The shelter environment may have a severe impact on the dogs’ quality of life, and there is thus a need to develop valid tools to assess their welfare. These tools should be sensitive not only to the animals’ physical health but also to their mental health, including the assessment of positive and negative emotions. Qualitative Behaviour Assessment (QBA) is a ‘whole animal’ measure that captures the expressive quality of an animal’s demeanour, using descriptive terms such as ‘relaxed’, ‘anxious’, and ‘playful’. In this study, for the first time, we developed and tested a fixed-list of qualitative QBA terms for application to kennelled dogs. A list of 20 QBA terms was developed based on literature search and an expert opinion survey. Inter-observer reliability was investigated by asking 11 observers to use these terms to score 13 video clips of kennelled dogs. Principal Component Analysis (PCA) was used to extract four main dimensions explaining 70.9% of the total variation between clips. PC1 characterised curious/playful/excitable/sociable demeanour, PC2 ranged from comfortable/relaxed to anxious/nervous/stressed expression, PC3 described fearful demeanour, and PC4 characterised bored/depressed demeanour. Observers’ agreement on the ranking of video clips on these four expressive dimensions was good (Kendall’s W: 0.60–0.80). ANOVA showed a significant effect of observer on mean clip score on all PCs (p<0.05), due to few observers scoring differently from the rest of the group. Results indicate the potential of the proposed list of QBA terms for sheltered dogs to serve, in alignment with other measures, as a non-invasive assessment tool. However, the observer effect on mean PC scores points towards the need for adequate observer training, particularly in live scoring conditions. The QBA scoring tool can be integrated with existing welfare assessment protocols for shelter dogs and strengthen the power of those protocols to evaluate the animals’ experience in shelters.

Metabolic diseases and obesity are developing worldwide in a context of plethoric intake of high energy diets. The intestine may play a pivotal role due to diet-induced alterations in microbiota composition and increased permeability to bacterial lipopolysaccharide inducing metabolic inflammation. Early programming of metabolic disorders appearing in later life is also suspected, but data on the intestine are lacking. Therefore, we hypothesized that early disturbances in microbial colonization have short- and long-lasting consequences on selected intestinal components including key digestive enzymes and protective inducible heat shock proteins (HSP). The hypothesis was tested in swine offspring born to control mothers (n = 12) or mothers treated with the antibiotic amoxicillin around parturition (n = 11), and slaughtered serially at 14, 28 and 42 days of age to assess short-term effects. To evaluate long-term consequences, young adult offspring from the same litters were offered a normal or a fat-enriched diet for 4 weeks between 140 and 169 days of age and were then slaughtered. Amoxicillin treatment transiently modified both mother and offspring microbiota. This was associated with early but transient reduction in ileal alkaline phosphatase, HSP70 (but not HSP27) and crypt depth, suggesting a milder or delayed intestinal response to bacteria in offspring born to antibiotic-treated mothers. More importantly, we disclosed long-term consequences of this treatment on jejunal alkaline phosphatase (reduced) and jejunal and ileal dipeptidylpeptidase IV (increased and decreased, respectively) of offspring born to antibiotic-treated dams. Significant interactions between early antibiotic treatment and later diet were observed for jejunal alkaline phosphatase and sucrase. By contrast, inducible HSPs were not affected. In conclusion, our data suggest that early changes in bacterial colonization not only modulate intestinal architecture and function transiently, but also exert site- and sometimes diet-specific long-term effects on key components of intestinal homeostasis.

Mankind directly controls the environment and lifestyles of several domestic species for purposes ranging from production and research to conservation and companionship. These environments and lifestyles may not offer these animals the best quality of life. Behaviour is a direct reflection of how the animal is coping with its environment. Behavioural indicators are thus among the preferred parameters to assess welfare. However, behavioural recording (usually from video) can be very time consuming and the accuracy and reliability of the output rely on the experience and background of the observers. The outburst of new video technology and computer image processing gives the basis for promising solutions. In this pilot study, we present a new prototype software able to automatically infer the behaviour of dogs housed in kennels from 3D visual data and through structured machine learning frameworks. Depth information acquired through 3D features, body part detection and training are the key elements that allow the machine to recognise postures, trajectories inside the kennel and patterns of movement that can be later labelled at convenience. The main innovation of the software is its ability to automatically cluster frequently observed temporal patterns of movement without any pre-set ethogram. Conversely, when common patterns are defined through training, a deviation from normal behaviour in time or between individuals could be assessed. The software accuracy in correctly detecting the dogs’ behaviour was checked through a validation process. An automatic behaviour recognition system, independent from human subjectivity, could add scientific knowledge on animals’ quality of life in confinement as well as saving time and resources. This 3D framework was designed to be invariant to the dog’s shape and size and could be extended to farm, laboratory and zoo quadrupeds in artificial housing. The computer vision technique applied to this software is innovative in non-human animal behaviour science. Further improvements and validation are needed, and future applications and limitations are discussed.

The aim of this study was to determine the effects of 3 antibiotics used for pulmonary pathologies added in the feed of weaned pigs on growth performance, commensal microbiota, and immune response. At weaning, a total of 72 pigs were randomly assigned by BW and litter to 1 of the following diets: control (typical weaning diet), control + 400 mg of tilmicosin/kg, control + 600 mg of amoxicillin/kg, and control + 300 mg of doxycycline/kg. Individually penned pigs were slaughtered after 3 wk (12 pigs/treatment) or 4 wk (6 pigs/treatment). During the fourth week, all pigs received the control diet to test the residual effect of the antimicrobial supplementation. The antibiotic supplementation increased growth and feed intake during the first week (P < 0.01) and over the first 3 wk combined (P < 0.05). Gain-to-feed ratio tended to improve during the first week (P = 0.076) by the antibiotics compared with the control. Among the antibiotic treatments, no difference was observed in ADG and feed intake, which were also unchanged by the diet in the fourth week. The fecal enterobacteria counts were increased by amoxicillin on d 14 and 21 (P < 0.05 and 0.01, respectively) and were decreased by tilmicosin (P < 0.001) compared with the control. Amoxicillin decreased lactic acid bacteria (P < 0.01) counts compared with the control. The antibiotic supplementation tended to decrease total bacteria variability in the jejunum (Shannon index, P = 0.091) compared with the control. The antibiotic treatment decreased the mean total serum IgM concentration (P = 0.016) after 3 wk and did not change the mucosal histomorphometry of the small intestine. For tilmicosin, the observed positive action on piglet performance and feed intake can originate by the decreased costs of immune activation determined by the action on intestinal microbiota. For amoxicillin and doxycycline, the observation on intestinal and fecal microbiota seems to be not sufficient to explain their growth-promoting effect. Copyright © 2011. American Society of Animal Science .