The Three Rings model has been used for many years to visualize the interactions of the affective state, physiology, and behavior in animal welfare. The intersection of the rings symbolized the need to consider the parts of animal welfare as an interactive whole, rather than separate, siloed domains. The Five Domain model presented the affective state as the true aspect of animal welfare with the first four domains having effects on the affective state. These models challenged us to understand the lives of animals as fluid, with many states and factors interacting rather than summations of individual metrics. The techniques we have historically used to assess animal welfare have essentially been limited to identifying negative welfare metrics individually within each ring or domain. Welfare assessments have been limited to the few things we can visualize during a farm visit. This blog presents an expanded concept of assessing data for animal welfare and using Machine Learning (ML) and Artificial Intelligence (AI) technology that can acknowledge the effects of many more factors on animal welfare. The three rings and five domain models have been expanded to three spheres of data that include farm and consumer effects on animal welfare.

The current state of disparate, siloed, predominantly SaaS-based insight models with first-generation data tools at the farm level has resulted in a complex web of data connections and numerous security threats. This situation has elevated the importance of data security as a fundamental aspect of food security. This first generation of digital tools has firmly placed the sector in the Trough of Disillusionment regarding the food-animal agriculture AgriTech Hype Cycle (1) as producers have been unable to effectively utilize data in innovative ways such as decision support, market access, auditing, and advanced research, without being reliant on AgriTech suppliers. To pave the way for the next generation of valuable welfare, behavior, and health AgriTech tools, it is crucial to have a deeper understanding of the three spheres within data in food animal agriculture: the Consumer, Farm, and Animal (see Figure 1). This concept is based on and includes Professor David Fraser’s Three-Rings Framework of Animal Welfare, which reflects ethical concerns about the quality of lives for farm animals (2). Fraser proposed three overlapping ethical concerns are commonly expressed regarding animal welfare: 1) that animals should lead natural lives through the development and use of their natural adaptations and capabilities, 2) that animals should feel well by being free from prolonged and intense fear, pain, and other negative states, and by experiencing normal pleasures, and 3) that animals should function well, in the sense of satisfactory health, growth and normal functioning of physiological and behavioral systems.

In the farm sphere, using farm data systems and aggregated quality food animal data from various systems across the farm will be required to enable its use for intelligence and insights into critical welfare, behavior, and health support and outputs. The use of farm-level data toward health and welfare outputs or metrics has promoted the development of the three spheres of data in food animal welfare as there needs to be Farm data ownership pre- and post-algorithmic processing (3). Farm data ownership will mean that a new interface between farm systems and animal data will need to emerge. This will be through building data standards, reducing Blackbox Algorithms, and removing data silos for critical welfare, behavior, and health metrics and outputs so that they are independent of suppliers. Welfare assessment of dairy cattle on real-time measurement and integration of valid and reliable Precision Livestock Farming (PLF) technologies is needed (4). The integration and aggregation of the data from farm-level Internet of Things systems for welfare, behavior, and health critical outputs will require assessment, independent of the AgriTech supplier, which will be imperative to ensure data quality and use towards market access and certification. This farm level of infrastructure and data ecosystem allows a farm data lake data infrastructure to be applied, where Intelligence and digital services multiplier effects can emerge, that is and can be, respective of the regionality, style, and need of the farm, as well as data ownership, governance, and overall agile approach to the deployment of future technology/ data needs (5). Adopting farm data ecosystems strengthens the defense against threats, with each farm becoming an independently decentralized/ distributed computing that is nodal rather than relying on a single service provider that is centralized. This autonomy enables farms to operate independently in the face of cyber threats or disconnection, promoting resilience in the system. While Application Program Interfaces (APIs) can be helpful, reducing their number is crucial to mitigate cyber threats, minimize costs, enhance data governance, and foster connectivity among small and regional AgriTech firms. Farm data ownership must be respected throughout the entire data process, as data is an asset for farmers (6). Ensuring the availability of quality farm-level data is essential to market certification and PLF.

Food animal welfare audits utilize the animal sphere to certify that animals are managed and housed to certain welfare standards. Currently, they are used to certify that for the sale of resulting products that the consumers see on the shelf. Food animal welfare audits have been developed to ensure this: they have to date been built around the Five Freedoms of animal welfare: 1) freedom from hunger and thirst; 2) freedom from discomfort; 3) freedom from pain, injury, and disease; 4) freedom to express normal and natural behavior (e.g. accommodating for a chicken’s instinct to roost); 5) and freedom from fear and distress. The Five Freedoms approach seeks to minimize bad animal welfare (lameness, injury, hunger, etc.). Animal welfare assessments and audits are transitioning to the Five Domains model, which relates to positive animal welfare experiences for animals. Information and data collected on-farm need to relate in real time to measurements associated with animal welfare that are useful to the farm and to audits (7). The three-sphere framework and how they incorporate the five freedoms are as follows:

Biological functioning: This concept addresses the physical fitness of the animal, including good health, normal body function, and normal growth and development. This part of the circle relates back most closely to the freedoms from hunger and thirst (Freedom 1); discomfort (Freedom 2); and pain, injury, and disease (Freedom 3) (8).

Natural living: This part of the circle emphasizes that animals should be able to lead reasonably natural lives. This includes being able to perform important, normal behaviors (e.g., dust bathing for chickens or grazing for horses) and having some natural elements in their environment (e.g., sunlight, fresh air or social contact for herd species). This concept relates most closely back to the freedom to express normal behavior (Freedom 4) (8).

Affective states: This circle considers the emotional state of the animal in that animals should feel mentally well and should not be subjected to excessive negative emotions. Negative emotions include unpleasant states such as pain, hunger, and distress. Beyond just avoiding the negative, animals should be able to experience positive emotions in the forms of pleasure or contentment (e.g., play or social contact). Affective states relate back most closely to freedom from hunger and thirst (Freedom 1); pain, injury, and disease (Freedom 3); and fear and distress (Freedom 5) (8).

Animal behavior broadly refers to any movement and activities and underlying mental process of an animal perceiving environmental stimuli and social contacts. Understanding both positive and problematic behaviors of individual animals may provide critical insights into the improvement of a broad spectrum of aspects in the animal industry, spanning from genetics, nutrition, disease, welfare, physiology, productivity, environment, management, and profitability to health that improves the farm and consumer trust in terms of standards, traceability, and quality (9,10,11). A better understanding of the values of high welfare standards can, among other things, support food security, improve productivity, and reduce antimicrobial use and greenhouse gas emission (12,13,14).

The recently introduced concept of One Welfare recognizes the interconnections between animal welfare, human well-being, and the environment (15). With the Farm [sphere], the ability for the farm to directly connect with Consumers [sphere] holds opportunity and value, kick-starting short supply chains, where a greater understanding and connection by the consumer can be given to where their food is coming from while not being bottlenecked by the supply chain. In a state like Pennsylvania (PA), the dairy industry contributes more than 52,000 jobs and $12.6 billion to the economy each year (16). 90% of PA farm income comes from within 20 miles of the farm; a state like PA needs to move toward a one-welfare PLF system, both for continued market access and to ensure incomes for thousands of farmers and their families. The overlapping areas between Farm [sphere] and Animal [sphere] with data, as well as the consumer [sphere] to the animal [sphere] with sustainability and ethical concerns, are other areas that need to be explored and further developed. For farms [sphere] and animals [sphere], data standards and open-source initiatives increase the decision support and subsequent value and use of data toward improved food-animals health and welfare models through an independent farm data infrastructure. This data can be used to inform the consumer, and where the consumer [sphere] and animal [sphere] overlap, an informed and improved relationship can emerge. The interface between Animal, Farm, and Consumer will better emerge, where sustainability and welfare-verified products can be supplied and transform our food-animal system.

The validation of data independent of AgriTech service suppliers becomes crucial when considering carbon markets, environmental standards measurements, and welfare standards. Distinguishing between farm, animal, environmental, and tech issues is essential for documenting and recording improvements. Centralizing data infrastructure and services at the farm level benefits all stakeholders by providing secure access to quality data, reducing costs, enhancing data governance, and facilitating efficient management and replication. Prioritizing the farmer and their team in the transition from mechanical to digital farming through enhanced decision support is key. It is imperative to examine the farm data ecosystem to identify and address many issues, promoting improvements and facilitating the emergence of a true economic multiplier effect. This allows for data management, basic intelligence, and interoperability of digital services and tools at the farm level, recognizing the variability of each farm and supporting appropriate decision-making processes within food animal farming and welfare.

References

1. Infographic: The Hype Cycle in Food Animal AgriTech at the Farm Level – AgriGates.io
2. A Scientific Conception of Animal Welfare that Reflects Ethical Concerns Concerns
3. Farmers Own Their Data! – AgriGates.io
4. Frontiers | A Systematic Review on Commercially Available and Validated Sensor Technologies for Welfare Assessment of Dairy Cattle (frontiersin.org)
5. Farm & Ranch Data Ecosystems – AgriGates.io
6. Data as an Asset for Livestock Farming – AgriGates.io
7. Improving Food Animal Welfare Begins with Quality Data – AgriGates.io
8. Animal welfare for youth: Part 3 – Introducing the Three Circles Model to youth – 4-H Animal Science (msu.edu)
9. Poultry Behaviour and Welfare – Michael C. Appleby, Joy A. Mench, Barry O. Hughes – Google Books
10. Observing the unwatchable through acceleration logging of animal behavior | SpringerLink
11. Frontiers | The Science of Animal Behavior and Welfare: Challenges, Opportunities, and Global Perspective (frontiersin.org)
12. High biosecurity and welfare standards in fattening pig farms are associated with reduced antimicrobial use – PubMed (nih.gov)
13. Invited review: The welfare of dairy cattle—Key concepts and the role of science – ScienceDirect
14. Frontiers | Association of Temperament and Acute Stress Responsiveness with Productivity, Feed Efficiency, and Methane Emissions in Beef Cattle: An Observational Study (frontiersin.org)
15. One Welfare – a platform for improving human and animal welfare – Pinillos – 2016 – Veterinary Record – Wiley Online Library
16. What is the Center? | Center for Dairy Excellence