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Item Review: Space allowance for growing pigs: animal welfare, performance and on-farm practicality(Elsevier B V on behalf of The Animal Consortium, 2024-06) Chidgey KLThere is considerable variation in the recommended minimum space allowance for growing pigs in scientific literature, and growing pressure, arising from recent reviews of current animal welfare standards for pigs, to increase the minimum space allowances set in legislation in some countries (e.g., European Union countries and New Zealand). The space provided for growing pigs needs to accommodate their physical body size in addition to social behaviour, activity, and essential functional behaviours. However, recommended minimum space allowances vary according to criteria such as temperature, live weight, flooring type, group size, behaviour, and enrichment availability. Though there may be justification for increasing current space requirements, this will present a practical issue on existing farms and could even result in unintended negative welfare outcomes, depending on how farmers address an increased requirement for space. This is not helped by inconsistent scientific approaches to assessing the effect of space on pig performance, and a lack of information on how space allowance impacts a pig's affective state. This review explores the scientific basis of the most common approaches to determining minimum space allowances for growing pigs and discusses the various factors that influence and interact with their spatial requirements. Consideration is given to their nutrition, physical environment, health, and behaviour to understand the welfare, performance, and practicality implications of differing recommendations for space allowance. More research is needed that investigates a range of space allowances to better understand the relationship between animal welfare and performance outcomes, and space allowance. This must replicate commercial conditions so that recommendations are relevant, future-focused, and achieve positive welfare outcomes in a practical but meaningful manner.Item Peripherally Restricted Activation of Opioid Receptors Influences Anxiety-Related Behaviour and Alters Brain Gene Expression in a Sex-Specific Manner.(MDPI (Basel, Switzerland), 2024-12-07) Parkar N; Young W; Olson T; Hurst C; Janssen P; Spencer NJ; McNabb WC; Dalziel JE; Szumlinski KK; Shiina TAlthough effects of stress-induced anxiety on the gastrointestinal tract and enteric nervous system (ENS) are well studied, how ENS dysfunction impacts behaviour is not well understood. We investigated whether ENS modulation alters anxiety-related behaviour in rats. We used loperamide, a potent μ-opioid receptor agonist that does not cross the blood-brain barrier, to manipulate ENS function and assess changes in behaviour, gut and brain gene expression, and microbiota profile. Sprague Dawley (male/female) rats were acutely dosed with loperamide (subcutaneous) or control solution, and their behavioural phenotype was examined using open field and elevated plus maze tests. Gene expression in the proximal colon, prefrontal cortex, hippocampus, and amygdala was assessed by RNA-seq and caecal microbiota composition determined by shotgun metagenome sequencing. In female rats, loperamide treatment decreased distance moved and frequency of supported rearing, indicating decreased exploratory behaviour and increased anxiety, which was associated with altered hippocampal gene expression. Loperamide altered proximal colon gene expression and microbiome composition in both male and female rats. Our results demonstrate the importance of the ENS for communication between gut and brain for normo-anxious states in female rats and implicate corticotropin-releasing hormone and gamma-aminobutyric acid gene signalling pathways in the hippocampus. This study also sheds light on sexually dimorphic communication between the gut and the brain. Microbiome and colonic gene expression changes likely reflect localised effects of loperamide related to gut dysmotility. These results suggest possible ENS pharmacological targets to alter gut to brain signalling for modulating mood.Item The Use of Triaxial Accelerometers and Machine Learning Algorithms for Behavioural Identification in Domestic Dogs (Canis familiaris): A Validation Study(MDPI (Basel, Switzerland), 2024-09-13) Redmond C; Smit M; Draganova I; Corner-Thomas R; Thomas D; Andrews C; Fullwood DT; Bowden AEAssessing the behaviour and physical attributes of domesticated dogs is critical for predicting the suitability of animals for companionship or specific roles such as hunting, military or service. Common methods of behavioural assessment can be time consuming, labour-intensive, and subject to bias, making large-scale and rapid implementation challenging. Objective, practical and time effective behaviour measures may be facilitated by remote and automated devices such as accelerometers. This study, therefore, aimed to validate the ActiGraph® accelerometer as a tool for behavioural classification. This study used a machine learning method that identified nine dog behaviours with an overall accuracy of 74% (range for each behaviour was 54 to 93%). In addition, overall body dynamic acceleration was found to be correlated with the amount of time spent exhibiting active behaviours (barking, locomotion, scratching, sniffing, and standing; R2 = 0.91, p < 0.001). Machine learning was an effective method to build a model to classify behaviours such as barking, defecating, drinking, eating, locomotion, resting-asleep, resting-alert, sniffing, and standing with high overall accuracy whilst maintaining a large behavioural repertoire.Item The Use of Triaxial Accelerometers and Machine Learning Algorithms for Behavioural Identification in Domestic Cats (Felis catus): A Validation Study(MDPI (Basel, Switzerland), 2023-08-14) Smit M; Ikurior SJ; Corner-Thomas RA; Andrews CJ; Draganova I; Thomas DG; Vanwanseele BAnimal behaviour can be an indicator of health and welfare. Monitoring behaviour through visual observation is labour-intensive and there is a risk of missing infrequent behaviours. Twelve healthy domestic shorthair cats were fitted with triaxial accelerometers mounted on a collar and harness. Over seven days, accelerometer and video footage were collected simultaneously. Identifier variables (n = 32) were calculated from the accelerometer data and summarized into 1 s epochs. Twenty-four behaviours were annotated from the video recordings and aligned with the summarised accelerometer data. Models were created using random forest (RF) and supervised self-organizing map (SOM) machine learning techniques for each mounting location. Multiple modelling rounds were run to select and merge behaviours based on performance values. All models were then tested on a validation accelerometer dataset from the same twelve cats to identify behaviours. The frequency of behaviours was calculated and compared using Dirichlet regression. Despite the SOM models having higher Kappa (>95%) and overall accuracy (>95%) compared with the RF models (64-76% and 70-86%, respectively), the RF models predicted behaviours more consistently between mounting locations. These results indicate that triaxial accelerometers can identify cat specific behaviours.Item How Lazy Are Pet Cats Really? Using Machine Learning and Accelerometry to Get a Glimpse into the Behaviour of Privately Owned Cats in Different Households(MDPI (Basel, Switzerland), 2024-04-19) Smit M; Corner-Thomas R; Draganova I; Andrews C; Thomas D; Friedrich CMSurprisingly little is known about how the home environment influences the behaviour of pet cats. This study aimed to determine how factors in the home environment (e.g., with or without outdoor access, urban vs. rural, presence of a child) and the season influences the daily behaviour of cats. Using accelerometer data and a validated machine learning model, behaviours including being active, eating, grooming, littering, lying, scratching, sitting, and standing were quantified for 28 pet cats. Generalized estimating equation models were used to determine the effects of different environmental conditions. Increasing cat age was negatively correlated with time spent active (p < 0.05). Cats with outdoor access (n = 18) were less active in winter than in summer (p < 0.05), but no differences were observed between seasons for indoor-only (n = 10) cats. Cats living in rural areas (n = 7) spent more time eating than cats in urban areas (n = 21; p < 0.05). Cats living in single-cat households (n = 12) spent more time lying but less time sitting than cats living in multi-cat households (n = 16; p < 0.05). Cats in households with at least one child (n = 20) spent more time standing in winter (p < 0.05), and more time lying but less time sitting in summer compared to cats in households with no children (n = 8; p < 0.05). This study clearly shows that the home environment has a major impact on cat behaviour.Item Review: The Five Domains model and promoting positive welfare in pigs(Elsevier B.V. on behalf of The Animal Consortium, 2022-06-16) Kells NJPublic concern for the welfare of farm animals has increased over recent years. Meeting public demands for higher animal welfare products requires robust animal welfare assessment tools that enable the user to identify areas of potential welfare compromise and enhancement. The Five Domains model is a structured, systematic, and comprehensive framework for assessing welfare risks and enhancement in sentient animals. Since its inception in 1994, the model has undergone regular updates to incorporate advances in animal welfare understanding and scientific knowledge. The model consists of five areas, or domains, that focus attention on specific factors or conditions that may impact on an animal's welfare. These include four physical/functional domains: nutrition, physical environment, health, and behavioural interactions, and a fifth mental or affective state domain. The first three domains draw attention to welfare-significant internal physical/functional states within the animal, whereas the fourth deals with welfare-relevant features of the animal's external physical and social environment. Initially named "Behaviour" Domain 4 was renamed "Behavioural Interactions" in the 2020 iteration of the model and was expanded to include three categories: interactions with the environment, interactions with other animals and interactions with humans. These explicitly focus attention on environmental and social circumstances that may influence the animal's ability to exercise agency, an important determinant of welfare. Once factors in Domains 1-4 have been considered, the likely consequences, in terms of the animal's subjective experiences, are assigned to Domain 5 (affective state). The integrated outcome of all negative and positive mental experiences accumulated in Domain 5 represents the animal's current welfare state. Because the model specifically draws attention to conditions that may positively influence welfare, it provides a useful framework for identifying opportunities to promote positive welfare in intensively farmed animals. When negative affective experiences are minimised, providing animals with the opportunity to engage in species-specific rewarding behaviours may shift them into an overall positive welfare state. In domestic pigs, providing opportunities for foraging, play, and nest building, along with improving the quality of pig-human interactions, has the potential to promote positive welfare.Item Validation of a combined approach-avoidance and conditioned stimulus aversion paradigm for evaluating aversion in chickens.(PLOS, 2021-02-25) Du Plessis EW; Beausoleil NJ; Bolwell CF; Stafford KJ; Olsson IASUnderstanding animals' aversion is important to improving their welfare. Aversion is often assessed using an approach-avoidance (AA) test in which animals have to forfeit a reward if they want to avoid an event or environment presented in the same place. However, sometimes the event/environment suspected to be aversive may physically impair the animal's ability to withdraw from that place (i.e. its ability to express aversion), leading to incorrect interpretations. Combining AA with a Conditioned-Stimulus that predicts the event/environment may overcome this problem by allowing animals to demonstrate aversion without exposure to the stimulus. We aimed to validate this paradigm for testing aversion in chickens. Seven Hyline-Brown chickens were trained to obtain a food reward from a coloured bowl located in the test chamber (TC) of a two-chambered box; the reward was presented in a green bowl with an inactivated air canister or a red bowl with the canister activated to deliver an air puff. Two 5-minute tests were conducted, one with each bowl colour and both with the canister inactivated. All chickens entered TC with the green bowl. With the red bowl, two chickens entered on their first attempt, one fully entered after a partial entry (3/7 fully entered), two made only partial entries and two made no attempts to enter. Chickens spent less time in the TC with the red bowl (median 31s, IQR 7-252) compared to the green bowl (293s, IQR 290-294; p = 0.008). The higher ratio of partial to full entries, failure to enter the TC and less time spent in TC reflected chickens' aversion to the air puff, signalled by the red bowl. The paradigm allowed chickens to demonstrate aversion without exposure to the aversive stimulus during testing.Item A randomised controlled trial to evaluate the impact of indoor living space on dairy cow production, reproduction and behaviour(Springer Nature Limited, 2022-03-09) Thompson JS; Hudson CD; Huxley JN; Kaler J; Robinson RS; Woad KJ; Bollard N; Gibbons J; Green MJAs a global society, we have a duty to provide suitable care and conditions for farmed livestock to protect animal welfare and ensure the sustainability of our food supply. The suitability and biological impacts of housing conditions for intensively farmed animals is a complex and emotive subject, yet poorly researched, meaning quantitative evidence to inform policy and legislation is lacking. Most dairy cows globally are housed for some duration during the year, largely when climatic conditions are unfavourable. However, the impact on biology, productivity and welfare of even the most basic housing requirement, the quantity of living space, remains unknown. We conducted a long-term (1-year), randomised controlled trial (CONSORT 10 guidelines) to investigate the impact of increased living space (6.5 m2 vs 3 m2 per animal) on critical aspects of cow biology, behaviour and productivity. Adult Holstein dairy cows (n = 150) were continuously and randomly allocated to a high or control living space group with all other aspects of housing remaining identical between groups. Compared to cows in the control living space group, cows with increased space produced more milk per 305d lactation (primiparous: 12,235 L vs 11,592 L, P < 0.01; multiparous: 14,746 L vs 14,644 L, P < 0.01) but took longer to become pregnant after calving (primiparous: 155 d vs 83 d, P = 0.025; multiparous: 133 d vs 109 d). In terms of behaviour, cows with more living space spent significantly more time in lying areas (65 min/d difference; high space group: 12.43 h/day, 95% CI = 11.70-13.29; control space group: 11.42 h/day, 95% CI = 10.73-12.12) and significantly less time in passageways (64 min/d), suggesting enhanced welfare when more space was provided. A key physiological difference between groups was that cows with more space spent longer ruminating each day. This is the first long term study in dairy cows to demonstrate that increased living space results in meaningful benefits in terms of productivity and behaviour and suggests that the interplay between farmed animals and their housed environment plays an important role in the concepts of welfare and sustainability of dairy farming.