Smart Technologies Lead to Smart Answers? On the Claim of Smart Sensing Technologies to Tackle Animal Related Societal Concerns in Europe Over Current Pig Husbandry Systems

How do pig veterinarians view technology-assisted data utilisation for pig health and welfare management? A qualitative study in Spain, the Netherlands, and Ireland

BACKGROUND

Application of data-driven strategies may support veterinarians' decision-making, benefitting pig disease prevention and control. However, little is known about veterinarians' need for data utilisation to support their decision-making process. The current study used qualitative methods, specifically focus group discussions, to explore veterinarians' views on data utilisation and their need for data tools in relation to pig health and welfare management in Spain, the Netherlands, and Ireland.

RESULTS

Generally, veterinarians pointed out the potential benefits of using technology for pig health and welfare management, but data is not yet structurally available to support their decision-making. Veterinarians pointed out the challenge of collecting, recording, and accessing data in a consistent and timely manner. Besides, the reliability, standardisation, and the context of data were identified as important factors affecting the efficiency and effectiveness of data utilisation by veterinarians. A user-friendly, adaptable, and integrated data tool was regarded as potentially helpful for veterinarians' daily work and supporting their decision-making. Specifically, veterinarians, particularly independent veterinary practitioners, noted a need for easy access to pig information. Veterinarians such as those working for integrated companies, corporate veterinarians, and independent veterinary practitioners expressed their need for data tools that provide useful information to monitor pig health and welfare in real-time, to visualise the prevalence of endemic disease based on a shared report between farmers, veterinarians, and other professional parties, to support decision-making, and to receive early warnings for disease prevention and control.

CONCLUSIONS

It is concluded that the management of pig health and welfare may benefit from data utilisation if the quality of data can be assured, the data tools can meet veterinarians' needs for decision-making, and the collaboration of sharing data and using data between farmers, veterinarians, and other professional parties can be enhanced. Nevertheless, several notable technical and institutional barriers still exist, which need to be overcome.

A qualitative survey approach to investigating beef and dairy veterinarians' needs in relation to technologies on farms

Globally, farmers are being increasingly encouraged to use technologies. Consequently, veterinarians often use farm data and technologies to provide farmers with advice. Yet very few studies have sought to understand veterinarians' perceptions of data and technologies on farms. The aim of this study was to understand veterinarians' experiences and opinions on data and technology on beef and dairy farms. An online qualitative survey was conducted with a convenience sample of 36 and 24 veterinarians from the United Kingdom and Ireland, respectively. The data were analysed using reflexive thematic analysis to generate four themes: (1) Improving veterinary advice through data; (2) Ensuring stock person skills are retained; (3) Longevity of technology; and (4) Solving social problems on farms. We show that technologies and data can make veterinarians feel more confident in the advice they give to farmers. However, the quality and quantity of data collected on cattle farms were highly variable. Furthermore, veterinarians were concerned that farmers can become over-reliant on technologies by not using their stockperson skills. As herd sizes increase, technologies can help to improve working conditions on farms with multiple employees of various skillsets. Veterinarians would like innovations that can help them to demonstrate their competence, influence farmers' behaviour, and ensure sustainability of the beef and dairy industries.

Exploring the data divide through a social practice lens: A qualitative study of UK cattle farmers

Appropriate management decisions are key for sustainable and profitable beef and dairy farming. Data-driven technologies aim to provide information which can improve farmers' decision-making practices. However, data-driven technologies have resulted in the emergence of a "data divide", in which there is a gap between the generation and use of data. Our study aims to further understand the data divide by drawing on social practice theory to recognise the emergence, linkages, and reproduction of youngstock data practices on cattle farms in the UK. Eight focus groups with fifteen beef and nineteen dairy farmers were completed. The topics of discussion included data use, technology use, disease management in youngstock, and future goals for their farm. The transcribed data were analysed using reflexive thematic analysis with a social practice lens. Social practice theory uses practices as the unit of analysis, rather than focusing on individual behaviours. Practices are formed of three elements: meaning (e.g., beliefs), materials (e.g., objects), and competencies (e.g., skills) and are connected in time and space. We conceptualised the data divide as a disconnection of data collection practices and data use and interpretation practices. Consequently, we were able to generate five themes that represent these breaks in connection.Our findings suggest that a data divide exists because of meanings that de-stabilise practices, tensions in farmers' competencies to perform practices, spatial and temporal disconnects, and lack of forms of feedback on data practices. The data preparation practice, where farmers had to merge different data sources or type up handwritten data, had negative meanings attached to it and was therefore sometimes not performed. Farmers tended to associate data and technology practices with larger dairy farms, which could restrict beef and small-scale dairy farms from performing these practices. Some farmers suggested that they lacked the skills to use technologies and struggled to transform their data into meaningful outputs. Data preparation and data use and interpretation practices were often tied to an office space because of the required infrastructure, but farmers preferred to spend time outdoors and with their animals. There appeared to be no normalisation of what data should be collected or what data should be analysed, which made it difficult for farmers to benchmark their progress. Some farmers did not have access to discussion groups or veterinarians who were interested in data and therefore could not get feedback on their data practices.These results suggest that the data divide exists because of three types of disconnect: a disconnect between elements within a practice because of tensions in competencies or negative meanings to perform a practice; a disconnect between practices because of temporal or spatial differences; and a break in the reproduction of practices because of lack of feedback on their practices. Data use on farms can be improved through transformation of practices by ensuring farmers have input in the design of technologies so that they align with their values and competencies.

US Swine Industry Stakeholder Perceptions of Precision Livestock Farming Technology: A Q-Methodology Study

This study used the Q-methodology approach to analyze perceptions of precision livestock farming (PLF) technology held by stakeholders directly or indirectly involved in the US swine industry. To see if stakeholders' perceptions of PLF changed over time as PLF is a rapidly evolving field, we deliberately followed up with stakeholders we had interviewed 6 months earlier. We identified three distinct points of view: PLF improves farm management, animal welfare, and laborer work conditions; PLF does not solve swine industry problems; PLF has limitations and could lead to data ownership conflict. Stakeholders with in-depth knowledge of PLF technology demonstrated elevated levels of optimism about it, whereas those with a basic understanding were skeptical of PLF claims. Despite holding different PLF views, all stakeholders agreed on the significance of training to enhance PLF usefulness and its eventual adoption. In conclusion, we believe this study's results hold promise for helping US swine industry stakeholders make better-informed decisions about PLF technology implementation.

Social and ethical implications of data and technology use on farms: a qualitative study of Swedish dairy and pig farmers

Introduction

Livestock farmers are being increasingly encouraged to adopt digital health technologies on their farms. Digital innovations may have unintended consequences, but there tends to be a pro-innovation bias in previous literature. This has led to a movement towards "responsible innovation," an approach that questions the social and ethical challenges of research and innovation. This paper explores the social and ethical issues of data and technologies on Swedish dairy and pig farms from a critical perspective.

Methods

Six focus groups were conducted with thirteen dairy and thirteen pig farmers. The data were analysed using reflexive thematic analysis and a digital critical health lens, which focuses on concepts of identity and power.

Results and discussion

The analysis generated four themes: extending the self, sense of agency, quantifying animals, and managing human labour. The findings suggest that technologies can change and form the identities of farmers, their workers, and animals by increasing the visibility of behaviours and bodies through data collection. Technologies can also facilitate techniques of power such as conforming to norms, hierarchical surveillance, and segregation of populations based on data. There were many contradictions in the way that technology was used on farms which suggests that farmers cannot be dichotomised into those who are opposed to and those that support adoption of technologies. Emotions and morality played an important role in the way animals were managed and technologies were used by farmers. Thus, when developing innovations, we need to consider users' feelings and attachments towards the technologies. Technologies have different impacts on farmers and farm workers which suggests that we need to ensure that we understand the perspectives of multiple user groups when developing innovations, including those that might be least empowered.

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.

Supplementary Information

The online version contains supplementary material available at 10.1007/s10460-023-10450-6.

Pig Manure Management: A Methodology for Environmentally Friendly Decision-Making

The current trend towards larger pig farms increases their profitability but might harm animal welfare and the environment. More efficient pig manure management is a way to address this challenge. Available manure handling and utilisation systems may feature from 8 to 50% nutrient loss to the environment. Therefore, the proper choice of technological solutions is of high priority. In regard, the study developed a methodology including calculation, analysis and modelling techniques for the accurate accounting of manure amount, its fractions and their nitrogen and phosphorus content for different processing technologies with due regard to the limiting factors of the farm and the end-product consumer requirements. The methodology was applied to justify the best suitable processing technology for a large-scale pig farm in the Leningrad Region with 17,800 heads of pigs and 54,750 t of pig manure per year. The selected technology included manure separation into fractions, aeration and secondary sedimentation of the liquid fraction and passive composting of the solid fraction. It demonstrated the total amount of nitrogen (N) and phosphorus (P) in the end-products of 278.94 t per year, with the 26% total nutrients loss on all technological stages, and specific capital and operating costs of USD 55.5 per ton of manure produced. The methodology was tested by comparing the calculated data and the data from previous surveys of 15 pig farms in Russia. The differences between the values were found from 0.9 to 12.5% in mass; 2.8 to 13.9% in N content and 1.7 to 9.9% in P content. The developed methodology supports planning the production of the manure-based end-products in a given amount and with target nutrient content, depending on different processing technological solutions, achieving both economic and environmental goals.