Precision Dairy Technologies

And the Development of Tacit Knowledge in Ontario Dairy Farmers

Writer: Carelle Sarkis, Ph.D Candidate

Introduction

This article examines the influence of emerging technologies in the Canadian dairy industry on the development and transformation of tacit knowledge in the handlers working within these systems. Interactions between handlers and their herd are shaped in part by the housing system and the scale of operation. As the dairy industry increasingly integrates more precision technologies, certain forms of tacit knowledge become obsolete while others are reconfigured. At each stage of industrialization, tacit knowledge is reshaped in response to changing technological and structural conditions. Focusing on three housing and milking systems – tie-stall, free-stall with parlour milking, and free-stall Automatic Milking System (AMS, also known as robot milkers) – this study explores how each of these systems change the modes of human-animal interaction and the impact these systems have on how tacit knowledge manifests. Drawing on these findings, I propose two sub-categories of tacit knowledge in animal agriculture, particularly the dairy sector: barn-specific and industry-specific. Barn-specific tacit knowledge refers to localized, experiential knowledge developed through sustained interaction with a particular herd within a specific environment. Industry-specific tacit knowledge encompasses a broader set of experiential understandings relevant to the agricultural sector, including knowledge of bovine behaviour, disease prevention and treatment, milk quality, nutrition, and hygiene.

My research in this article draws from interviews conducted with five dairy farmers from southern Ontario, originally conducted as part of my doctoral research, Tacit Terrains: Mechanisation and Tacit Knowledge in Ontario Farmers, 1950s-2010s. These interviews have been recontextualized for this investigation into Ontario dairy farms. The findings offer insight into the unique nature of the Canadian dairy industry, particularly in relation to the adoption of labour-saving and automatic milking technologies, and the impact these technologies have for the development of tacit knowledge. Importantly, this analysis does not seek to make moral judgements about the housing systems used by Canadian dairy farmers. 

The Canadian Dairy Sector

The Canadian dairy sector is uniquely structured around a national supply management system, controlled by federal and provincial marketing boards, to maintain a stable supply of dairy while ensuring a fair profit for dairy farmers [1]. This policy uses “import controls, production discipline, and producer pricing to make sure milk supply remains secure," [2]. The Canadian Dairy Commission (CDC) purchases fluid milk from dairy farmers at “established support prices and administers the direct subsidy which manufacturing milk producers receive on milk sold,” [3]. Shares are regulated through market share quotas that are administered by provincial marketing board agencies on behalf of the provincial government, or by provincial government agencies [4]. Farmers must purchase or inherit a production quota, which acts as a license to sell milk [5]. Federal legislation manages the marketing of industrial milk “by determining the supply of milk through Market Sharing Quota (MSQ), setting the target price producers receive for raw milk, and establishing support prices for butter and skim milk powder," [6]. Provincial legislation oversees the marketing of fluid milk by “determining provincial milk demand and setting the production level and price for fluid milk," [7]. The MSQ ensures that there is no overproduction of milk and milk products in each province. International trade in the dairy sector is highly regulated and strictly enforced to ensure that Canadian dairy farmers are protected and prioritized in the Canadian market.

Tie-Stall System

The first housing system observed in this paper is the tie-stall system, which typically utilises a pipeline milking system. Here, the milkers – usually with automatic takeoff units – are brought to the cow, as opposed to corralling the cows and bringing them to a parlour. A distinct characteristic of the tie-stall operation is that cows are assigned an individual stall and confined to it with a tether, often a metal chain. In Canada, especially Ontario and Quebec, tie-stall housing remains the most common housing system used by dairy farmers [8]. Within this housing system, the cows remain confined to the same stall until their drying period, when they are moved to a separate area. When walking into a dairy barn, these cows become part of the physical landscape through which the handler navigates. When the handler’s tacit knowledge develops in a specific barn, their body also responds to the position of these cows and the different behaviours of these cows. Steven Feld and Keith H. Basso emphasises the importance of place and the experience of sensing it as a physical and personal process [9]. The lived body, they state, “integrates itself with its immediate environment,” [10]. The way one integrates themselves with their environment is highly dependent on the topography, morphology, meteorology, and culture of a specific place. Because of the complex makeup of places and its historical processes that have occurred to create these places, sensing places is a form of cultural activity [11]. When applying this concept to dairy farmers, their cultural activity takes place in their dairy barns and through their interactions with their herd and other dairy farmers. Places are also “complex constructions of social histories, personal and interpersonal experiences, and selective memory,” [12]. Places are actively sensed through corporeal interactions. The physical landscape thus becomes “wedded to the landscape of the mind,” [13].

A tie stall barn at the Canada Agriculture and Food Museum in Ottawa, ON.

In a tie-stall barn, the handler’s body responds to the physical placement of each cow in her tie stall. Tacit knowledge is an embodied understanding of place; thus, physical interactions  are a necessary precondition to developing tacit knowledge. Whichever handler spends the most time in the barn interacting with the cows has likely developed a deeper and more tacit understanding of these cows. Similarly, the longer a handler has been working around female bovines, the more tacit knowledge they may have around how to interact with, and care for, these animals. Dairy farmers who have been in the business their whole lives, like Joe Dairyman who has farmed for over 50 years [14], have developed an incredibly deep tacit understanding of dairy cows and the dairy industry. For Joe, he instinctually knows that upon going into the barn if “the cows are all laying down, chewing their cuds, they're all happy,” [15]. Ensuring that cows are happy and comfortable is not just a welfare concern, it also ensures productivity. There is a lot of research dedicated to understanding bovine behaviours and creating housing that prioritizes animal welfare while also staying practical and efficient [16].

Tie-Stall Scenarios

The following section presents two scenarios involving handlers operating in tie-stall barns equipped with pipeline milking systems and automatic take-off units. In each case, the handler conducts a routine walkthrough of their respective barn. While the technological setup is comparable, the handlers work in different environments with distinct herds, each with unique needs and temperaments. These scenarios illustrate how barn-specific tacit knowledge emerges and manifests, shaped by the particularities of both the herd and the physical environment.

In Figure 1, Handler 1’s herd responds with curiosity and excitement, prompting the handler to make more frequent stops during the walkthrough to manage the animals’ behaviour. They stop at cows A, B, C, and D. In this barn, Cow A frequently twists her chain, requiring more frequent adjustments. Cow B tends to kick Cow C, prompting the handler to monitor Cow C for signs of injury. Cow D often pushes her feed out of reach and becomes disruptive, leading the handler to routinely stop and reposition her feed during each walkthrough. These are behaviours that Handler 1 has become attuned to through their experience in the barn with this particular herd. While walkthroughs will vary, these may be some things that Handler 1 is looking out for in addition to their usual set of observations.

In Figure 2, Handler 2’s herd is curious and enjoys engaging with the people who enter the barn; some of the cows even enjoy being pet. Handler 2 proceeds through the barn, deliberately avoiding Cow A, who tends to lunge her head forward and attempt to nudge them. The handler then stops at Cow B—typically a brief, affectionate interaction—but on this occasion, the pause is to assess her recovery from winter dysentery and to monitor any remaining symptoms. In each scenario, the handlers rely on sensory cues to make observations and judgements about the animals – listening for certain sounds or absences of sound, assessing barn ventilations through smell, and any visual indications that may indicate distress or signs of estrus in the herd [17]. The knowledge of what to look for and how to know that things are going well is a knowledge developed through experience working on the farm. If we were to place Handler 1 in Handler 2’s barn, they may very well get nudged by Cow A because Handler 1 is not familiar with this barn. However, in terms of industry-specific tacit knowledge, these handlers can effectively manage each other’s barns because of their understanding of dairy farming that can be broadly applied to other barns; they may just need some time to adjust to the environment and to the herd. These scenarios do not account for the interactions that occur during milking times or barn maintenance; however, the same principles may still be applied [18].

Because the tie-stall barn ensures that each cow is in the same place day after day (apart from when she is being dried off or culled), the handlers become deeply familiar with the animals and begin to associate these cows with the specific stall they are assigned to in the barn. Tie-stall barns require “more labour per cow for feeding and milking [which creates] greater opportunity for the herdsperson to observe welfare problems in individual cows,” [19]. The handlers in a tie-stall operation are granted more chances for close encounters with individual animals versus in a free-stall housing system where the cows are free to roam. The tie-stalls create the expectation that the same cow will be in the same place at any given time. The handler’s physical understanding of the barn includes the different cows. 

A key characteristic of tie-stalls is confinement to a singular stall [20]. These cows have limited movement and are easy for the handler to locate and control. In a loose-housing or free-stall system, cows use stalls primarily for lying but are not tethered and can move freely within the pen. Consequently, animal handling differs from the tie-stall system, as the cows are not consistently located in predictable positions. The interactions that the handler has with the animals changes drastically and being safe around the animals changes too. In this context, the handler’s “responses to warning sensations must be embodied and automatic” [21] to stay safe – they must also be aware of these warning signs and have a certain familiarity with bovine behaviours. In both housing systems, there is the risk of being kicked, but the risks are increased in the free-stall system if the handler does not know how to properly and safely move the bovines. Additionally, cows have a strong social hierarchy [22] that becomes more pronounced in the loose housing system because higher ranking animals may become more possessive over certain pens. 

Loose Housing Systems

Parlour milking system via Government of Ontario, 2022.

In loose housing systems, the cows are brought to the milking parlour – a separate room that has the milking devices [23] – rather than having the milkers brought to them, like in a tie-stall operation. Out of the three farmers I interviewed with this milking system, all of them use rumination collars that track data such as “how much they're chewing their cud [rumination], how much time they're spending eating, how much time they're spending lying down, how much time they're spending walking,”[24]. These collars act as ID tags in the parlour [25], which tracks the milk volume, the conductivity of the milk, and the litres of milk produced by each cow [26]. For Bryan Dairyman, these collars increase efficiency in the barn because “without having to go look at the cows all the time, I can go on the computer and it'll alert me to cows that are either in heat or cows that aren't feeling good," [27]. These collars present a different way for dairy farmers to know and understand their herds. Unlike the place-based familiarity characteristic of tie-stall operations, handlers in free-stall systems rely on technologies such as rumination collars to monitor their herds, especially when scale or constant movement complicates direct tracking. As Bryan pointed out in the interview, when operating in a tie-stall operation, one could physically see which cows were not eating because there would be food sitting in front of her stall. However, in an open-stall system, the only way to efficiently and effectively track the consumption of a singular cow is through the rumination collars.

Additionally, the movement through the barn changes drastically when moving from a tie-stall system to an open-stall system. During a regular walkthrough, as depicted in Figure 3, the handler does not stop often. When they do stop, they do not directly interact with any of the cows. Some cows are eating, while others lay in the stalls, and a few roam. The cows are constantly moving, and thus the handler’s development of barn-specific tacit knowledge does not depend on the physical placement of the cows in the barn; instead, it depends on an intimate understanding of the collar technology and a strong understanding of cow behaviour that is broadly applied. A strong understanding of bovine behaviour is important for a handler in this system because they are moving cows more frequently to the milking parlour and need to have this knowledge in order to be safe, but also to effectively move the cows in the proper direction [28]. In Figure 4, a depiction of what it may look like for the handler to walk through the pen shows that the handler has to avoid the cows. Figure 4 is a static depiction of what may happen, but the bovines would likely not remain stagnant. 

As previously noted, the cows living in these housing systems are brought to a milking parlour where they are milked by automatic takeoff milkers at the same time. In all milking systems, the process is the same: the cow’s teats are cleaned with iodine, the milkers are placed on the teats, she is milked, the milker comes off, and her teats are cleaned with iodine once more. In both the tie-stall and parlour milking system, handlers work in close physical proximity to the cows, developing tactile and visual familiarity with the udder and the ability to distinguish between healthy teats and those potentially affected by mastitis by feeling how turgid the udder is and seeing how ‘full’ it looks. This knowledge is an example of industry-specific tacit knowledge that most dairy farmers have developed through their experience. Although interactions between handlers and cows change in a free-stall system, the process of corralling cows to the parlour and attaching milkers still enables handlers to develop a close understanding of the animals and cultivate a substantial repertoire of tacit knowledge – both industry- and barn-specific. 

Automatic Milking System (AMS)

As technologies become more advanced, the development of tacit knowledge grows complex and becomes more challenging to identify. The acquisition of the AMS further complicates the relationship between handler and bovine because of the decrease in face-to-face interactions. The purpose of these machines is to “replace conventional twice-a-day milking managed by people with a system that supposedly allows cows the freedom to be milked automatically whenever they choose" [30]. Similar to rumination collars used in parlour systems, AMS collars are equipped with radio frequency tags that also regulate access to the milking robots, as well as “keeping a record of their milk yield and milking frequency, and determining how much food to provide during each milking," [31]. Some robots can also sample the milk and test it for infections – if/when an infection is detected, the robot can “automatically divert the cow’s milk sample and alert the farmer," [32]. The labour requirements of the AMS differs from those of other dairy farms. While milking is automated, new tasks emerge such as “pushing” cows toward the robot if they have gone too long between milkings [33].  Labour shifts toward data management, with farmers spending more time analysing information collected by the AMS. A study by Butler and Bear (2012) reveals that “more time had to be set aside to observe the cows with the aim of picking up health and welfare issues which had not been identified by the AMS," [34].  The structure of the workload changes and milking is no longer at the forefront when farmers adopt the AMS [35]. As Butler and Bear note: “farmers may have less hands-on contact with their cows in the milking parlour, but more time can be released for observation of cows which can still be done together with the aid of the data generated by the AMS," [36]. Here, more ‘traditional’ labour is being changed by the onset of technology. 

The development of tacit knowledge in dairy farmers who use the robot milking system differs from those who do not use them. While there is still plenty of overlap in the tasks that are being done by farmers with AMS and those without, the majority of the interactions that farmers have with their herd happens during milking thus milking cows is a key factor in determining the depth of tacit knowledge in dairy farmers [37].The acquisition of robot milkers removes those interactions that are key in developing a strong understanding of the herd – but the data collected by the AMS changes the nature of the knowledge acquired by farmers. In Figure 5, the handler enters the utility room, then the cow pen, and stops at the robot milker. They conduct a walkthrough to ‘push’ specific cows toward the unit, then exit the pen, pausing twice along the way. In an AMS barn, walkthroughs become more intentional as the autonomy provided by AMS reduces the need for a routine presence. For example, in her free-stall system, Sally was regularly around the cows by performing routine chores in the barn and corralling the cows for milkings. After installing the AMS, however, she began doing “more intentional walkthroughs [of the barn] to just look at the cows and check things out," [38].

Unlike the continuous, incidental exposure to animals that fosters tacit knowledge in traditional milking systems, AMS requires farmers to engage more intentionally to maintain this knowledge. For farmers using AMS, barn-specific tacit knowledge shifts from a focus on cattle to a focus on the technology and its data outputs. A dairy farmer with deep familiarity with their robotic milking system possesses a rich form of tacit knowledge that diverges from the traditional skill set developed in tie-stall or parlour systems.

Conclusion

This article has explored the development of tacit knowledge on Ontario dairy farms, with particular attention to the distinction between barn-specific and industry-specific forms. As dairy agriculture increasingly integrates precision technologies, the expression and transmission of tacit knowledge become more diffused and challenging to trace. The acquisition of tacit knowledge is inherently embodied and for dairy farmers, emerges through habitual interaction with both animals and environment; our bodies are our instruments through which we process the external world [39]. However, technologies like AMS, sensors, and cameras reduce the need for the farmer to be physically present in the barn, and as a result, the lens through which tacit knowledge develops becomes mediated through data. While this paper offers an initial examination of how tacit knowledge manifests within this context, it merely begins to address a complex and underexplored field.

Glossary

Cow: Refers to a female bovine who has given birth to at least 1-2 calves and is producing milk. 

Heifer: Refers to a young female bovine who has not yet given birth to a calf. 

Calf: Term used to describe young cattle, male or female, from birth until the end of the weaning period. 

Dry Cow: All dairy cows must go through a ‘dry’ period in which milk production is paused. The dry period is “the period before calving that cows are not milked, which is traditionally about 6 to 8 weeks.” 

Culling Cow: A cow that is being removed from the herd – the reasons vary and depend on a range of factors. 

Female Bovine: A general term that includes cows, heifers, calves, and dry cows. 

Handler: This term refers to the operator working with the female bovines on the dairy farms. 

Industrial Milk: Refers to dairy products such as butter, cheese, yogurt, and ice cream.

Fluid Milk: Refers to dairy products such as milk and cream.

Tacit knowledge: a form of intuitive knowledge that is developed and strengthened through experience.

Endnotes

[1] The Canadian Egg and Poultry sectors are also under supply management but will not be discussed in this paper. 

[2] Dairy Farmers of Ontario. Managing Supply. 2022.

[3] Carol Elizabeth Bray. Canadian Dairy Policy. Washington, D.C: U.S. Dept. of Agriculture, Economic Research Service, Foreign Demand and Competition Division, 1976. Pp. ii. 

[4] Bray. Canadian Dairy Policy. pp. ii.

[5] Nogueira, Lia, Richard R. Barichello, Kathy Baylis, and Hayley H. Chouinard. “Policy Risk in the Canadian Dairy Industry.” Applied Economic Perspectives and Policy 34, no. 1 (2012). pp. 148. 

[6] John Stephen (J.S.) Clark. An Investigation of the Marketing of Butterfat by the Canadian Dairy Industry. Consumer and Market Demand Agricultural Policy Research Network. Dept. of Rural Economy, University of Alberta, 2008. pp. 3.

[7] Clark, J. S. An Investigation of the Marketing of Butterfat. Pp. 3.

[8] Government of Canada. Dairy Barns by Type. 2024. 

[9] Steven Feld and Keith H. Basso. Senses of Place. 1st ed. Santa Fe, N.M: School of American Research Press, 1996. pp. 55.

[10] Feld, Steven., and Keith H. Basso. Senses of Place. pp. 22.

[11] Ibid, 83.

[12] Ibid, 167.

[13] Ibid, 55.

[14] Name changed for privacy.

[15]  Haley, D.B, J Rushen, and A.M De Passille. “Behavioural Indicators of Cow Comfort: Activity and Resting Behaviour of Dairy Cows in Two Types of Housing.”Canadian Journal of Animal Science 80, no. 2. 2000. pp. 257.

[16] For more see: Chambers, Robert, Arnold Pacey, and Lori Ann Thrupp. Farmer First: Farmer Innovation and Agricultural Research. London: Intermediate Technology Publications, 1993. ; Aland, Andres, and Thomas Banhazi. Livestock Housing: Modern Management to Ensure Optimal Health and Welfare of Farm Animals. Wageningen: Wageningen Academic Publishers, 2013. ; Haley, D.B, J Rushen, and A.M De Passille. “Behavioural Indicators of Cow Comfort: Activity and Resting Behaviour of Dairy Cows in Two Types of Housing.” Canadian Journal of Animal Science 80, no. 2 (2000): 257–63.

[17] Interviews: Bryan Dairyman* (Ontario Dairy Farmer) interviewed by author. April 9, 2025; Cameron Dairyman* (Ontario Dairy Farmer) interviewed by author. January 21, 2025; Joe Dairyman* (Ontario Dairy Farmer) interviewed by author. January 7, 2025; Sally Dairy* (Ontario Dairy Farmer) interviewed by author. March 10, 2025. *Names changed for privacy

[18] While these scenarios are hypothetical, they are based on my own observations made during a tour of a tie-stall barn. During the tour, the farmer was stopping at certain cows and petting them while also making comments to me like ‘look out for that one, she tends to nudge.’ The farmer demonstrated a deep connection to his herd and a subconscious spatial awareness of his barn.

[19] C.J.C. Phillips et al. “A review of the impact of housing on dairy cow behaviour, health and welfare” Chapter in: Aland, Andres, and Thomas Banhazi. Livestock Housing: Modern Management to Ensure Optimal Health and Welfare of Farm Animals. Wageningen: Wageningen Academic Publishers, 2013. pp. 38.

[20] Elise Shepley, Joop Lensink, and Elsa Vasseur. “Cow in Motion: A Review of the Impact of Housing Systems on Movement Opportunity of Dairy Cows and Implications on Locomotor Activity.” Applied Animal Behaviour Science 230 (2020). pp. 2.

[21] Joy Parr. “Our Bodies and Our Histories of Technology and the Environment” in: Reuss, Martin., and Stephen H. Cutcliffe. The Illusory Boundary: Environment and Technology in History. Charlottesville: University of Virginia Press, 2010. pp. 32.

[22] See: Schein, Martin W, and Milton H Fohrman. “Social Dominance Relationships in a Herd of Dairy Cattle.” British Journal of Animal Behaviour 3, no. 2. 1955. 45–55. 

[23] There are different kinds of parlour systems – a rotary parlour, step-up walk-through parlour, and a parallel parlour. The farmers I interviewed had either a step-up walk-through or a parallel parlour.

[24] Interview: Cameron Dairyman. January 21, 2025

[25] These collars differ from the ID tags that are typically seen on cattle’s ears as these collars are barn-specific and have no correlation to the Canadian Cattle Identification Agency. 

[26] Interview: Bryan Dairyman. April 9, 2025

[27] Ibid.

[28] See: Grandin, Temple. Livestock Handling and Transport. 2nd ed. Oxon, UK ; CAB International Pub., 2000.

[29] Interviews: Bryan Dairyman. April 9, 2025; Cameron Dairyman. January 21, 2025; Joe Dairyman. January 7, 2025.

[30] Lewis Holloway, Christopher Bear, and Katy Wilkinson. “Re-Capturing Bovine Life: Robot–Cow Relationships, Freedom and Control in Dairy Farming.” Journal of Rural Studies. 2014. pp. 132.

[31] Holloway, Bear, Wilkinson. “Re-Capturing Bovine Life.” pp. 133.

[32] Interview: Sally Dairy. March 10, 2025

[33] Nathalie Hostiou, Jocelyn Fagon, Sophie Chauvat, Amélie Turlot, Florence Kling-Eveillard, Xavier Boivin, and Clément Allain. “Impact of Precision Livestock Farming on Work and Human-Animal Interactions on Dairy Farms. A Review.” Biotechnologie, Agronomie, Société et Environnement 21, no. 4. 2017. pp. 271. ; Interview: Sally Dairy. March 10, 2025.

[34] Deborah Butler, Lewis Holloway, and Christopher Bear. “The impact of technological change in dairy farming: Robotic milking systems and the changing role of the stockperson.” Journal of the Royal Agricultural Society of England. 173. 2012. pp. 4.

[35] For more see: Tse, Christina. "The adoption of automatic milking systems on Canadian dairy farms: Changes in cow health, management and animal welfare." PhD diss., University of Calgary, 2016. ; Tse, C, H.W Barkema, T.J DeVries, J Rushen, and E.A Pajor. “Effect of Transitioning to Automatic Milking Systems on Producers’ Perceptions of Farm Management and Cow Health in the Canadian Dairy Industry.” Journal of Dairy Science 100, no. 3 (2017): 2404–14. ; Von Keyserlingk, Marina A.G, Katelyn E Mills, and Daniel M Weary. “Attitudes of Western Canadian Dairy Farmers toward Technology.” Journal of Dairy Science 107, no. 2 (2024): 933–43.

[36] Butler, Holloway, Bear. “The impact of technological change in dairy farming.” pp. 5-6.

[37] This is not to suggest that dairy farmers using AMS possess less tacit knowledge, nor is it an attempt to assign value to different forms of such knowledge. Rather, it highlights that direct interaction with animals remains a central aspect of dairy farming, and those without AMS often engage more frequently with their herds due to the demands of scheduled milking.

[38] Interview: Sally Dairy. March 10, 2025.

[39] Michael Polanyi. The Tacit Dimension. [1st ed.]. Garden City, N. Y: Doubleday, 1966. pp. 16. ; Joy Parr. Sensing Changes: Technologies, Environments, and the Everyday, 1953-2003. Vancouver: UBC Press, 2010. pp. 1.

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