regarded as a pilot study only, and further research is needed to validate the use of QBA in this context.

Artificial rearing affects piglets pre-weaning behaviour, welfare and growth performance

One strategy adopted on farms to deal with managing large litters involves removing piglets from their mothers at seven days old to be reared in specialised accommodation with milk replacer. Effects on piglet behaviour, growth and some aspects of welfare were evaluated in this study by comparing 10 pairs of two litters (one sow-reared: SR, one artificially-reared: AR) selected at seven days-old at a similar weight. Piglet behaviour was recorded for 20 min following transfer of AR piglets to the artificial-rearing enclosure (D0) and for 20 min hourly between 09:00 h and 17:00 h (8 h) on D5 and D12. Hourly 5 min live observations were also undertaken. Qualitative Behavioural Assessment (QBA) was conducted on D14 to evaluate piglets’ emotional state. Survival and illness events were recorded until weaning. On D0, D1, D8 and D15 piglets were weighed and scored for tear staining, dirtiness of the face and severity of lesions on the snout, limbs, ear and tail. Survival and illness rates, as well as the rates of behaviours/min were analysed using GLMMs. Weights and QBA scores were analysed using GLM. Lesions, tear staining and dirtiness scores were averaged per litter and analysed using GLM. When AR piglets were transferred to the artificial-rearing enclosure, their behaviour was not different to SR piglets. Over the two observation days, AR piglets performed more belly-nosing (F1,76.53 = 42.25; P < 0.001), nursing-related displacements (F1,79 = 19.32, P < 0.001), visits to the milk cup (compared to nursing bouts; F1,73.8 = 38.42, P < 0.001), and oral manipulation of littermates’ ears (F1,91.95 = 12.79, P < 0.001) and tails (F1,58.54 = 15.63, P < 0.001) than SR piglets. However, SR piglets played alone (F1,88.99 = 8.29, P < 0.005) and explored their environment (F1,99.42 = 4.52, P < 0.05) more frequently than AR piglets. The QBA scores indicated a lower emotional state in AR piglets (t25.1=-3.25, P < 0.05). Survival rate and overall illness rate of piglets were similar between the treatments. AR piglets experienced a growth check following their transfer to the artificial-rearing enclosure and remained lighter than SR piglets through to weaning (6.53 ± 0.139 kg vs. 7.97 ± 0.168 kg, t256 = 9.79, P < 0.001). Overall, snout lesion scores were not different between the treatments, but AR piglets had lower limb (F1,10.1 = 5.89, P < 0.05) and ear (F1,14.5 = 24.89, P < 0.001) lesion scores and higher tail lesion scores (F1,34.5 = 15.54, P < 0.001). AR piglets were dirtier (F1,17.4 = 23.38, P < 0.001) but had lower tear staining scores (F1,19.1 = 68.40, P < 0.001) than SR piglets. In conclusion, artificial rearing impaired piglets’ behaviour, welfare and growth.

What can the quantitative and qualitative behavioural assessment of videos of sheep moving through an autonomous data capture system tell us about welfare?

Sheep can be exposed to a variety of challenges and failure to adapt to these challenges can compromise their health and wellbeing. Regular monitoring of stock on large-scale or extensive systems may not always be possible, although recent technological advancements in automated data capture, such as walk-over-weighing (WoW), can make monitoring easier. The potential benefit of including behavioural assessment in such a system has yet to be tested. We investigated whether quantitative and qualitative behavioural assessment (QBA) methods could be applied to short video footage collected automatically within a WoW setup, to differentiate between sheep that were, presumably, in different (positive and negative) welfare states. Video footage was collected from 36 Merino sheep within the four treatment groups; Control (n = 12), Habituated to the WoW setup and human interaction (n = 8), Lame (n = 8) and Inappetent (n = 8). Habituated sheep were exposed to a low-stress handling regimen for six consecutive days prior to filming. At the same time, feeding behaviour was recorded by means of radio-frequency identification (RFID) technology to identify sheep suffering inappetence. Lame sheep were identified using a 6-point scoring system, and Control animals were selected ensuring that they were not Lame, Inappetent or Habituated. For QBA, the footage was presented, in a random order, to 18 observers. There was a significant (P < 0.001) consensus among the observers in their assessment of the behavioural expression of the sheep. Observers described the Habituated and Lame sheep as significantly more focused/collected/assured compared to the Control sheep (P < 0.05). There was no difference in observer scores between the Inappetent sheep compared to the Controls. A number of associations were found between the QBA scores and the quantitative behavioural measures recorded. Sheep that baulked more frequently at the entrance to the WoW system (Rs = −0.70; P < 0.001) or had a greater number of circling events (Rs = −0.68; P < 0.001) were described as more reluctant/tense/wary, while those that recorded faster walking speeds (Rs = 0.65; P < 0.001) or spent less time standing stationary (Rs= −0.48; P < 0.01) were described as more focused/collected/assured. We conclude that qualitative and quantitative behavioural measures can be used to identify differences in animal behaviour, presumably related to their welfare state, when applied to short video clips automatically collected in a WoW setup. These findings suggest that behavioural measures could be collected, practically, within automated biometric data capture systems to provide additional information to aid in the assessment of sheep welfare in extensive systems.

The Use of Qualitative Behaviour Assessment for the On-Farm Welfare Assessment of Dairy Goats.

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.

Dairy cows under experimentally-induced Escherichia coli mastitis show negative emotional states assessed through Qualitative Behaviour Assessment

Mastitis and associated pain have been identified as a major health and welfare problem affecting dairy cows, however little is known about how cows emotionally experience this illness. Qualitative behaviour assessment (QBA) is a ‘whole animal’ methodology for assessing animal emotion, through description and quantification of the expressive qualities of an animal’s dynamic style of behaving (eg as relaxed, anxious). The aim of this study was to use QBA to investigate whether emotional expression in dairy cows is affected by an experimental intra-mammary challenge (mastitis) with Escherichia coli, and to investigate the relationship of QBA scores with nine other clinical, physiological and behavioural welfare indicators.Six Holstein-Friesian cows were inoculated with E. coli in one healthy quarter. Evolution of the disease was assessed using bacteriological growth and somatic cell counts (SCC). The cows’ response to the challenge was assessed using QBA, clinical observations, data loggers, rumen temperature sensor, and physiological indicators (inflammation, stress) at ten time-points defining the phase of the disease: before inoculation (Phase 0: 0 h), in the pre-clinical Phase (Phase 1: 8 h), in the acute phase (Phase 2: 12 h, 16 h, 24 h) and in the remission phase (Phase 3 : 32 h, 40 h, 56 h, 64 h and 80 h post-inoculation (hpi)).Principal Component Analysis of QBA scores identified two main dimensions of cow expression: PC1, ranging from active/vigorous/happy/bright to suffering/dejected/lethargic, and PC2, ranging from fearful/tense/anxious to confident/calm/relaxed, together explaining 58% of the total variation. QBA PC1 and PC2 scores varied with mastitis phases: QBA PC1 scores decreased by 4.09 in Phase 2, and by 1.98 in Phase 3, reflecting suffering/dejected/lethargic expressivity. QBA PC2 scores decreased by 1.91 in Phase 3, reflecting a confident/calm/relaxed expressivity. Clinical and physiological welfare indicators were associated with QBA. The higher the udder severity score, the body temperature, the concentrations of cortisol, SAA, TNF-α, and IL-1β, the more the cows were suffering/dejected/lethargic (PC1) (coefficients: -0.51, -0.92, -2.46, 7.52 × 10−5, -0.72, -1.13 respectively).These findings indicate that dairy cows experienced negative emotional state in the acute phase and positive emotional state in the remission phase of mastitis. This suggests that provision of pain-relief treatment during mastitis may improve animal welfare, and potentially lead to faster disease remission. However the sample size of this study was small, and larger controlled studies are needed to further investigate these findings and hypotheses. The sensitivity of QBA in this small study suggests it could potentially be a useful tool for E. coli mastitis detection.

Using qualitative behaviour assessment (QBA) to explore the emotional state of horses and its association with human-animal relationship

This study aimed to apply qualitative behaviour assessment (QBA) to horses farmed in single boxes, in order to investigate their emotional state and explore its association with indicators of human-animal relationship. A fixed list of 13 QBA descriptive terms was determined. Three assessors experienced with horses and skilled in measuring animal behaviour underwent a common training period, consisting of a theoretical phase and a practical phase on farm. Their inter-observer reliability was tested on a live scoring of 95 single stabled horses. Principal Component Analysis (PCA) was conducted to analyse QBA scores and identify perceived patterns of horse expression, both for data obtained in the training phase and from the on-farm study. Given the good level of agreement reached in the training phase (Kendall W = 0.76 and 0.74 for PC1 and PC2 scores respectively), it was considered acceptable in the subsequent on-farm study to let these three observers each carry out QBA assessments on a sub-selection of a total of 355 sport and leisure horses, owned by 40 horse farms. Assessment took place immediately after entering the farms: assessors had never entered the farms before and were unaware of the different backgrounds of the farms. After concluding QBA scoring, the assessors further evaluated each horse with an avoidance distance test (AD) and a forced human approach test (FHA). A MANOVA test was used to assess the association of the AD and FHA tests with the on-farm QBA PC scores. The QBA approach described in this paper was feasible on farm and showed good acceptability by owners. In the analysis of on-farm QBA scores, the first Principal Component ranged from relaxed/at ease to uneasy/alarmed, the second Component ranged from curious/pushy to apathetic. Horses perceived as more relaxed/at ease with QBA showed less avoidance during the AD test (P = 0.0376), and responded less aggressively and fearfully to human presence in the FHA test (P < 0.0001). Our results support the hypothesis that QBA is sensitive to the quality of human contact in horses.

Emotions after victory or defeat assessed through qualitative behavioural assessment, skin lesions and blood parameters in pigs

Aggression between pigs causes injuries and production losses and is a long standing animal welfare issue. Although the physiological impact of aggression has been well described, little is known about the emotional experience of aggressive interactions. Our aim was to investigate the emotional expression of winners and losers after a fight and how this relates to costs of fighting. Emotions were studied through use of Qualitative Behavioural Assessment (QBA), a method where participants qualitatively assess the emotional expression of animals seen live or on video. Eighteen pig farmers watched 28 short video clips of pigs which had just won (n=14) or lost (n=14) a fight. Farmers rated the pigs’ emotions based on a pre-existing list with 21 descriptors of emotions, while being unaware of the contest outcome (winner/loser). Scores were analysed by a Principal Component Analysis (PCA), which resulted in two factors combining the 21 descriptors into four expressive quadrants. Factor 1 ranged from relaxed/content to tense/frustrated, thereby describing valence (explaining 43% of total variance), and factor 2 ranged from active/lively to listless/indifferent, describing arousal (explaining 16%). Winners (W) and losers (L) did not significantly differ in their expression of valence (W −0.19±−0.20; L 0.16±0.17; P=0.16) or arousal separately (W −0.07±0.22; L 0.06±0.18; P=0.51), but did in the valence-arousal interaction (P=0.02). In winners a high valence related to low arousal whereas in losers high valence related to high arousal. In addition, winners were observed as more negatively affected than losers by a high number of skin lesions (P<0.01). QBA scores significantly correlated with skin lesions (skin lesions positively correlated with 12 descriptive QBA terms reflecting impaired welfare), blood lactate (curious r=−0.41; lively r=−0.44; playful r=−0.40; positively occupied r=−0.39), blood glucose (distressed r=0.40; fearful r=0.39; playful r=−0.38) and the contest duration (sociable r=−0.39) (all P<0.05). This shows that skin lesions not only reflect physical injury but can also be associated with a negative emotional state, which adds value to their use as a welfare assessment tool. The use of QBA in this study sheds light on the complex ways in which animals emotionally perceive aggression and physical injury. Further studies of this kind will enable better understanding of the true welfare impact of aggressive interactions.

On-farm Qualitative Behaviour Assessment of dairy goats in different housing conditions

This study reports the results of the first investigation on the use of Qualitative Behaviour Assessment (QBA) in dairy goats, using a fixed-list of descriptors specifically developed for this species. It aimed to verify whether QBA can be reliably used by observers with different backgrounds to differentiate between the emotional states of goats kept under different environmental conditions. Two trained observers simultaneously assessed 16 dairy goat farms (8 “Housed” (H) farms, where animals were observed in free stall pens, and 8 “Pasture” (P) farms, where animals were observed in open ranges), using a list of 16 QBA descriptors that were based on literature studies and discussed within a focus group of goat experts. One H farm was removed from analysis due to procedural error. The QBA scores were analysed together using Principal Component Analysis (PCA, correlation matrix, no rotation). Observer agreement for farm scores on PCA Components (PCs) and on separate QBA terms was investigated using Pearson and Spearman correlations respectively. The effects of housing system and observer on PC scores were analysed using analysis of variance (treatments=observer, housing system, and their interaction; block=farm). PCA identified three main components explaining 60.87% of the total variation between goat farms: PC1 (29.04%) ranged from “content/calm” to “frustrated/aggressive”, suggesting a relationship to the animals’ general mood; PC2 (19.70%) ranged from “curious/attentive” to “calm/bored”, suggesting a relationship to the animals’ level of arousal, and PC3 (12.13%) ranged from “sociable/playful” to “alert/agitated”. The two observers showed a good level of agreement on the three PCA dimensions (PC1: r=0.75, P=0.001; PC2: r=0.67, P=0.006; PC3: r=0.69, P=0.004), and also on 7 out of 16 separate QBA descriptors (P<0.05). Two additional descriptors showed a moderate level of agreement (P=0.10). These results indicate an integrated PCA approach to QBA to be more robust. There were significant effects of housing system on both PC1 (ANOVA; P=0.05) and PC2 (P=0.02), indicating goats on P farms to be more “content/calm” and “curious/attentive” than goats on H farms. There was a significant observer effect on PC2 (P=0.04), and a significant observer by housing interaction on PC3 (P=0.009). In sum, these results suggest that QBA can be a reliable welfare indicator, used by observers with different backgrounds; however, further development of QBA training procedures is required to extend inter-observer reliability to all main expressive dimensions emerging from the analysis.

On-farm qualitative behaviour assessment in sheep: Repeated measurements across time, and association with physical indicators of flock health and welfare

Qualitative Behavioural Assessment (QBA) is a ‘whole-animal’ methodology that assesses the expressive qualities of animal behaviour using terms such as ‘tense’, ‘relaxed’, ‘anxious’, and ‘content’. The reliability and validity of QBA as an indicator for on-farm welfare assessment in pigs, cattle, poultry and sheep has been examined in a number of ways. However, the use of QBA on farms over longer periods of time has not yet been examined. The aim of this study was to investigate whether and how on-farm QBA of sheep varies over the different seasons of the year, and whether it is associated with physical measures of sheep health and welfare such as lameness. A trained assessor visited each of 12 farms six times within a one year period at two month intervals, and made group level assessments of approximately 100 sheep selected ad hoc (assuming homogeneity within the flock). The sheep flocks were assessed with a list of twelve QBA descriptive terms previously developed for sheep. Following QBA, the same sheep were also assessed with seven physical indicators of health and welfare (‘dull physical demeanour’, lameness, breech and abdominal soiling, pruritis, wool loss, and coughing). QBA scores from all visits were analysed together, and also in combination with the physical measures, with Principal Component Analysis (PCA – correlation matrix, no rotation). The effect of visit on PCA flock scores was analysed with random-effects multiple linear regression models. The association between PCA flock scores and physical measures was investigated using Spearman rank correlation (rS), and the correlation of flock rankings across visits was examined with Kendall Coefficient of Concordance. PCA distinguished two main dimensions of sheep expression: PC1 (47% variation) ranging from content/relaxed/thriving to distressed/dull/dejected (summarised as ‘mood’) and PC2 (21%), which ranged from anxious/agitated/responsive to relaxed/dejected/dull (summarised as ‘responsiveness’). No significant effect of visit on PC1 scores was found (p=0.155), and PC1 flock scores correlated at W=0.84 (p<0.001) across the 6 visits, indicating high consistency of characterisations of individual flock mood over the year. However there was an effect of visit on PC2 scores (p<0.001), and PC2 flock scores were correlated at W=0.60 (p<0.001) across visits, indicating that the presence of young lambs may have had a consistently relaxing effect on flocks. There was also an effect of visit period on lameness (p=0.025), and on breech (p<0.001) and abdominal (p=0.0048) soiling. With the exception of lameness and breech and abdominal soiling, the physical indicators were observed at a low prevalence (<2%) across the study farms. The highest lameness levels were observed during the winter period (mean 17.86%, 95% CI 7.83–27.90) whilst breech soiling was highest in spring (mean 23.83%, 95% CI 11.86–35.81). An effect of farm type was found on lameness scores (p=0.0176) and an effect of flock size on abdominal soiling scores (p=0.025). PC1 ‘mood’ scores were negatively correlated to the proportion of lame sheep (n=72; rS=−0.72, p<0.001), and to the proportion of animals with dull physical demeanour (rS=−0.70, p<0.001), while PC2 ‘responsiveness’ scores showed a weak correlation with breech soiling (rS=0.42, p<0.001). In summary, these results suggest that QBA has the potential to serve as a sensitive, meaningful indicator for on-farm welfare assessment in sheep.

Use of Qualitative Behaviour Assessment as an indicator of welfare in donkeys

One of the objectives of the Animal Welfare Indicators project was to develop animal-based indicators to assess donkey welfare, including their emotional state. This study aimed to develop a fixed rating scale of Qualitative Behaviour Assessment (QBA) for donkeys, to evaluate the inter-observer reliability when applied on-farm, and to assess whether the QBA outcomes correlate to other welfare measures.A fixed list of 16 descriptors was designed on the basis of a consultation in a focus group. The fixed list was then used by four trained observers to score nine 2min videos of groups of donkeys owned by six farms and on-farm to score 11 donkey facilities representative of the most common type of donkey facilities in Western Europe. On each farm one experienced assessor collected different welfare measures on all the adult donkeys. The QBA scores and welfare measures were analysed using Principal Component Analysis (PCA, correlation matrix, no rotation). Kendall's W and ANOVA were used to assess inter-observer reliability. PCA revealed three main components explaining 79% of total variation between them. PC1 ranged from at ease/relaxed to aggressive/uncomfortable, suggesting that this Component is important in the description of the valence of donkeys’ affective states. PC2 was more related to the level of arousal of donkeys, ranging from apathetic to distressed/responsive. The four assessors showed a good level of agreement on the first two dimensions of the PCA (Kendall's W varying from 0.61 to 0.90), and there was no significant effect of observer on donkey QBA scores (ANOVA p>0.05), both for the videos and on-farm. PCA of all measures together showed positive QBA descriptors on PC1 (relaxed, at ease, happy, friendly) to be associated with positive human–donkey interaction indicators (absence of tail tuck, no avoidance, and positive reaction to an assessor walking down the side of the donkey).Our findings suggest that QBA is a suitable tool to identify the emotional state of donkeys on-farm. A fixed list of descriptors can be used consistently by different trained assessors as a valid addition to a number of animal welfare assessment indicators.

Does the environmental background (intensive v. outdoor systems) influence the behaviour of piglets at weaning?

Under intensive pig husbandry, outdoor systems offer a more complex physical and social environment compared with indoor systems (farrowing sheds). As the rearing environment affects behavioural development, it can, therefore, influence behavioural responses of pigs to stressful environments in later stages of production. We tested how the rearing environment influenced behavioural responses to a novel arena test in piglets on the day that they were weaned and mixed into large groups. We recorded video footage and compared the behavioural responses of 30 outdoor-raised and 30 farrowing shed-raised piglets tested in an experimental arena and sequentially exposed to four challenges (each for 5 min) on the day of weaning. Quantitative and qualitative behavioural measures were recorded using time budgets and scoring demeanour or ‘qualitative behavioural expression’ (using Qualitative Behavioural Assessment (QBA)). When held in isolation (challenge 1), both groups were scored as more ‘scared/worried’, while outdoor-raised piglets spent more time eating and jumping against the arena walls. Both groups interacted with a plastic ball (challenge 2: exposure to a novel object) during which they were scored as more ‘playful/curious’ than other challenges. When a food bowl was introduced (challenge 3), farrowing shed-raised piglets were more interested in playing with the food bowl itself, whereas outdoor-raised piglets spent more time eating the feed. Finally, there were no significant differences in social behaviour (challenge 4: introduction of another piglet) between the two groups in terms of the latency to contact each other, amount of time recorded engaged in aggressive/non-aggressive social interactions or QBA scores. Although piglets spent 30% of their time interacting with the other piglet, and half of this time (47%) was engaged in negative interactions (pushing, biting), the levels of aggression were not different between the two groups. Overall, outdoor-raised piglets ate more and were scored as more ‘calm/passive’, whereas farrowing shed-raised piglets spent more time investigating their environment and were scored as more ‘playful/inquisitive’. In conclusion, we did not find differences in behaviour between outdoor-raised and farrowing shed-raised piglets that would highlight welfare issues. The differences found in this study may reflect conflicting affective states, with responses to confinement, neophobia and motivation for exploration evident.

Flooring and driving conditions during road transport influence the behavioural expression of cattle

This study examined whether observers could distinguish between cattle that were exposed to various road transport conditions: Experiment 1 compared a manipulated flooring treatment (non-grip flooring, NG) with a control transport event (grip flooring, G) and Experiment 2 compared a manipulated driving style (stop-start driving, SS) with a control transport event of smooth, continuous (C) driving. The behavioural expression of cattle was assessed through the process of Qualitative Behavioural Assessment (QBA), and these assessments were tested for correlation with various physiological parameters. Fourteen Angus steers were assessed. Blood samples were collected immediately before and after transport, and heart rate and core body temperature were measured continuously throughout each transport event. Continuous video footage recorded during each transport event was edited to isolate short clips of individual animals which were randomly ordered and shown to observers for QBA and analysis by Generalised Procrustes Analysis (GPA) which identifies common dimensions of behavioural expression. There was significant consensus amongst 39 observers in their assessment of behavioural expression of the cattle (P<0.001). In Experiment 1, observers scored cattle exposed to NG flooring during road transport relatively higher (on visual analogue scales) for terms such as ‘agitated’, ‘restless’ and ‘anxious’ compared with cattle exposed to G flooring, which were scored higher for ‘calm’, ‘comfortable’ and ‘relaxed’ (GPA dimension 1, P<0.001). In Experiment 2, cattle exposed to SS driving received higher average GPA dimension 1 scores (P<0.01) and higher GPA dimension 2 scores (P<0.05). These cattle were therefore scored relatively higher for terms such as ‘restless’, ‘agitated’ and ‘scared’ (GPA dimension 1) or ‘curious’, ‘interested’ and ‘inquisitive’ (GPA dimension 2) compared with cattle exposed to C driving, which were scored higher for ‘calm’, ‘relaxed’ and ‘comfortable’ (GPA dimension 1), or ‘stressed’, ‘tense’ and ‘alert’ (GPA dimension 2). There were some significant correlations between physiological responses and behavioural expression of animals for both experiments, with informative correlations between the different dimensions of behavioural expression and white blood cell counts, red blood cell parameters and heart rate. For example, the neutrophil: lymphocyte ratio, a typical marker of stress in ruminants, was elevated in cattle that were described as more ‘agitated’, ‘restless’ and ‘anxious’ (G-NG flooring: GPA dimension 1) or ‘stressed’, ‘tense’ and ‘alert’ (C-SS driving: GPA dimension 2). These results suggest that the QBA process captured behavioural manifestations of stress in cattle. We conclude that QBA is a valuable method of assessing cattle welfare under the conditions tested since there was significant consensus in the ability of human observers to interpret behavioural expression of cattle during these experimental conditions (i.e. QBA is repeatable), observers could distinguish between transport treatments on the basis of the animals’ QBA scores, and these scores were correlated with meaningful physiological measures.

Qualitative Behavioural Assessment of Angus steers during pre-slaughter handling and relationship with temperament and physiological responses

This study examined the behavioural expression of cattle immediately prior to slaughter through the process of Qualitative Behavioural Assessment (QBA), and compared these results to measurements of physiology and temperament. Twenty-eight Angus steers were filmed while in a funnel chute as they were being moved towards an abattoir killing box. Footage of cattle was shown in random order to 15 observers. Observers assessed the cattle using a qualitative approach based on Free Choice Profiling (FCP) methodology, which gives observers complete freedom to choose their own descriptive terms. Data were analysed with Generalised Procrustes Analysis (GPA). There was significant consensus (P<0.001) amongst observers in terms of their assessment of the behavioural expression of the cattle. Two main dimensions were identified, explaining 58.8% and 9.2% of the variation between animals, respectively. Low values for GPA dimension 1 were associated with terms such as ‘calm’ and ‘relaxed’ and high values associated with terms such as ‘nervous’ and ‘anxious’. Low values for GPA dimension 2 were associated with terms such as ‘annoyed’ and ‘frightened’ and high values associated with terms such as ‘curious’ and ‘interested’. We found no significant correlations between the QBA scores and three temperament measures (taken at weaning). However, cattle slaughtered towards the end of the line (rs=0.45, P=0.016) and cattle with a greater plasma lactate concentration (measured at exsanguinations) (R24=0.45, P=0.020) were attributed higher GPA dimension 1 scores (i.e. more ‘nervous’/‘anxious’). The only animal with an ultimate muscle pH>5.7 (classified as a ‘dark cutter’) had a low value for GPA dimension 2 (scored as relatively more ‘annoyed’/‘frightened’). The findings from this study suggest that QBA could contribute to assessing pre-slaughter animal handling, highlighting potential issues to be followed up with additional measures. The significant correlations between GPA dimension 1 with slaughter order and plasma lactate warrant further investigation, comparing behavioural expression with aspects of meat quality.