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A continuous recording approach to qualitative behaviour assessment in dairy buffaloes (Bubalus bubalis)
Applied Animal Behaviour Science 166 (2015) 35–43
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Applied Animal Behaviour Science journal homepage: www.elsevier.com/locate/applanim
A continuous recording approach to qualitative behaviour assessment in dairy buffaloes (Bubalus bubalis) Fabio Napolitano a,∗ , Giuseppe De Rosa b , Maria Serrapica a , Ada Braghieri a a b
Scuola di Scienze Agrarie, Forestali, Alimentari ed Ambientali, Università degli Studi della Basilicata, Italy Dipartimento di Agraria, Università degli Studi di Napoli “Federico II”, Italy
a r t i c l e
i n f o
Article history: Accepted 18 January 2015 Available online 7 February 2015 Keywords: Continuous recording Mediterranean dairy buffalo Observer training Qualitative behaviour assessment Temporal dominant behavioural expression
a b s t r a c t In order to develop a method suitable for a continuous qualitative evaluation of animal behaviour while it changes during the observation period, two recently described techniques, the Qualitative Behaviour Assessment (QBA) and the Temporal Dominant Behavioural Expression (TDBE), derived by the Temporal Dominance of Sensations, were used in combination and applied to 8 Mediterranean buffalo heifers. Animals were subjected to two isolation tests lasting 150 s each. One consisted in isolating individual animals from the rest of the group in the indoor part of the home pen, the other in leading animals individually to an outdoor paddock, which was novel to the animals. The behaviour of the animals was video-recorded and the resulting 16 video clips were assessed by a twelve-member trained panel with previous experience in animal behaviour observation. The TDBE allowed the QBA to be performed continuously (C-QBA) during the observation period on a pre-determined list of six behavioural descriptors. Data were subjected to analysis of variance using observer (n = 12), replication (n = 4), animal (n = 16) and the first order interactions as factors. Changes of behavioural expressions during the test were assessed by dividing it into three intervals of 50 s and using the 2 one-sample test to check the dominance of each descriptor in each interval. The Wilcoxon test was used to compare quantitative and qualitative behavioural variables as assessed indoors and outdoors. The low level of variance explained for each descriptor by the interactions animal × replication and animal × assessor as compared with the animal (the F of the factor animal was roughly 10 times higher than that of the interactions), showed the intra- and inter-observer reliability of the panel. Indoors, the dominant descriptors of buffalo behaviour (calm, apathetic and curious) were all indicative of a low level of arousal and frequently switched from one another. Outdoors, most of the animals were described with terms indicating a high level of arousal (e.g. Active and Nervous) and only at the end of the test they were generally scored as Curious. Accordingly, the dominance of the descriptor Curious changed during the test when the animals were tested outdoors (2 = 7.00, P < 0.05), whereas no significant changes were observed for all the other descriptors both indoors and outdoors (P > 0.05). The results indicate that C-QBA, if combined with the appropriate tools (i.e. TDBE), may be able to follow and describe the variations of animal behavioural expressions in time. © 2015 Elsevier B.V. All rights reserved.
∗ Corresponding author at: Scuola di Scienze Agrarie, Forestali, Alimentari ed Ambientali, Università degli Studi della Basilicata, Via dell’Ateneo Lucano 10, 85100 Potenza, Italy. Tel.: +39 0971205078; fax: +39 0971205378. E-mail address: [email protected] (F. Napolitano). http://dx.doi.org/10.1016/j.applanim.2015.01.017 0168-1591/© 2015 Elsevier B.V. All rights reserved.
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F. Napolitano et al. / Applied Animal Behaviour Science 166 (2015) 35–43
1. Introduction The interpretation of animal behaviour both in familiar (e.g. home pen) and unfamiliar environments (e.g. response to open field testing) may be difficult due to the coexistence of several motivations and emotions affecting animal behaviour. Numerous studies support the hypothesis that the assessment of animal behaviour through Qualitative Behaviour Assessment (QBA) can add important pieces of expressive information to animal studies, identifying differences in emotional valence that can be difficult to capture quantitatively, thus helping in the interpretation of this latter kind of data (Wemelsfelder et al., 2001; Napolitano et al., 2008). In fact, this methodology allows the description of how animals interact with the environment, including humans (Ellingsen et al., 2014), rather than measuring what they do, based on the use of qualitative behavioural descriptors. In most studies a free choice profiling (FCP) approach has been used where observers used different descriptors (e.g. Wemelsfelder et al., 2001 in pigs, Stockmana et al., 2013 in cattle). Therefore, agreement was assessed by comparing the entire vocabularies of all observers, rather than on comparison of scores generated for specific terms. Conversely, fixed-term lists were mostly used for welfare monitoring purposes where a standardised way of evaluation was needed for feasibility reasons (Wemelsfelder et al., 2009a; Bassler et al., 2013; Sant’Anna and Paranhos da Costa, 2013). In this case the observers should discuss the meaning of each term in order to standardise their evaluations. In addition, observer agreement on individual terms should be tested and the terms failing to reach good levels of agreement should be eliminated. Both FCP and fixed lists have advantages and disadvantages when used for qualitative assessment purposes, and each should be used when they are best suited. One advantage of FCP is that it provides information on how observers use single terms; therefore, the study of word charts allow to assess the degree of semantic convergence among the observers. However, following this methodology observers perform a post hoc evaluation (i.e. they score the descriptors of animal behaviour after that the animals have been observed). Therefore, when QBA is conducted following the FCP method, an overall evaluation of the behaviour observed in a certain period of time is performed, regardless of the fluctuations possibly occurring during that observation. Temporal Dominance of Sensations (TDS) is a methodology recently developed in the field of sensory analysis that gives the opportunity to describe the evolution of the dominant perceptions occurring during testing (Pineau et al., 2009). This methodology relies on the use of a fixed list of terms; on the meaning of these terms a selected panel has to previously agree. TDS experiments have been conducted to describe the temporal sensory patterns of different foods and beverages such as dairy products (Pineau et al., 2009), olive oil (Dinnella et al., 2012), fish sticks (Albert et al., 2012), etc. In addition, data analysis methodologies have been proposed to compare products (Meyners & Pineau, 2010) and to assess panel agreement (Meyners, 2011). In this study TDS has
been adapted to the assessment of animal behavioural expression and therefore called Temporal Dominant Behavioural Expression (TDBE). Therefore, in this study the qualitative approach to the study of animal behaviour has been paired with the TDBE methodology in order to verify whether QBA is not only valid (e.g. Napolitano et al., 2008; Rutherford et al., 2012; Stockman et al., 2011, 2013) and reliable (e.g. Wemelsfelder et al., 2001, 2009b) but it is also capable to capture the style of interaction of the animals with the environment in a dynamic manner. The specific question we aimed to answer was about whether QBA was able to continuously describe the behaviour while it changes during the observation period, that is whether fluctuations could be perceived by the observers, hence detected by the method, which was therefore called Continuous QBA (C-QBA).
2. Material and methods 2.1. Experimental procedure Eight Mediterranean buffalo heifers aged 16–18 months were used (see Napolitano et al., 2012 for details on animals and farming conditions). Animals were subjected to two different isolation tests. One consisted in isolating individual animals from the rest of the group in the indoor part of the home pen, and one in leading animals individually through a single-file chute to an outdoor paddock (5.0 m × 4.6 m, with earth floor and open metal fencing), which was novel to the animals and located approx. 20 m away from the home pen. Four animals were tested first in the home indoor pen and subsequently in the novel outdoor paddock; the other four were tested in the opposite order. During tests subjects were isolated from tactile and visual contact with conspecifics, but could receive auditory and olfactory stimuli from other animals; they could not receive any stimuli from humans. All testing procedures were performed by a stockperson well known to the animals. Each animal was confined individually for 150 s in each testing condition, and her behaviour during this time was video-recorded using a DVL-157 JVC video camera equipped with a wide-angle lens, located at a corner of the test area at a distance from the fence of 6 m and operated by remote control. From this material 16 clips (8 animals in two conditions: indoors and outdoors) of 150 s duration each were created. Thus the total duration of the video recording presented to observers was 40 min. Although the animals were subjected to handling and isolation, these procedures were similar to those routinely used in a commercial farm (e.g. handling performed to move the animals to different farm facilities, isolation for veterinary interventions, etc.). In any case, all aspects of the study adhered to the European legal requirements concerning the protection of both animals kept for farming purposes and animals used for scientific purposes (Dir. 98/58/EC and Dir. 2010/63/UE, respectively).
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2.2. Continuous qualitative behaviour assessment A twelve-member panel (3 female and 9 male, aged 22–29 years) was used. Panellists were undergraduate and graduate animal science students recruited from the University of Basilicata. Panellist selection was based on willingness to participate, previous experience in animal behaviour observation, ability in generation of terms for qualitative behaviour assessment and discrimination of animal responses to different environmental challenges according to a predetermined list of terms. They were paid for their participation in the study. The socio-demographic features of the subjects participating to the qualitative behaviour assessment are reported in Table 1. Six behavioural descriptors were chosen according to the frequency of elicitation performed by three panels in a previous study (Napolitano et al., 2012). They were: “calm”, “active”, “curious”, “nervous”, “shy” and “apathetic”. 2.2.1. Panel training The definitions of behavioural descriptors are reported in Table 2. Such definitions were used for assessor training and were available both during the training and the experimental observations. Panel training consisted of seven preliminary sessions of 45 min each. Two of them were used to teach panellists how to use the TDBE computerised data acquisition system. The following five sessions were used to train the assessors to the continuous evaluation of the behavioural descriptors to be used during the C-QBA. During session three the assessors watched six clips (10–15 s each) representing the standard for each descriptor (learning phase). In particular, each clip showed an animal expressing one of the behavioural descriptor at high intensity. The objective of this session was the memorisation of the six behavioural descriptors through the observation of the clips, the corresponding descriptors and their definitions. During sessions four and five the assessors evaluated 18 clips (10–15 s each) showing the expression of each behavioural descriptor at medium and high intensity. Three-digit numbers identified clips. The assessors evaluated individual clips by indicating the dominant behavioural descriptor with the help of the descriptor list and definitions. During the last two sessions the assessors evaluated the same clips and were asked to indicate both the dominant behavioural descriptor and its perceived intensity. 2.2.2. Assessment through temporal dominant behavioural expression The clips were assessed according to the TDBE procedure (Pineau et al., 2009). The TDBE method consisted in presenting to the panellists the entire list of behavioural descriptors on a computer screen along with each clip. Each assessor was then asked to select the dominant descriptor and to score its intensity level on an unstructured scale of 100 mm length (0 mm: descriptor absent; 100 mm: descriptor could not be stronger). A behavioural descriptor was considered as dominant when it gained most of the attention of the observer (i.e. the most striking impression at a given time). Thereafter, each time the observer felt the behaviour changed, either in intensity or in quality, he/she
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scored the new dominant descriptor (or the new descriptor level), until the clip ended. During the observation of each clip the panellists were free to choose a descriptor several times, whereas other descriptors could be completely ignored. Each clip was identified by a three-digit code and observed 4 times by each observer (4 replications) in a randomised order. The order of the descriptors was also randomised across assessors although it did not change within assessors. Each assessor observed eight clips in each session. Five min intervals were given between two series of four clips. A total of sixteen clips (eight animals in two conditions) by four replications were observed in 8 sessions of about 25 min each. These four replications were performed in order to stay well above the suggested value of 30 evaluations for each item (12 observers × 4 replications = 48 evaluations) as suggested by Pineau et al. (2012). 2.3. Continuous quantitative behaviour assessment The behaviour shown by buffalo heifers in the 16 video clips was analysed quantitatively by means of continuous recording technique using the software The Observer XT version 8.0 (Noldus Information Technology). One trained observer performed all the observations. Training consisted in the observation of 3 outdoor and 3 indoor clips with the aim to instruct the observer in recognising the behavioural categories identified in a previous study (Napolitano et al., 2012). The behaviours recorded are described briefly in Table 3. These behaviours are indicated in the text as quantitative variables. 2.4. Statistical analysis TDBE data were acquired and processed through the software FIZZ (Biosystemes, Couternon, France), version 2.31G. For each clip, each observer, each replication and each descriptor the total dominance duration in s was computed. For each point of time (recorded at 2 s intervals), the proportion of runs (observer × replication) for which a given descriptor was selected (i.e. assessed as dominant), was computed and called dominance rate (%). These calculations allowed the construction of the TDBE curves for each animal. The chance level and significance level were reported along with TDBE curves. The chance level (P0 ) is the dominance rate that a descriptor can obtain by chance (P0 = 1/p, where p is the number of descriptors). Descriptors with dominant rates below the chance level are negligible. The significance level is the minimum value that a descriptor should reach to be deemed significantly higher than the chance level. Therefore, TDBE curves above the significance level can be considered consistent across the observers. The signifiaccording to the following cance level (Ps ) was calculated formula: Ps = P0 + 1.645 P0 (1 − P0 )/n, where n = number of observers × replications (Pineau et al., 2009). The software also allowed collecting the intensity level for each point of time. As suggested by Labbe et al. (2009), on the basis of the duration of dominance and intensity levels the following scores were calculated: Score = ( Scoring Inten sity level × Duration)/( Scoring Duration). Dominance
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F. Napolitano et al. / Applied Animal Behaviour Science 166 (2015) 35–43
Table 1 Socio-demographic features of the subjects participating to the continuous qualitative behaviour assessment. Participant
Sex
Age
Educational level
N. family components
1 2 3 4 5 6 7 8 9 10 11 12
F M M M F M M M M M F M
27 24 23 24 34 28 22 22 29 24 29 24
PhD student Graduated High school Graduated Graduated Graduated High school High school Graduated High school PhD student High school
4 3 4 4 4 4 4 4 3 2 2 4
Table 2 Descriptors and definitions used for assessor training to continuous qualitative behaviour assessment. Descriptor
Definition
Calm Active Curious
The animal moves slowly with head raised but without overt signs of vigilance and/or agitation The animal shows high levels of general activity and vigilance with sustained locomotion The animal is explorative, sniffing partitions or other environmental stimuli such as the ground with lowered head. Locomotion is present but not sustained The animal is frightened, showing sudden, exaggerated reactions to environmental stimuli The animal moves slowly showing circumspection, uncertainty and insecurity. Avoidance reactions are displayed even to neutral stimuli The animal is indifferent to the environment showing low levels of activity and locomotion
Nervous Shy Apathetic
durations and scores of the descriptors are indicated in the text as qualitative variables. For each descriptor and each animal the values of dominance durations and scores were subjected to analysis of variance using observer (12), replication (4), animal (16) and the first order interactions as factors. In order to verify possible changes of behavioural expressions during the test (duration = 150 s), test duration was divided into three intervals of 50 s. For each descriptor the frequency of occurrences of dominance in each testing condition was analysed using a 2 (dominance presence vs. absence) × 3 (test intervals) 2 test. A principal component analysis (PCA) was used to investigate the relationship between quantitative and qualitative data, and to indicate which variables were most closely associated in explaining the variation between clips. The PCA was based on the dominance durations and scores obtained from TDBE and on quantitative behaviour data recorded during the two isolation tests through the Observer XT. A correlation matrix was used and no
rotation was applied. The analysis was performed using the software Unscrambler X v.10.1. The Wilcoxon test was used to compare both quantitative variables (recorded through The Observer XT) and qualitative variables recorded through TDBE (mean values of dominance durations and scores) as assessed indoors and outdoors.
3. Results 3.1. Observer reliability The analysis of variance of the qualitative variables (mean duration and score) showed no significant interaction animal × replication, thus indicating that the behaviour of the animals was not assessed differently in different replications. Although the interaction animal × assessor was always significant (P < 0.001), the F of the factor animal was roughly 10 times higher than that of
Table 3 Description of behavioural categories continuously recorded through The Observer XT version 8.0 (Noldus Information Technology) during the indoor and outdoor isolation tests. Variable
Definition
Inactive (duration) Walking (duration) Running (duration) Flight attempts (frequency)
Standing or lying, no overt activity. Walking slowly, looking in front or around. Rapid forward movement including gallop and trotting. Fast run towards the fence abruptly interrupted either before or after crashing into it. Final posture with head protruding beyond the fence. Standing still with elevated neck and intently oriented head. Walking slowly with the neck horizontal often interrupted by stopping and sniffing the ground or the fence. Emission of acoustic signals. Circular movements of the tail. Emission of urine and faeces.
Vigilance (duration) Exploration (duration) Vocalisation (frequency) Tail movement (duration) Urination/defecation (duration)
F. Napolitano et al. / Applied Animal Behaviour Science 166 (2015) 35–43 Table 4 F values of the descriptors used in the continuous qualitative assessment. Variables Duration Calm Active Curious Nervous Shy Apathetic Score Calm Active Curious Nervous Shy Apathetic
Animal
Animal × assessor
Animal × replication
47.46 87.70 107.11 323.72 29.43 167.03
4.91 6.93 3.23 7.87 3.67 5.16
0.95 0.94 1.03 1.03 0.86 0.82
17.24 51.04 23.89 191.09 32.66 76.66
2.12 3.75 2.47 4.41 2.84 2.88
1.16 1.10 0.90 1.21 1.01 0.83
the interaction (Table 4), which was therefore considered negligible, thus suggesting satisfactory panel reliability. Another measure of observer reliability is given by the calculation of the dominant descriptors as performed through TDBE. In particular, Figs. 1 and 2 show most of the time descriptors above the level of significance that can be interpreted as consistent across the observers (Pineau et al., 2009). 3.2. Continuous qualitative behaviour assessment Figs. 1 and 2 display the TDBE curves of the same buffalo heifer (animal number 1) in the two testing conditions (indoors and outdoors, respectively). The chance level, which is the dominance rate that a descriptor can be obtained by chance, was 0.167, corresponding to a dominance rate of 17%. Accordingly, attributes presenting dominance rates below 17% were not considered dominant. The significance level was calculated taking into account the chance level and the 48 evaluations performed by the panel (12 observers × 4 replications) and was 0.259, corresponding to a dominance rate of 26% (see Pineau et al., 2009 for more details). Fig. 1 shows that indoors this animal interchanged between three dominant behavioural descriptors (calm, apathetic and curious). None of them was dominant for more than 23 s. The first dominant descriptor was Calm from 3 to 15 s, from 51 to 82 s, with the highest dominance rate at s 77 (42.5%), and then maintained a steady dominance rate from 102 to 123 s. The second dominant descriptor was Apathetic. This descriptor showed two distinct peaks from 15 to 38 s and then from 124 to 139 s, with the highest dominance rate at 32 s (65%). Curious was the third dominant descriptor, which peaked from 39 to 50 s, from 83 to 101 s (the highest dominance rate was observed at 91 s with a value of 72.5%) and then prevailed from 140 s to the end of the test (150 s). The same animal showed a completely different pattern in outdoor conditions (Fig. 2). Only two descriptors were dominant throughout the test. Nervous was scored as dominant from the beginning of the test (3 s) to 136 s (more than 2 min corresponding to 89% of the time). The highest dominance rate was reached at 12.5 s (88%). Subsequently, curious dominated from 137 s to the end of the test (150 s)
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with a maximum of dominance rate of 69% at 138 s. For sake of brevity the remaining 14 curves of the other 7 buffaloes are not shown. In agreement with the previously described results, the 2 test showed that the dominance of the descriptor Curious changed during the test when the animals were tested outdoors (2 = 7.00, P < 0.05), whereas no significant changes were observed for all the other descriptors both indoors and outdoors (P > 0.05). In particular, the dominance of Curious moved from 25.0 and 16.7% in the first and second interval of observation, respectively, to 58.3% in the third interval. Table 5 shows duration and score of the qualitative variables and the results of the analysis conducted using the Wilcoxon test. As to score, Curious, Shy and Calm showed no significant differences, Active and Nervous were higher outdoors and apathetic was higher indoors (P < 0.05). Similar results were obtained for duration, although only Curious showed no significant differences. Calm, Shy and Apathetic were higher indoors, whereas Active and Nervous were higher outdoors (P < 0.05). 3.3. Continuous quantitative behaviour assessment Table 5 also reports quantitative variables as assessed indoors and outdoors. The Wilcoxon test showed that buffalo heifers were more inactive (P < 0.05) and tended to urinate/defecate more indoors than outdoors (P < 0.10). Conversely, outdoor animals were vigilant and run for longer (P < 0.05) and tended to perform a higher number of flight attempts (P < 0.10). No other differences between indoor and outdoor tests were observed for any other quantitative variables. 3.4. The relationship between quantitative and qualitative variables The PCA of qualitative (score and duration from TDBE) and quantitative (from the software The Observer XT) data yielded two main components explaining 43% and 17% of the variation among experimental subjects, respectively. Fig. 3 displays the loadings of the different variables on these two components. The highest positive loadings on the first PCA component were shown by duration of Nervous (0.26), intensities of Nervous (0.28) and Active (0.28) and the quantitative variable Tail movements (0.25), whereas durations of Shy (−0.26) and Apathetic (−0.26), intensities of Shy (−0.26), Apathetic (−0.30) and Calm (−0.26) and the quantitative variable Inactive (−0.29) displayed the highest negative loadings. Duration and score of Curious (0.48 and 0.40, respectively) and the quantitative variable Exploration (0.41) showed the highest positive loadings on the second PCA component, whereas the quantitative variable Walking (−0.36) was the only one receiving a high negative loading on the second component. 4. Discussion Both the results obtained from the analysis of variance and those produced by TDBE consistently showed the reliability of the panel used for the dynamic qualitative behaviour assessment. These results on one hand
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Fig. 1. TDBE (Temporal Dominant Behavioural Expression) curves describing the behavioural expressions of animal 1 during the indoor test. The curves describe the agreement between observers on the dominant descriptors as the trial proceeded. When reliability is above the level of significance a descriptor can be considered consistent across the observers.
confirmed that the training (based on a combination of term descriptions and video references) was effective in gaining alignment in the panel, on the other were fundamental to perform subsequent analyses and allow sound interpretations of data. Indoors the behaviour of buffaloes was not characterised by a particular trend and the dominant descriptors (Calm, Apathetic and Curious), which were all indicative of a low level of arousal, frequently switched from one another (Fig. 1). More importantly, the animals started to be scored as Curious soon after the test started. This descriptor is mainly linked to the explorative activity of the animals (see Table 2 for the definition of the qualitative descriptor Curious and Fig. 3 showing the correlation of this descriptor with the quantitative variable Exploration), which was possibly induced by the novel social
condition (isolation) produced by the experimental procedure. In fact, when the environment is very familiar to the animals, exploratory behaviour is usually not performed. However, this behaviour reappears when any changes occur in the home environment. An early engagement in exploration may be due to the fact that the animals were in their home pen, thus confident enough to start the exploration of the environment soon. According to Hogan (2005), fear and exploration are not independent and the latter is performed only at low levels of fear. The same animals showed a different behavioural pattern when tested outdoors. Through C-QBA most of the animals were described with terms indicating a high level of arousal (e.g. Active, Nervous) and only at the end of the test they were generally scored as Curious (Fig. 2). An outdoor setting unknown to the animals may have, at least initially, induced a fear
Fig. 2. TDBE (Temporal Dominant Behavioural Expression) curves describing the behavioural expressions of animal 1 during the outdoor test. The curves describe the agreement between observers on the dominant descriptors as the trial proceeded. When reliability is above the level of significance a descriptor can be considered consistent across the observers.
F. Napolitano et al. / Applied Animal Behaviour Science 166 (2015) 35–43
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Table 5 Mean ± sd (min–max) of quantitative variables continuously recorded through The Observer XT version 8.0 (Noldus Information Technology) and qualitative variables continuously recorded through Temporal Dominant Behavioural Expression (duration and score). Variables Quantitative Inactive (s) Walking (s) Running (s) Flight attempts, n Vigilance (s) Exploration (s) Vocalisation, n Tail movement (s) Urination/defecation (s) Duration Calm Active Curious Nervous Shy Apathetic Score Calm Active Curious Nervous Shy Apathetic a
Indoor
Outdoor
Za
P
54.4 30.8 0.0 0.0 5.1 52.1 5.5 84.4 10.4
± ± ± ± ± ± ± ± ±
36.8 (9.0–123.0) 24.1 (0.0–65.0) 0.0 (0.0–0.0) 0.0 (0.0–0.0) 13.0 (0.0–37.0) 19.3 (17.0–70.0) 7.4 (0.0–21.0) 35.4 (20.0–133.0) 13.5 (0.0–38.0)
15.5 25.1 11.3 1.5 16.1 74.5 4.5 99.9 0.0
± ± ± ± ± ± ± ± ±
22.3 (0.0–54.0) 16.4 (0.0–45.0) 16.9 (0.0–48.0) 1.9 (0.0–5.0) 18.1 (0.0–54.0) 35.3 (43.0–131.0) 5.7 (0.0–13.0) 44.1 (17.0–139.0) 0.0 (0.0–0.0)
−2.52 −0.28 −2.02 −1.82 −2.37 −1.12 −0.27 −1.12 −1.83
0.012 0.779 0.043 0.068 0.018 0.263 0.787 0.263 0.068
46.0 14.7 41.7 1.5 11.4 27.4
± ± ± ± ± ±
12.9 (24.7–62.7) 20.2 (0.6–60.8) 18.1 (11.5–65.5) 2.1 (0.0–5.8) 9.8 (0.5–25.1) 28.0 (3.7–83.7)
19.4 26.6 48.7 34.6 6.6 8.5
± ± ± ± ± ±
15.3 (2.7–43.3) 23.0 (7.3–70.6) 30.9 (23.4–100.8) 36.1 (0.9–90.4) 7.7 (0.0–19.6) 11.0 (0.0–26.2)
−2.10 −2.24 −0.42 −2.52 −2.24 −2.52
0.036 0.025 0.674 0.012 0.025 0.012
44.9 17.3 48.2 2.9 22.4 33.7
± ± ± ± ± ±
9.1 (27.6–53.0) 16.7 (1.6–49.2) 11.6 (24.2–59.4) 3.0 (0.0–7.7) 13.7 (1.5–40.4) 22.3 (5.7–68.7)
32.6 41.7 53.6 36.1 18.7 17.1
± ± ± ± ± ±
18.4 (8.2–58.5) 12.2 (27.6–56.6) 10.7 (36.4–68.9) 26.3 (2.2–72.5) 17.2 (0.0–44.6) 20.1 (0.0–52.5)
−1.26 −2.52 −0.70 −2.52 −0.98 −2.52
0.208 0.012 0.483 0.012 0.327 0.012
Statistics used in the Wilcoxon test.
Fig. 3. Principal component analysis performed on quantitative variables continuously recorded through The Observer XT version 8.0 (Noldus Information Technology) and qualitative variables continuously recorded through Temporal Dominant Behavioural Expression (D = duration, S = score).
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(flight) response (see Fig. 3 showing the correlation of the qualitative descriptors Nervous and Active with the quantitative variables Flight attempts and Running) and only at the end of the test, after a certain degree of habituation, the animals possibly started to be more curious. The results concerning the qualitative descriptors perfectly matched those obtained in the quantitative assessment: no differences were observed between the mean values of dominance duration and score for Curious as assessed indoors and outdoors through C-QBA; no differences were observed for the expression of quantitative variables such as Exploration and Walking. Conversely, other quantitative variables, such as Running, Vigilance and Flight attempts, all indicative of high levels of arousal, alert and fear, discriminated the behaviour expressed indoors from that expressed outdoors; the same did the qualitative descriptors Nervous and Active. Accordingly, the quantitative variable Inactive and the qualitative descriptor Apathetic, overtly indicating a low level of arousal, were higher in indoor conditions. A good degree of agreement between quantitative and qualitative variables is also shown by principal component analysis. This multivariate analysis displayed a meaningful convergence of quantitative and qualitative variables. However, C-QBA was able to give information additional to those obtained through quantitative variables or standard QBA by detecting the changing features of the behaviour in time. For instance, in a study conducted by Morgan et al. (2014), socialised piglets were scored as less curious than control non-socialised animals when mixed with unknown conspecifics. However, no information could be collected about the variation of this and other behavioural expression as the time progressed. Similarly, Stockmana et al. (2013) observed a significant effect of driving style on cattle behavioural expression, but they were unable to monitor any changes during transport. Conversely, in our study C-QBA showed that the descriptor Curious, albeit not significantly different between indoor and outdoor conditions in quantitative terms, was visible only at the end of the outdoor test, whereas indoors it was detectable independently from time. Several studies on animal behaviour are based on continuous recording (see Martin and Bateson, 2007 for a detailed description of the method). When a quantitative variable is continuously recorded a precise pattern of the behaviour is gathered in terms of frequencies and durations; other pieces of information, such as when a particular behavioural expression starts and when it stops, can also be obtained. However, subtle and continuous changes in the emotional state of the animals cannot be detected unless a more sensitive tool is adopted. C-QBA seems to possess the requisites to identify and follow the fluctuations of such animal behavioural expressions. 5. Conclusion The results obtained in this study indicate that C-QBA, if combined with the appropriate tools, may be able to follow the variation of animal behaviour in time, as no other method does. In a previous work QBA associated with FCP was able to detect higher levels of activity and nervousness
in the animals recorded in the outdoor novel environment, as compared with buffaloes observed in indoor familiar conditions. This study confirmed the previous findings. However, the combination of C-QBA with TDBE, even in a short period of observation, allowed monitoring the variation of the dominant behavioural expressions, such as the gradual reduction of the buffalo fear response to the novel environmental conditions experienced outdoors, as suggested by the concomitant increase of curiosity. Acknowledgments Thanks are due to Smell and Taste Association (Potenza, Italy) for help in conducting the video assessment and to A.M. Riviezzi and G. Migliori for expert technical assistance. The authors want to express a special thank to Francoise Wemelsfelder for comments on the early draft of the manuscript and the enthusiasm about QBA she conveyed to them. References Albert, A., Salvador, A., Schlich, P., Fiszman, S., 2012. Comparison between temporal dominance of sensations (TDS) and key-attribute sensory profiling for evaluating solid food with contrasting textural layers: fish sticks. Food Qual. Pref. 24, 111–118. Bassler, A.W., Arnould, C., Butterworth, A., Colin, L., De Jong, I.C., Ferrante, V., Ferrari, P., Haslam, S., Wemelsfelder, F., Blokhuis, H.J., 2013. Potential risk factors associated with contact dermatitis, lameness, negative emotional state, and fear of humans in broiler chicken flocks. Poult. Sci. 92, 2811–2826. Dinnella, C., Masi, C., Zoboli, G., Monteleone, E., 2012. Sensory functionality of extra-virgin olive oil in vegetable foods assessed by temporal dominance of sensations and descriptive analysis. Food Qual. Pref. 26, 141–150. Ellingsen, K., Coleman, G.J., Lund, V., Mejdell, C.M., 2014. Using qualitative behaviour assessment to explore the link between stockperson behaviour and dairy calf behaviour. Appl. Anim. Behav. Sci. 153, 10–17. Hogan, J.A., 2005. Motivation. In: Bolhuis, J.J., Giraldeau, L.A. (Eds.), The Behaviour of Animals. Blackwell, USA, pp. 41–70. Labbe, D., Schlich, P., Pineau, N., Gilbert, F., Martin, N., 2009. Temporal dominance of sensations and sensory profiling: a comparative study. Food Qual. Pref. 20, 216–221. Martin, P., Bateson, P., 2007. Measuring Behaviour. An Introductory Guide. Cambridge University Press, Cambridge, UK. Meyners, M., 2011. Panel and panelist agreement for product comparisons in studies of temporal dominance of sensations. Food Qual. Pref. 22, 365–370. Meyners, M., Pineau, N., 2010. Statistical inference for temporal dominance of sensations data using randomization tests. Food Qual. Pref. 21, 805–814. Morgan, T., Pluske, J., Miller, D., Collins, T., Barnes, A.L., Wemelsfelder, F., Fleming, P.A., 2014. Socialising piglets in lactation positively affects their post-weaning behaviour. Appl. Anim. Behav. Sci. 158, 23–33. Napolitano, F., De Rosa, G., Braghieri, A., Grasso, F., Bordi, A., Wemelsfelder, F., 2008. The qualitative assessment of responsiveness to environmental challenge in horses and ponies. Appl. Anim. Behav. Sci. 109, 342–354. Napolitano, F., De Rosa, G., Braghieri, A., Grasso, F., Wemelsfelder, F., 2012. Qualitative behaviour assessment of dairy buffaloes (Bubalus bubalis). Appl. Anim. Behav. Sci. 141, 91–100. Pineau, N., Schlich, P., Cordelle, S., Mathonnière, C., Issanchou, S., Imbert, A., Rougeaux, M., Etièvant, P., Koster, E., 2009. Temporal Dominance of Sensations: construction of the TDS curves and comparison with TI. Food Qual. Pref. 20, 450–455. Pineau, N., Goupil de Bouillé, A., Lepage, M., Lenfant, F., Schlich, P., Martin, N., Rytz, A., 2012. Temporal Dominance of Sensations: what is a good attribute list? Food Qual. Pref. 26, 159–165. Rutherford, K.M.D., Donald, R.D., Lawrence, A.B., Wemelsfelder, F., 2012. Qualitative behaviour assessment of emotionality in pigs. Appl. Anim. Behav. Sci. 139, 218–224.
F. Napolitano et al. / Applied Animal Behaviour Science 166 (2015) 35–43 Sant’Anna, A.C., Paranhos da Costa, M.J.R., 2013. Validity and feasibility of qualitative behavior assessment for the evaluation of Nellore cattle temperament. Livest. Sci. 157, 254–262. Stockman, C.A., Collins, T., Barnes, A.L., Miller, D., Wickham, S.L., Beatty, D.T., Blache, D., Wemelsfelder, F., Fleming, P.A., 2011. Qualitative behavioural assessment and quantitative physiological measurement of cattle naive and habituated to road transport. Anim. Prod. Sci. 51, 240–249. Stockmana, C.A., Collins, T., Barnes, A.L., Miller, D., Wickham, S.L., Beatty, D.T., Blache, D., Wemelsfelder, F., Fleming, P.A., 2013. Flooring and driving conditions during road transport influence the behavioural expression of cattle. Appl. Anim. Behav. Sci. 143, 18–30.
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Wemelsfelder, F., Hunter, T.E.A., Mendl, M.T., Lawrance, A.B., 2001. Assessing the whole animal: a free choice profiling approach. Anim. Behav. 62, 209–220. Wemelsfelder, F., Millard, F., De Rosa, G., Napolitano, F., 2009a. Qualitative behaviour assessment. In: Forkman, B., Keeling, L. (Eds.), Welfare Quality® Report No. 11—Assessment of Animal Welfare Measures for Dairy Cattle, Beef Bulls and Veal Calves. Cardiff University, Cardiff, pp. 215–224. Wemelsfelder, F., Nevison, I., Lawrence, A.B., 2009b. The effect of perceived environmental background on qualitative assessment of pig behaviour. Anim. Behav. 78, 477–484.
Contents lists available at ScienceDirect
Applied Animal Behaviour Science journal homepage: www.elsevier.com/locate/applanim
A continuous recording approach to qualitative behaviour assessment in dairy buffaloes (Bubalus bubalis) Fabio Napolitano a,∗ , Giuseppe De Rosa b , Maria Serrapica a , Ada Braghieri a a b
Scuola di Scienze Agrarie, Forestali, Alimentari ed Ambientali, Università degli Studi della Basilicata, Italy Dipartimento di Agraria, Università degli Studi di Napoli “Federico II”, Italy
a r t i c l e
i n f o
Article history: Accepted 18 January 2015 Available online 7 February 2015 Keywords: Continuous recording Mediterranean dairy buffalo Observer training Qualitative behaviour assessment Temporal dominant behavioural expression
a b s t r a c t In order to develop a method suitable for a continuous qualitative evaluation of animal behaviour while it changes during the observation period, two recently described techniques, the Qualitative Behaviour Assessment (QBA) and the Temporal Dominant Behavioural Expression (TDBE), derived by the Temporal Dominance of Sensations, were used in combination and applied to 8 Mediterranean buffalo heifers. Animals were subjected to two isolation tests lasting 150 s each. One consisted in isolating individual animals from the rest of the group in the indoor part of the home pen, the other in leading animals individually to an outdoor paddock, which was novel to the animals. The behaviour of the animals was video-recorded and the resulting 16 video clips were assessed by a twelve-member trained panel with previous experience in animal behaviour observation. The TDBE allowed the QBA to be performed continuously (C-QBA) during the observation period on a pre-determined list of six behavioural descriptors. Data were subjected to analysis of variance using observer (n = 12), replication (n = 4), animal (n = 16) and the first order interactions as factors. Changes of behavioural expressions during the test were assessed by dividing it into three intervals of 50 s and using the 2 one-sample test to check the dominance of each descriptor in each interval. The Wilcoxon test was used to compare quantitative and qualitative behavioural variables as assessed indoors and outdoors. The low level of variance explained for each descriptor by the interactions animal × replication and animal × assessor as compared with the animal (the F of the factor animal was roughly 10 times higher than that of the interactions), showed the intra- and inter-observer reliability of the panel. Indoors, the dominant descriptors of buffalo behaviour (calm, apathetic and curious) were all indicative of a low level of arousal and frequently switched from one another. Outdoors, most of the animals were described with terms indicating a high level of arousal (e.g. Active and Nervous) and only at the end of the test they were generally scored as Curious. Accordingly, the dominance of the descriptor Curious changed during the test when the animals were tested outdoors (2 = 7.00, P < 0.05), whereas no significant changes were observed for all the other descriptors both indoors and outdoors (P > 0.05). The results indicate that C-QBA, if combined with the appropriate tools (i.e. TDBE), may be able to follow and describe the variations of animal behavioural expressions in time. © 2015 Elsevier B.V. All rights reserved.
∗ Corresponding author at: Scuola di Scienze Agrarie, Forestali, Alimentari ed Ambientali, Università degli Studi della Basilicata, Via dell’Ateneo Lucano 10, 85100 Potenza, Italy. Tel.: +39 0971205078; fax: +39 0971205378. E-mail address: [email protected] (F. Napolitano). http://dx.doi.org/10.1016/j.applanim.2015.01.017 0168-1591/© 2015 Elsevier B.V. All rights reserved.
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1. Introduction The interpretation of animal behaviour both in familiar (e.g. home pen) and unfamiliar environments (e.g. response to open field testing) may be difficult due to the coexistence of several motivations and emotions affecting animal behaviour. Numerous studies support the hypothesis that the assessment of animal behaviour through Qualitative Behaviour Assessment (QBA) can add important pieces of expressive information to animal studies, identifying differences in emotional valence that can be difficult to capture quantitatively, thus helping in the interpretation of this latter kind of data (Wemelsfelder et al., 2001; Napolitano et al., 2008). In fact, this methodology allows the description of how animals interact with the environment, including humans (Ellingsen et al., 2014), rather than measuring what they do, based on the use of qualitative behavioural descriptors. In most studies a free choice profiling (FCP) approach has been used where observers used different descriptors (e.g. Wemelsfelder et al., 2001 in pigs, Stockmana et al., 2013 in cattle). Therefore, agreement was assessed by comparing the entire vocabularies of all observers, rather than on comparison of scores generated for specific terms. Conversely, fixed-term lists were mostly used for welfare monitoring purposes where a standardised way of evaluation was needed for feasibility reasons (Wemelsfelder et al., 2009a; Bassler et al., 2013; Sant’Anna and Paranhos da Costa, 2013). In this case the observers should discuss the meaning of each term in order to standardise their evaluations. In addition, observer agreement on individual terms should be tested and the terms failing to reach good levels of agreement should be eliminated. Both FCP and fixed lists have advantages and disadvantages when used for qualitative assessment purposes, and each should be used when they are best suited. One advantage of FCP is that it provides information on how observers use single terms; therefore, the study of word charts allow to assess the degree of semantic convergence among the observers. However, following this methodology observers perform a post hoc evaluation (i.e. they score the descriptors of animal behaviour after that the animals have been observed). Therefore, when QBA is conducted following the FCP method, an overall evaluation of the behaviour observed in a certain period of time is performed, regardless of the fluctuations possibly occurring during that observation. Temporal Dominance of Sensations (TDS) is a methodology recently developed in the field of sensory analysis that gives the opportunity to describe the evolution of the dominant perceptions occurring during testing (Pineau et al., 2009). This methodology relies on the use of a fixed list of terms; on the meaning of these terms a selected panel has to previously agree. TDS experiments have been conducted to describe the temporal sensory patterns of different foods and beverages such as dairy products (Pineau et al., 2009), olive oil (Dinnella et al., 2012), fish sticks (Albert et al., 2012), etc. In addition, data analysis methodologies have been proposed to compare products (Meyners & Pineau, 2010) and to assess panel agreement (Meyners, 2011). In this study TDS has
been adapted to the assessment of animal behavioural expression and therefore called Temporal Dominant Behavioural Expression (TDBE). Therefore, in this study the qualitative approach to the study of animal behaviour has been paired with the TDBE methodology in order to verify whether QBA is not only valid (e.g. Napolitano et al., 2008; Rutherford et al., 2012; Stockman et al., 2011, 2013) and reliable (e.g. Wemelsfelder et al., 2001, 2009b) but it is also capable to capture the style of interaction of the animals with the environment in a dynamic manner. The specific question we aimed to answer was about whether QBA was able to continuously describe the behaviour while it changes during the observation period, that is whether fluctuations could be perceived by the observers, hence detected by the method, which was therefore called Continuous QBA (C-QBA).
2. Material and methods 2.1. Experimental procedure Eight Mediterranean buffalo heifers aged 16–18 months were used (see Napolitano et al., 2012 for details on animals and farming conditions). Animals were subjected to two different isolation tests. One consisted in isolating individual animals from the rest of the group in the indoor part of the home pen, and one in leading animals individually through a single-file chute to an outdoor paddock (5.0 m × 4.6 m, with earth floor and open metal fencing), which was novel to the animals and located approx. 20 m away from the home pen. Four animals were tested first in the home indoor pen and subsequently in the novel outdoor paddock; the other four were tested in the opposite order. During tests subjects were isolated from tactile and visual contact with conspecifics, but could receive auditory and olfactory stimuli from other animals; they could not receive any stimuli from humans. All testing procedures were performed by a stockperson well known to the animals. Each animal was confined individually for 150 s in each testing condition, and her behaviour during this time was video-recorded using a DVL-157 JVC video camera equipped with a wide-angle lens, located at a corner of the test area at a distance from the fence of 6 m and operated by remote control. From this material 16 clips (8 animals in two conditions: indoors and outdoors) of 150 s duration each were created. Thus the total duration of the video recording presented to observers was 40 min. Although the animals were subjected to handling and isolation, these procedures were similar to those routinely used in a commercial farm (e.g. handling performed to move the animals to different farm facilities, isolation for veterinary interventions, etc.). In any case, all aspects of the study adhered to the European legal requirements concerning the protection of both animals kept for farming purposes and animals used for scientific purposes (Dir. 98/58/EC and Dir. 2010/63/UE, respectively).
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2.2. Continuous qualitative behaviour assessment A twelve-member panel (3 female and 9 male, aged 22–29 years) was used. Panellists were undergraduate and graduate animal science students recruited from the University of Basilicata. Panellist selection was based on willingness to participate, previous experience in animal behaviour observation, ability in generation of terms for qualitative behaviour assessment and discrimination of animal responses to different environmental challenges according to a predetermined list of terms. They were paid for their participation in the study. The socio-demographic features of the subjects participating to the qualitative behaviour assessment are reported in Table 1. Six behavioural descriptors were chosen according to the frequency of elicitation performed by three panels in a previous study (Napolitano et al., 2012). They were: “calm”, “active”, “curious”, “nervous”, “shy” and “apathetic”. 2.2.1. Panel training The definitions of behavioural descriptors are reported in Table 2. Such definitions were used for assessor training and were available both during the training and the experimental observations. Panel training consisted of seven preliminary sessions of 45 min each. Two of them were used to teach panellists how to use the TDBE computerised data acquisition system. The following five sessions were used to train the assessors to the continuous evaluation of the behavioural descriptors to be used during the C-QBA. During session three the assessors watched six clips (10–15 s each) representing the standard for each descriptor (learning phase). In particular, each clip showed an animal expressing one of the behavioural descriptor at high intensity. The objective of this session was the memorisation of the six behavioural descriptors through the observation of the clips, the corresponding descriptors and their definitions. During sessions four and five the assessors evaluated 18 clips (10–15 s each) showing the expression of each behavioural descriptor at medium and high intensity. Three-digit numbers identified clips. The assessors evaluated individual clips by indicating the dominant behavioural descriptor with the help of the descriptor list and definitions. During the last two sessions the assessors evaluated the same clips and were asked to indicate both the dominant behavioural descriptor and its perceived intensity. 2.2.2. Assessment through temporal dominant behavioural expression The clips were assessed according to the TDBE procedure (Pineau et al., 2009). The TDBE method consisted in presenting to the panellists the entire list of behavioural descriptors on a computer screen along with each clip. Each assessor was then asked to select the dominant descriptor and to score its intensity level on an unstructured scale of 100 mm length (0 mm: descriptor absent; 100 mm: descriptor could not be stronger). A behavioural descriptor was considered as dominant when it gained most of the attention of the observer (i.e. the most striking impression at a given time). Thereafter, each time the observer felt the behaviour changed, either in intensity or in quality, he/she
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scored the new dominant descriptor (or the new descriptor level), until the clip ended. During the observation of each clip the panellists were free to choose a descriptor several times, whereas other descriptors could be completely ignored. Each clip was identified by a three-digit code and observed 4 times by each observer (4 replications) in a randomised order. The order of the descriptors was also randomised across assessors although it did not change within assessors. Each assessor observed eight clips in each session. Five min intervals were given between two series of four clips. A total of sixteen clips (eight animals in two conditions) by four replications were observed in 8 sessions of about 25 min each. These four replications were performed in order to stay well above the suggested value of 30 evaluations for each item (12 observers × 4 replications = 48 evaluations) as suggested by Pineau et al. (2012). 2.3. Continuous quantitative behaviour assessment The behaviour shown by buffalo heifers in the 16 video clips was analysed quantitatively by means of continuous recording technique using the software The Observer XT version 8.0 (Noldus Information Technology). One trained observer performed all the observations. Training consisted in the observation of 3 outdoor and 3 indoor clips with the aim to instruct the observer in recognising the behavioural categories identified in a previous study (Napolitano et al., 2012). The behaviours recorded are described briefly in Table 3. These behaviours are indicated in the text as quantitative variables. 2.4. Statistical analysis TDBE data were acquired and processed through the software FIZZ (Biosystemes, Couternon, France), version 2.31G. For each clip, each observer, each replication and each descriptor the total dominance duration in s was computed. For each point of time (recorded at 2 s intervals), the proportion of runs (observer × replication) for which a given descriptor was selected (i.e. assessed as dominant), was computed and called dominance rate (%). These calculations allowed the construction of the TDBE curves for each animal. The chance level and significance level were reported along with TDBE curves. The chance level (P0 ) is the dominance rate that a descriptor can obtain by chance (P0 = 1/p, where p is the number of descriptors). Descriptors with dominant rates below the chance level are negligible. The significance level is the minimum value that a descriptor should reach to be deemed significantly higher than the chance level. Therefore, TDBE curves above the significance level can be considered consistent across the observers. The signifiaccording to the following cance level (Ps ) was calculated formula: Ps = P0 + 1.645 P0 (1 − P0 )/n, where n = number of observers × replications (Pineau et al., 2009). The software also allowed collecting the intensity level for each point of time. As suggested by Labbe et al. (2009), on the basis of the duration of dominance and intensity levels the following scores were calculated: Score = ( Scoring Inten sity level × Duration)/( Scoring Duration). Dominance
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Table 1 Socio-demographic features of the subjects participating to the continuous qualitative behaviour assessment. Participant
Sex
Age
Educational level
N. family components
1 2 3 4 5 6 7 8 9 10 11 12
F M M M F M M M M M F M
27 24 23 24 34 28 22 22 29 24 29 24
PhD student Graduated High school Graduated Graduated Graduated High school High school Graduated High school PhD student High school
4 3 4 4 4 4 4 4 3 2 2 4
Table 2 Descriptors and definitions used for assessor training to continuous qualitative behaviour assessment. Descriptor
Definition
Calm Active Curious
The animal moves slowly with head raised but without overt signs of vigilance and/or agitation The animal shows high levels of general activity and vigilance with sustained locomotion The animal is explorative, sniffing partitions or other environmental stimuli such as the ground with lowered head. Locomotion is present but not sustained The animal is frightened, showing sudden, exaggerated reactions to environmental stimuli The animal moves slowly showing circumspection, uncertainty and insecurity. Avoidance reactions are displayed even to neutral stimuli The animal is indifferent to the environment showing low levels of activity and locomotion
Nervous Shy Apathetic
durations and scores of the descriptors are indicated in the text as qualitative variables. For each descriptor and each animal the values of dominance durations and scores were subjected to analysis of variance using observer (12), replication (4), animal (16) and the first order interactions as factors. In order to verify possible changes of behavioural expressions during the test (duration = 150 s), test duration was divided into three intervals of 50 s. For each descriptor the frequency of occurrences of dominance in each testing condition was analysed using a 2 (dominance presence vs. absence) × 3 (test intervals) 2 test. A principal component analysis (PCA) was used to investigate the relationship between quantitative and qualitative data, and to indicate which variables were most closely associated in explaining the variation between clips. The PCA was based on the dominance durations and scores obtained from TDBE and on quantitative behaviour data recorded during the two isolation tests through the Observer XT. A correlation matrix was used and no
rotation was applied. The analysis was performed using the software Unscrambler X v.10.1. The Wilcoxon test was used to compare both quantitative variables (recorded through The Observer XT) and qualitative variables recorded through TDBE (mean values of dominance durations and scores) as assessed indoors and outdoors.
3. Results 3.1. Observer reliability The analysis of variance of the qualitative variables (mean duration and score) showed no significant interaction animal × replication, thus indicating that the behaviour of the animals was not assessed differently in different replications. Although the interaction animal × assessor was always significant (P < 0.001), the F of the factor animal was roughly 10 times higher than that of
Table 3 Description of behavioural categories continuously recorded through The Observer XT version 8.0 (Noldus Information Technology) during the indoor and outdoor isolation tests. Variable
Definition
Inactive (duration) Walking (duration) Running (duration) Flight attempts (frequency)
Standing or lying, no overt activity. Walking slowly, looking in front or around. Rapid forward movement including gallop and trotting. Fast run towards the fence abruptly interrupted either before or after crashing into it. Final posture with head protruding beyond the fence. Standing still with elevated neck and intently oriented head. Walking slowly with the neck horizontal often interrupted by stopping and sniffing the ground or the fence. Emission of acoustic signals. Circular movements of the tail. Emission of urine and faeces.
Vigilance (duration) Exploration (duration) Vocalisation (frequency) Tail movement (duration) Urination/defecation (duration)
F. Napolitano et al. / Applied Animal Behaviour Science 166 (2015) 35–43 Table 4 F values of the descriptors used in the continuous qualitative assessment. Variables Duration Calm Active Curious Nervous Shy Apathetic Score Calm Active Curious Nervous Shy Apathetic
Animal
Animal × assessor
Animal × replication
47.46 87.70 107.11 323.72 29.43 167.03
4.91 6.93 3.23 7.87 3.67 5.16
0.95 0.94 1.03 1.03 0.86 0.82
17.24 51.04 23.89 191.09 32.66 76.66
2.12 3.75 2.47 4.41 2.84 2.88
1.16 1.10 0.90 1.21 1.01 0.83
the interaction (Table 4), which was therefore considered negligible, thus suggesting satisfactory panel reliability. Another measure of observer reliability is given by the calculation of the dominant descriptors as performed through TDBE. In particular, Figs. 1 and 2 show most of the time descriptors above the level of significance that can be interpreted as consistent across the observers (Pineau et al., 2009). 3.2. Continuous qualitative behaviour assessment Figs. 1 and 2 display the TDBE curves of the same buffalo heifer (animal number 1) in the two testing conditions (indoors and outdoors, respectively). The chance level, which is the dominance rate that a descriptor can be obtained by chance, was 0.167, corresponding to a dominance rate of 17%. Accordingly, attributes presenting dominance rates below 17% were not considered dominant. The significance level was calculated taking into account the chance level and the 48 evaluations performed by the panel (12 observers × 4 replications) and was 0.259, corresponding to a dominance rate of 26% (see Pineau et al., 2009 for more details). Fig. 1 shows that indoors this animal interchanged between three dominant behavioural descriptors (calm, apathetic and curious). None of them was dominant for more than 23 s. The first dominant descriptor was Calm from 3 to 15 s, from 51 to 82 s, with the highest dominance rate at s 77 (42.5%), and then maintained a steady dominance rate from 102 to 123 s. The second dominant descriptor was Apathetic. This descriptor showed two distinct peaks from 15 to 38 s and then from 124 to 139 s, with the highest dominance rate at 32 s (65%). Curious was the third dominant descriptor, which peaked from 39 to 50 s, from 83 to 101 s (the highest dominance rate was observed at 91 s with a value of 72.5%) and then prevailed from 140 s to the end of the test (150 s). The same animal showed a completely different pattern in outdoor conditions (Fig. 2). Only two descriptors were dominant throughout the test. Nervous was scored as dominant from the beginning of the test (3 s) to 136 s (more than 2 min corresponding to 89% of the time). The highest dominance rate was reached at 12.5 s (88%). Subsequently, curious dominated from 137 s to the end of the test (150 s)
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with a maximum of dominance rate of 69% at 138 s. For sake of brevity the remaining 14 curves of the other 7 buffaloes are not shown. In agreement with the previously described results, the 2 test showed that the dominance of the descriptor Curious changed during the test when the animals were tested outdoors (2 = 7.00, P < 0.05), whereas no significant changes were observed for all the other descriptors both indoors and outdoors (P > 0.05). In particular, the dominance of Curious moved from 25.0 and 16.7% in the first and second interval of observation, respectively, to 58.3% in the third interval. Table 5 shows duration and score of the qualitative variables and the results of the analysis conducted using the Wilcoxon test. As to score, Curious, Shy and Calm showed no significant differences, Active and Nervous were higher outdoors and apathetic was higher indoors (P < 0.05). Similar results were obtained for duration, although only Curious showed no significant differences. Calm, Shy and Apathetic were higher indoors, whereas Active and Nervous were higher outdoors (P < 0.05). 3.3. Continuous quantitative behaviour assessment Table 5 also reports quantitative variables as assessed indoors and outdoors. The Wilcoxon test showed that buffalo heifers were more inactive (P < 0.05) and tended to urinate/defecate more indoors than outdoors (P < 0.10). Conversely, outdoor animals were vigilant and run for longer (P < 0.05) and tended to perform a higher number of flight attempts (P < 0.10). No other differences between indoor and outdoor tests were observed for any other quantitative variables. 3.4. The relationship between quantitative and qualitative variables The PCA of qualitative (score and duration from TDBE) and quantitative (from the software The Observer XT) data yielded two main components explaining 43% and 17% of the variation among experimental subjects, respectively. Fig. 3 displays the loadings of the different variables on these two components. The highest positive loadings on the first PCA component were shown by duration of Nervous (0.26), intensities of Nervous (0.28) and Active (0.28) and the quantitative variable Tail movements (0.25), whereas durations of Shy (−0.26) and Apathetic (−0.26), intensities of Shy (−0.26), Apathetic (−0.30) and Calm (−0.26) and the quantitative variable Inactive (−0.29) displayed the highest negative loadings. Duration and score of Curious (0.48 and 0.40, respectively) and the quantitative variable Exploration (0.41) showed the highest positive loadings on the second PCA component, whereas the quantitative variable Walking (−0.36) was the only one receiving a high negative loading on the second component. 4. Discussion Both the results obtained from the analysis of variance and those produced by TDBE consistently showed the reliability of the panel used for the dynamic qualitative behaviour assessment. These results on one hand
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F. Napolitano et al. / Applied Animal Behaviour Science 166 (2015) 35–43
Fig. 1. TDBE (Temporal Dominant Behavioural Expression) curves describing the behavioural expressions of animal 1 during the indoor test. The curves describe the agreement between observers on the dominant descriptors as the trial proceeded. When reliability is above the level of significance a descriptor can be considered consistent across the observers.
confirmed that the training (based on a combination of term descriptions and video references) was effective in gaining alignment in the panel, on the other were fundamental to perform subsequent analyses and allow sound interpretations of data. Indoors the behaviour of buffaloes was not characterised by a particular trend and the dominant descriptors (Calm, Apathetic and Curious), which were all indicative of a low level of arousal, frequently switched from one another (Fig. 1). More importantly, the animals started to be scored as Curious soon after the test started. This descriptor is mainly linked to the explorative activity of the animals (see Table 2 for the definition of the qualitative descriptor Curious and Fig. 3 showing the correlation of this descriptor with the quantitative variable Exploration), which was possibly induced by the novel social
condition (isolation) produced by the experimental procedure. In fact, when the environment is very familiar to the animals, exploratory behaviour is usually not performed. However, this behaviour reappears when any changes occur in the home environment. An early engagement in exploration may be due to the fact that the animals were in their home pen, thus confident enough to start the exploration of the environment soon. According to Hogan (2005), fear and exploration are not independent and the latter is performed only at low levels of fear. The same animals showed a different behavioural pattern when tested outdoors. Through C-QBA most of the animals were described with terms indicating a high level of arousal (e.g. Active, Nervous) and only at the end of the test they were generally scored as Curious (Fig. 2). An outdoor setting unknown to the animals may have, at least initially, induced a fear
Fig. 2. TDBE (Temporal Dominant Behavioural Expression) curves describing the behavioural expressions of animal 1 during the outdoor test. The curves describe the agreement between observers on the dominant descriptors as the trial proceeded. When reliability is above the level of significance a descriptor can be considered consistent across the observers.
F. Napolitano et al. / Applied Animal Behaviour Science 166 (2015) 35–43
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Table 5 Mean ± sd (min–max) of quantitative variables continuously recorded through The Observer XT version 8.0 (Noldus Information Technology) and qualitative variables continuously recorded through Temporal Dominant Behavioural Expression (duration and score). Variables Quantitative Inactive (s) Walking (s) Running (s) Flight attempts, n Vigilance (s) Exploration (s) Vocalisation, n Tail movement (s) Urination/defecation (s) Duration Calm Active Curious Nervous Shy Apathetic Score Calm Active Curious Nervous Shy Apathetic a
Indoor
Outdoor
Za
P
54.4 30.8 0.0 0.0 5.1 52.1 5.5 84.4 10.4
± ± ± ± ± ± ± ± ±
36.8 (9.0–123.0) 24.1 (0.0–65.0) 0.0 (0.0–0.0) 0.0 (0.0–0.0) 13.0 (0.0–37.0) 19.3 (17.0–70.0) 7.4 (0.0–21.0) 35.4 (20.0–133.0) 13.5 (0.0–38.0)
15.5 25.1 11.3 1.5 16.1 74.5 4.5 99.9 0.0
± ± ± ± ± ± ± ± ±
22.3 (0.0–54.0) 16.4 (0.0–45.0) 16.9 (0.0–48.0) 1.9 (0.0–5.0) 18.1 (0.0–54.0) 35.3 (43.0–131.0) 5.7 (0.0–13.0) 44.1 (17.0–139.0) 0.0 (0.0–0.0)
−2.52 −0.28 −2.02 −1.82 −2.37 −1.12 −0.27 −1.12 −1.83
0.012 0.779 0.043 0.068 0.018 0.263 0.787 0.263 0.068
46.0 14.7 41.7 1.5 11.4 27.4
± ± ± ± ± ±
12.9 (24.7–62.7) 20.2 (0.6–60.8) 18.1 (11.5–65.5) 2.1 (0.0–5.8) 9.8 (0.5–25.1) 28.0 (3.7–83.7)
19.4 26.6 48.7 34.6 6.6 8.5
± ± ± ± ± ±
15.3 (2.7–43.3) 23.0 (7.3–70.6) 30.9 (23.4–100.8) 36.1 (0.9–90.4) 7.7 (0.0–19.6) 11.0 (0.0–26.2)
−2.10 −2.24 −0.42 −2.52 −2.24 −2.52
0.036 0.025 0.674 0.012 0.025 0.012
44.9 17.3 48.2 2.9 22.4 33.7
± ± ± ± ± ±
9.1 (27.6–53.0) 16.7 (1.6–49.2) 11.6 (24.2–59.4) 3.0 (0.0–7.7) 13.7 (1.5–40.4) 22.3 (5.7–68.7)
32.6 41.7 53.6 36.1 18.7 17.1
± ± ± ± ± ±
18.4 (8.2–58.5) 12.2 (27.6–56.6) 10.7 (36.4–68.9) 26.3 (2.2–72.5) 17.2 (0.0–44.6) 20.1 (0.0–52.5)
−1.26 −2.52 −0.70 −2.52 −0.98 −2.52
0.208 0.012 0.483 0.012 0.327 0.012
Statistics used in the Wilcoxon test.
Fig. 3. Principal component analysis performed on quantitative variables continuously recorded through The Observer XT version 8.0 (Noldus Information Technology) and qualitative variables continuously recorded through Temporal Dominant Behavioural Expression (D = duration, S = score).
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F. Napolitano et al. / Applied Animal Behaviour Science 166 (2015) 35–43
(flight) response (see Fig. 3 showing the correlation of the qualitative descriptors Nervous and Active with the quantitative variables Flight attempts and Running) and only at the end of the test, after a certain degree of habituation, the animals possibly started to be more curious. The results concerning the qualitative descriptors perfectly matched those obtained in the quantitative assessment: no differences were observed between the mean values of dominance duration and score for Curious as assessed indoors and outdoors through C-QBA; no differences were observed for the expression of quantitative variables such as Exploration and Walking. Conversely, other quantitative variables, such as Running, Vigilance and Flight attempts, all indicative of high levels of arousal, alert and fear, discriminated the behaviour expressed indoors from that expressed outdoors; the same did the qualitative descriptors Nervous and Active. Accordingly, the quantitative variable Inactive and the qualitative descriptor Apathetic, overtly indicating a low level of arousal, were higher in indoor conditions. A good degree of agreement between quantitative and qualitative variables is also shown by principal component analysis. This multivariate analysis displayed a meaningful convergence of quantitative and qualitative variables. However, C-QBA was able to give information additional to those obtained through quantitative variables or standard QBA by detecting the changing features of the behaviour in time. For instance, in a study conducted by Morgan et al. (2014), socialised piglets were scored as less curious than control non-socialised animals when mixed with unknown conspecifics. However, no information could be collected about the variation of this and other behavioural expression as the time progressed. Similarly, Stockmana et al. (2013) observed a significant effect of driving style on cattle behavioural expression, but they were unable to monitor any changes during transport. Conversely, in our study C-QBA showed that the descriptor Curious, albeit not significantly different between indoor and outdoor conditions in quantitative terms, was visible only at the end of the outdoor test, whereas indoors it was detectable independently from time. Several studies on animal behaviour are based on continuous recording (see Martin and Bateson, 2007 for a detailed description of the method). When a quantitative variable is continuously recorded a precise pattern of the behaviour is gathered in terms of frequencies and durations; other pieces of information, such as when a particular behavioural expression starts and when it stops, can also be obtained. However, subtle and continuous changes in the emotional state of the animals cannot be detected unless a more sensitive tool is adopted. C-QBA seems to possess the requisites to identify and follow the fluctuations of such animal behavioural expressions. 5. Conclusion The results obtained in this study indicate that C-QBA, if combined with the appropriate tools, may be able to follow the variation of animal behaviour in time, as no other method does. In a previous work QBA associated with FCP was able to detect higher levels of activity and nervousness
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