As if you were hiring a new employee: on pig veterinarians’ perceptions of professional roles and relationships in the context of smart sensing technologies in pig husbandry in the Netherlands and Germany

Veterinarians are increasingly confronted with new technologies, such as Precision Livestock Farming (PLF), which allows for automated animal monitoring on commercial farms. At the same time, we lack information on how veterinarians, as stakeholders who may play a mediating role in the public debate on livestock farming, perceive the use and the impact of such technologies. This study explores the meaning veterinarians attribute to the application of PLF in the context of public concerns related to pig production. Semi-structured interviews were carried out with pig veterinarians located in the Netherlands and Germany. By using an inductive and semantic approach to reflexive thematic analysis, we developed four main themes from the interview data: (1) the advisory role of the veterinarian, which is characterized by a diverse scope, including advice on PLF, generally positive evaluations and financial dependencies; (2) the delineation of PLF technologies as supporting tools, which are seen as an addition to human animal care; (3) the relationship between veterinarian and farmer, which is context-related, ranging from taking sides with to distancing oneself from farmers; and (4) the distance between agriculture and society, in the context of which PLF has both a mitigating and reinforcing potential. The present findings indicate that veterinarians play an active role in the emerging field of PLF in livestock farming. They are aware of and reflect on competing interests of different groups in society and share positions with different stakeholders. However, the extent to which they are able to mediate between stakeholder groups in practice seems to be constrained by external factors, such as financial dependencies

Advances in keeping laying hens in various cage-free systems: part I rearing phase

SUMMARY: Cage-free housing of pullets and laying hens is becoming more and more popular around the world. This paper reviews the literature on the most common cage-free rearing systems for pullets: floor systems with or without elevated structures, multi-tier systems, systems with access to a covered veranda and/or a free-range, and organic systems. The aim is to provide an extensive overview of various aspects of these cage-free systems, such as structure and size and functional elements for the birds. Most research on pullets in cage-free systems focuses on the prevention of health and welfare problems during the later laying period. Investigations on the actual health and welfare status during rearing are rare. There is evidence that pullets should be reared in a system as similar as possible to the later housing system for layers. Particularly for complex multi-tier systems, pullets need to develop sufficient adaptive skills. Effects of providing environmental enrichment during rearing, such as plastic objects, hay or alfalfa bales and pecking blocks, on welfare in early and later life are inconsistent across all alternative pullet housing systems. To prevent feather pecking, other factors like diet and space allowance have to be considered as well. There is a need for further research regarding free-range and organic housing systems for pullets. In addition, environmental-, economic- and food safety aspects of rearing pullets in cage-free systems should be investigated in future research

Do we improve any aspects of animal welfare by implementing Computer Vision in livestock farming?

Computer Vision technology has been developed recently as a tool for measuring behaviour on the individual level in group housed livestock. This form of digital agriculture or precision livestock farming has the potential to answer to public concerns on farm animal welfare by using the data to reduce the risk of harmful social interactions such as tail biting in pig production and severe feather pecking in laying hen production. Computer Vision, however comes with changes to livestock farming and therefore can lead to new moral questions. Currently it has not resulted in much public debate. We argue that this is not to be understood as a sign that there are no societal and ethical challenges, but that – as part of responsible research and innovation – this is an important moment to explore and analyse the potential societal and ethical issues. In this paper we aim to explore the moral dimensions of the use of Computer Vision in livestock farming with a special focus on poultry. We analyse the moral dimensions from an animal welfare perspective. Although introduced to prevent welfare risks or improve the welfare status of animals, this innovation can lead to welfare questions depending on one’s concept of animal welfare

How smart should resilience be? On the need of a transdisciplinary approach to transform pig production systems

Pig production is related to many societal challenges. This raises the question whether and how pig production systems can be transformed in a way that better includes animal welfare and is responsive to (other) societal concerns. In a project funded by the Netherlands Organisation for Scientific Research (NWO), we focus on the role of resilience to explore the possibilities of defining novel production systems that better match with the interests and adaptive capacities of animals. However, to play this central role, the concept of resilience needs an integrated and transdisciplinary approach. Using the ‘SmartResilience’ project as an example, we argue that to address societal challenges in livestock production it is not sufficient to view one topic through the lenses of multiple disciplines and to produce research results from each discipline which are only supplementary to one another. We argue why complex societal challenges like transforming livestock systems can only be tackled by real collaboration between different disciplines, and why this collaboration already needs to start in the design-phase of innovations. We discuss three stages of collaboration that will lead to a deepened integration of disciplines, which will ultimately result in positive societal impact: (1) identifying the underlying concepts that play a role for achieving the project aim (e.g. animal welfare, resilience); (2) making the implicit assumptions of these concepts explicit by integrating knowledge and methods from different disciplines (e.g. philosophy and animal science); and (3) translating and incorporating the explicit assumptions of concepts into practice and into further actions within the project (e.g. pig breeding or housing strategies). By doing this, we expect to prepare a route forward for more welfare-friendly and sustainable pig production that is in dialogue with society

Tracing responsibilities in food production with animals

This paper summarises some results of the final report of the research project ‘Systematics of Responsibilities for Animal Welfare in the Livestock Sector’ (2018-2020). The project focused on the question who is fundamentally responsible for the treatment of farm animals. This question is largely and to some extent pointlessly discussed in the public. The study was commissioned by the German Federal Ministry of Agriculture (BMEL). It is based on a systematic examination of the term ‘responsibility’. Responsibility means that agents (who have the necessary means) act accordingly to their value preferences and cause consequences. In this respect, it must be taken into account that animal welfare (as based on altruistic reasoning) is not always given overriding priority in decision-making. This result becomes more plausible when analysing concrete examples of how real decisions were made. The report establishes a characteristic pattern that re-occurs in many discussions on problems in farm animal husbandry: There is an enormous gap between partakers ascribing responsibility to themselves or unto others. The report in contrast uses and extends well established ethical models and principles to create a matrix that makes it possible to say more precisely who is in fact responsible, and why. The report offers a detailed and rather extensive map of possible agents and stakeholders involved in animal husbandry based on the criteria of the matrix. This will lead to a much more distinguished judgement on responsibilities. The project has also developed a database tool in order to locate players in regards to certain characteristics. One result is to filter out those agents who may be called big players in the game at hand. The big food retailers and political bodies are prime candidates. The model can prove why they have indeed an enormous share of responsibility. The role of ‘the consumer’ is in turn to be reconsidered on this basis. The report finally offers an explanation on how responsibility and reliability are interconnected: It is much easier to stick to one’s own responsibilities if other players reliably stick to theirs. In turn, confidence in the system and its elements can be boosted whenever agents evidentially take up their responsibility and do ‘their jobs

Individuality of a group: detailed walking ability analysis of broiler flocks using optical flow approach

Impaired walking ability is one of the most important factors affecting broiler welfare. Routine monitoring of walking ability provides insights in the welfare status of a flock and assists farmers in taking remedial measures at an early stage. Several computer vision techniques have been developed for automated assessment of walking ability, providing an objective and biosecure alternative to the currently more subjective and time-consuming manual assessment of walking ability. However, these techniques mainly focus on assessment of averages at flock level using pixel movement. Therefore, the aim of this study was to investigate the potential of optical flow algorithms to identify flock activity, distribution and walking ability in a commercial setting on levels close to individual monitoring. We used a combination of chicken segmentation and optical flow methods, where chicken contours were first detected and were then used to identify activity, spatial distribution, and gait score distribution (i.e. walking ability) of the flock via optical flow. This is a step towards focusing more on individual chickens in an image and its pixel representation. In addition, we predicted the gait score distribution of the flock, which is a more detailed assessment of broiler walking ability compared to average gait score of the flock, as slight changes in walking ability are more likely to be detected when using the distribution compared to the average score. We found a strong correlation between predicted and observed gait scores (R2 = 0.97), with separate gait scores all having R2 > 0.85. Thus, the algorithm used in this study is a first step to measure broiler walking ability automatically in a commercial setting on a levels close to individual monitoring. These validation results of the developed automatic monitoring of flock activity, distribution and gait score are promising, but further validation is required (e.g. for chickens at a younger age, with very low and very high gait scores)

Group level and individual activity of broiler chickens hatched in 3 different systems

Information on the behavior of chickens hatched in different systems is limited and inconsistent across different studies. Changes in broiler activity can be measured automatically and continuously. The aim of this study was to assess the effects of 3 hatching systems on flock activity using a commercial tracking system, and to compare these findings to individual activity measured under experimental conditions. As this experiment was part of a larger study, it was possible to investigate the effects of vaccination on individual activity. In study 1, flock activity was measured in chickens that hatched either conventionally in the hatchery (HH), in a system which provided nutrition in the hatcher (HF), or on-farm (OH). Chickens were reared in 2 batches, in 12 pens/batch (1,155 animals/pen). One camera recorded top-view images of each pen. A daily activity index (moved pixels/total pixels × 100) was calculated by automated image analysis. In study 2, individual activity was measured under experimental conditions using an ultra-wideband (UWB) system. Chickens from the 3 hatching systems were reared in 3 pens (1 pen/treatment, 30 animals/pen). At d14, UWB-tags were attached to 5 chickens/pen, which tracked the distances moved (DM). In study 1, group level activity showed a significant age × hatching system interaction (F 8,752= 5.83, P < 0.001). HH and HF chickens showed higher activity levels than OH chickens in wk 1, 4, and 5. In wk 3, higher activity levels were measured in HH compared to HF, and in HF compared to OH pens. In contrast, HH chickens in small groups in study 2 showed lower DM than HF and OH chickens in wk 3 (P < 0.001). DM did not differ between treatments before vaccination, however, thereafter, HH chickens showed longer DM, whereas HF and OH chickens moved less. The results indicate that hatching system affected broiler activity at specific ages. Effects found at flock level could not be reproduced by individual measurements in study 2, although stocking density was comparable

Effects of hatching system on chick quality, welfare and health of young breeder flock offspring

Alternative hatching systems have been developed for broiler chickens to provide immediately feed and water after hatch and reduce the number or severity of early life stressors. Besides beneficial effects of these alternative hatching systems on chick quality and performance, broiler health and welfare may be positively affected as well. Especially offspring from young broiler breeder flocks may benefit, as they have been shown to be more sensitive to preturbations than offspring from older breeder flocks. This study evaluated effects of hatching systems on chick quality, health and welfare of young breeder flock offspring, using 3 different hatching systems: conventional hatchery-hatched (HH), hatchery-fed (HF), and on-farm hatching (OH). A total of 24 pens were used in a completely randomized block design, with 8 pens per hatching system and 30 chickens per pen. Chick quality at hatch and performance until 35 d of age was improved in the HF and OH compared to HH treatment, but only minor effects were found on the welfare indicators: footpad dermatitis, hock burn, cleanliness, skin lesion and gait score. No effect was observed on the dynamics of a humoral immune response after NCD vaccination, given at d 0 and 14 of age, as no differences between NCD titers were found at d 18. Animals were vaccinated with a live attenuated infectious bronchitis vaccine virus (IBV) at d 28 to address treatment related differences to disease resilience. The expressions of inflammation and epithelial integrity related genes in the trachea and histo-pathological changes in the trachea were examined at 3 d after vaccine administration. No differences between treatment groups were observed. Although beneficial effects of HF and OH systems were found for young breeder flock offspring on chick quality at hatch and body weight posthatch, only one effect of alternative hatching systems on welfare and health indicators were found. No effect of hatching system on humoral immune response or disease resilience was found

Seeing is caring – automated assessment of resource use of broilers with computer vision techniques

Routine monitoring of broiler chickens provides insights in the welfare status of a flock, helps to guarantee minimum defined levels of animal welfare and assists farmers in taking remedial measures at an early stage. Computer vision techniques offer exciting potential for routine and automated assessment of broiler welfare, providing an objective and biosecure alternative to the current more subjective and time-consuming methods. However, the current state-of-the-art computer vision solutions for assessing broiler welfare are not sufficient to allow the transition to fully automated monitoring in a commercial environment. Therefore, the aim of this study was to investigate the potential of computer vision algorithms for detection and resource use monitoring of broilers housed in both experimental and commercial settings, while also assessing the potential for scalability and resource-efficient implementation of such solutions. This study used a combination of detection and resource use monitoring methods, where broilers were first detected using Mask R-CNN and were then assigned to a specific resource zone using zone-based classifiers. Three detection models were proposed using different annotation datasets: model A with annotated broilers from a research facility, model B with annotated broilers from a commercial farm, and model A+B where annotations from both environments were combined. The algorithms developed for individual broiler detection performed well for both the research facility (model A, F1 score > 0.99) and commercial farm (model A+B, F1 score > 0.83) test data with an intersection over union of 0.75. The subsequent monitoring of resource use at the commercial farm using model A+B for broiler detection, also performed very well for the feeders, bale and perch (F1 score > 0.93), but not for the drinkers (F1 score = 0.28), which was likely caused by our evaluation method. Thus, the algorithms used in this study are a first step to measure resource use automatically in commercial application and allow detection of a large number of individual animals in a non-invasive manner. From location data of every frame, resource use can be calculated. Ultimately, the broiler detection and resource use monitoring might further be used to assess broiler welfare

Caught on Camera: On the Need of Responsible Use of Video Observation for Animal Behavior and Welfare Research

Video analysis is a popular and frequently used tool in animal behavior and welfare research. In addition to the actual object of research, video recordings often provide unforeseen information about the progress of the study, the animals or the people involved. Conflicts can arise when this information is weighed against the original intention of the recordings and broader social expectations. Uncertainty may prevent the video observers, often less experienced researchers, to properly address these conflicts, which can pose a threat to animal welfare and research quality and integrity. In this article, we aim to raise awareness of the interrelationship of variables characteristic for video-based animal studies and the potential conflicts emerging from this. We propose stepping stones for a framework which enables a culture of openness in dealing with unexpected and unintended events observed during video analysis. As a basis, a frame of reference regarding privacy and duty of care toward animals should be created and shared with all persons involved. At this stage, expectations and responsibilities need to be made explicit. During running and reporting of the study, the risk of animal welfare and research integrity issues can be mitigated by making conflicts discussible and offering realistic opportunities on how to deal with them. A practice which is outlined and guided by conversation will prevent a mere compliance-based approach centered on checklists and decision trees. Based on these stepping stones, educational material can be produced to foster reflection, co-creation and application of ethical practice