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Consumer Perceptions of Precision Livestock Farming-A Qualitative Study in Three European Countries.

ABSTRACT: Scholars in the fields of animal science and technology have investigated how precision livestock farming (PLF) can contribute to the quality and efficiency of animal husbandry and to the health and welfare of farm animals. Although the results of such studies provide promising avenues for the development of PLF technologies and their potential for the application in animal husbandry, the perspectives of consumers with regard to PLF technologies have yet to be the subject of much investigation. To address this research gap, the current study explores consumer perceptions of PLF technologies within the pork and dairy value chains. The investigation is based on results from six focus group discussions conducted in three European countries, each reflecting a different market environment: Finland, the Netherlands and Spain. The results indicate that consumers expect the implementation of different PLF technologies to enhance the health and welfare of farm animals, while generating environmental improvements and increasing the transparency of value-chain processes. The analysis further reveals three over-arching consumer concerns: (1) the fear that the integration of PLF technologies will introduce more industrialisation into livestock farming production; (2) the concern that PLF technologies and data are vulnerable to misuse and cyber-crime; and (3) the concern that PLF information is not communicated adequately to allow informed purchase decisions. The research findings provide directions for members of the animal-based food value chain to make informed decisions to improve their sustainability, social responsibility and credibility by endorsing the acceptance of PLF (technologies) amongst European consumers.

SUBMITTER: Krampe C

PROVIDER: S-EPMC8146409 | biostudies-literature |

REPOSITORIES: biostudies-literature

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Project description:BackgroundPrecision Livestock Farming (PLF) is a promising approach to minimize the conflicts between socio-economic activities and landscape conservation. However, its application on extensive systems of livestock production can be challenging. The main difficulties arise because animals graze on large natural pastures where they are exposed to competition with wild herbivores for heterogeneous and scarce resources, predation risk, adverse weather, and complex topography. Considering that the 91% of the world's surface devoted to livestock production is composed of extensive systems (i.e., rangelands), our general aim was to develop a PLF methodology that quantifies: (i) detailed behavioural patterns, (ii) feeding rate, and (iii) costs associated with different behaviours and landscape traits.MethodsFor this, we used Merino sheep in Patagonian rangelands as a case study. We combined data from an animal-attached multi-sensor tag (tri-axial acceleration, tri-axial magnetometry, temperature sensor and Global Positioning System) with landscape layers from a Geographical Information System to acquire data. Then, we used high accuracy decision trees, dead reckoning methods and spatial data processing techniques to show how this combination of tools could be used to assess energy balance, predation risk and competition experienced by livestock through time and space.ResultsThe combination of methods proposed here are a useful tool to assess livestock behaviour and the different factors that influence extensive livestock production, such as topography, environmental temperature, predation risk and competition for heterogeneous resources. We were able to quantify feeding rate continuously through time and space with high accuracy and show how it could be used to estimate animal production and the intensity of grazing on the landscape. We also assessed the effects of resource heterogeneity (inferred through search times), and the potential costs associated with predation risk, competition, thermoregulation and movement on complex topography.DiscussionThe quantification of feeding rate and behavioural costs provided by our approach could be used to estimate energy balance and to predict individual growth, survival and reproduction. Finally, we discussed how the information provided by this combination of methods can be used to develop wildlife-friendly strategies that also maximize animal welfare, quality and environmental sustainability.

Project description:Several precision livestock farming (PLF) technologies, conceived for optimizing farming processes, are developed to detect the physical and behavioral changes of animals continuously and in real-time. The aim of this review was to explore the capacity of existing PLF technologies to contribute to the assessment of pig welfare. In a web search for commercially available PLF for pigs, 83 technologies were identified. A literature search was conducted, following systematic review guidelines (PRISMA), to identify studies on the validation of sensor technologies for assessing animal-based welfare indicators. Two validation levels were defined: internal (evaluation during system building within the same population that were used for system building) and external (evaluation on a different population than during system building). From 2,463 articles found, 111 were selected, which validated some PLF that could be applied to the assessment of animal-based welfare indicators of pigs (7% classified as external, and 93% as internal validation). From our list of commercially available PLF technologies, only 5% had been externally validated. The more often validated technologies were vision-based solutions (n = 45), followed by load-cells (n = 28; feeders and drinkers, force plates and scales), accelerometers (n = 14) and microphones (n = 14), thermal cameras (n = 10), photoelectric sensors (n = 5), radio-frequency identification (RFID) for tracking (n = 2), infrared thermometers (n = 1), and pyrometer (n = 1). Externally validated technologies were photoelectric sensors (n = 2), thermal cameras (n = 2), microphone (n = 1), load-cells (n = 1), RFID (n = 1), and pyrometer (n = 1). Measured traits included activity and posture-related behavior, feeding and drinking, other behavior, physical condition, and health. In conclusion, existing PLF technologies are potential tools for on-farm animal welfare assessment in pig production. However, validation studies are lacking for an important percentage of market available tools, and in particular research and development need to focus on identifying the feature candidates of the measures (e.g., deviations from diurnal pattern, threshold levels) that are valid signals of either negative or positive animal welfare. An important gap identified are the lack of technologies to assess affective states (both positive and negative states).

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Consumer Perceptions of Precision Livestock Farming-A Qualitative Study in Three European Countries.

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