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Romano, E.; Brambilla, M.; Cutini, M.; Giovinazzo, S.; Lazzari, A.; Calcante, A.; Tangorra, F.M.; Rossi, P.; Motta, A.; Bisaglia, C.; et al. Cattle Feeding Precision by Automatic Feeding Systems. Encyclopedia. Available online: https://encyclopedia.pub/entry/51531 (accessed on 17 November 2024).
Romano E, Brambilla M, Cutini M, Giovinazzo S, Lazzari A, Calcante A, et al. Cattle Feeding Precision by Automatic Feeding Systems. Encyclopedia. Available at: https://encyclopedia.pub/entry/51531. Accessed November 17, 2024.
Romano, Elio, Massimo Brambilla, Maurizio Cutini, Simone Giovinazzo, Andrea Lazzari, Aldo Calcante, Francesco Maria Tangorra, Paolo Rossi, Ambra Motta, Carlo Bisaglia, et al. "Cattle Feeding Precision by Automatic Feeding Systems" Encyclopedia, https://encyclopedia.pub/entry/51531 (accessed November 17, 2024).
Romano, E., Brambilla, M., Cutini, M., Giovinazzo, S., Lazzari, A., Calcante, A., Tangorra, F.M., Rossi, P., Motta, A., Bisaglia, C., & Bragaglio, A. (2023, November 14). Cattle Feeding Precision by Automatic Feeding Systems. In Encyclopedia. https://encyclopedia.pub/entry/51531
Romano, Elio, et al. "Cattle Feeding Precision by Automatic Feeding Systems." Encyclopedia. Web. 14 November, 2023.
Cattle Feeding Precision by Automatic Feeding Systems
Edit

Livestock farming is experiencing a significant shift towards automation to reduce the many repetitive tasks requiring little skills and high workloads. For farmers, automatic feeding systems for ruminants can be an excellent way to reduce their daily workload and improve animal welfare and production quality. Studies have demonstrated that adopting automatic feeding systems leads to lower energy requirements, lower feed waste, and improved animal welfare, which unequivocally aligns with the farmers' perspective. However, to maximize the flexibility of the feeding robots and reap the benefits, thorough economic and structural planning that considers all of the farming site's features is necessary. Additionally, automatic feeding systems can help involve younger generations in animal farming and increase inclusivity, which may foster female entrepreneurship, all while maintaining good feeding practices.

total mixed ration TMR AFS automation beef Ruminants Dairy

1. Introduction

Automatic feeding systems (AFSs) ease the workload of dairy farmers, save time, and increase workload flexibility.
Decreased workloads related to shed procedures allow the farmers to focus on organizational activities. As reported by Hansen et al. [1], who studied the farmers’ well-being following the adoption of an automatic milking system (AMS), automatic systems facilitate the occurrence of these scenarios. Additionally, a review conducted by Lovarelli et al. [2] highlights how automatic systems (AFSs and AMSs) and precision livestock farming (PLF) can improve the economic sustainability of livestock systems. A comparison of a conventional dairy farm with a precision-agriculture-based farm by Bragaglio et al. [3] found that using an AFS and AMS led the precision-agriculture-based farm to lower its values of MJ consumption and oil equivalents, which resulted in a positive impact on the environment. In terms of the effect of feeding systems on ammonia and greenhouse gas (GHG) emissions from the decomposition of dairy cows’ excreta on the housing floor, Rodrigues et al. [4] have pointed out that administering the total mixed ration (TMR) with an AFS can lower N–NH3 emissions (g/kg excreta) compared to conventional feeding, without a significant difference regarding their contribution to GHG emissions.
The fully functioning AFS relies on the studies that introduced the concept of total mixed ration (TMR) for ruminants’ feeding. The presentation of the TMR feeding concept for dairy herds dates back to the 2nd half of the 20th century [5] following the increases in herd dimension and the modernization of animal housing (i.e., free-stall handling and the use of a milking parlor), which resulted in a significant rise in milk production [6].
However, the introduction of TMR rationing in dairy and beef farms had to wait until the 1960s [7], thanks to the design, development, and subsequent spread of mechanical mixing devices (stationary mixing plants and mixing feeding wagons—MFWs), which have become the dominant equipment for TMR preparation and distribution on cattle farms [8]. TMR feeding has proven to be the feeding method closest to reared ruminants’ physiology [9][10], obtaining remarkable consensus given the suitability of existing AFSs for European dairy farms [11].
The TMR fosters ruminants’ feed reception with subsequent improvements in their efficiency and health status [12] provided operators adopt proper precautions (e.g., water addition during mixing) and adequate mixing times [13][14][15], which are fundamental regarding the TMR particle size and consistency limiting aspects [16][17].

The TMR improves ruminants' efficiency and health status [12] and promotes better feed reception, particularly when frequently administered to animals. However, it is essential that operators take proper precautions, such as adding water during mixing, and allow for adequate mixing times [13][14][15]. This is particularly important regarding TMR particle size and consistency, which are limiting factors that should be considered closely. Studies have shown that TMR's particle size and consistency can significantly impact ruminant health and efficiency [16][17].

2. Automatic Feeding Pushing and Administering Technological Solutions

Feeding cattle on livestock farms is a labor-intensive operation. Automatic feed pushers (AFPs) are the first tools developed for the recurring pushing and approaching of the feed that the animals move away from the manger when they sort the TMR against long forage particles in favor of the smaller, high-starch grain particles [18]. AFPs warrant constant cattle feed availability in the manger between TMR distributions.
AFS design aims to reduce workforce use and improve work flexibility. Their introduction dates to the end of the 20th and the beginning of the 21st century, first in the Northern European countries and then in Italy (since 2013, mainly in the Northern Italian regions) [19]. However, their versatility has caused them to go far beyond the initial concept, making them complementary to the well-consolidated chopping–mixing wagon technology in both milk and meat production and a wide range of farming situations (e.g., farms in mountainous areas or aimed at the protected designation of origin productions) [20][21]. The systems currently on offer differ in their mode of operation and increasing complexity of technological level; ration preparation and delivery may be carried out in a stationary mixer, which feeds ration-delivering wagons, up to fully automatic systems that carry out all of the operations necessary to prepare the TMR autonomously.
Nowadays, the AFS market is thriving. In 2018, Tangorra et al. [22] identified 20 AFS manufacturers and more than 1250 robotic units on farms. Reger et al. [23] recently listed 24 AFS-producing companies, including those operating under third-party brands. The AFS types currently on the market refer to three increasing automation levels [24]:
  • Stage I: machinery whose automation refers specifically to TMR shredding, mixing, and distribution (several times a day). They commonly rely on a stationary mixer that operators fill daily with each ingredient of the TMR from bunker silos either manually or using suitable loading machines.
  • Stage II: compared to Stage I machinery, the automation extends to the initial filling operation. TMR ingredients can either be loaded automatically in a stationary mixer, which facilitates mixing and shredding and fills the delivery wagons, or stored in a mixing station. Here, mechanical systems load them into auger-equipped wagons that mix the TMR before proceeding with the ration distribution.
  • Stage III: the TMR preparation is fully automated. The AFS autonomously provides load mixing–distributing wagons with each ration component directly from bunker silos without human intervention.
Moreover, AFSs differ not only by the level of automation achieved but also by the feed delivery unit’s construction characteristics, making them suitable for the various specific housing conditions retrievable on the farm (Figure 1).
Figure 1. Models of AFSs on the market (from Haidn, 2014 [25]; modified by CREA).

3. What Farmers Perceive about AFSs

Based on the results of a survey among Italian cattle farmers [26], stage II self-propelled AFSs are more likely to equip bigger livestock-farming units. On the contrary, farmers running smaller livestock units are more prone to opt for stage I rail-suspended model AFSs, where only the chopping–mixing and ration distribution tasks are mechanized (not the mixer filling).
The implementation of robotic feeding in livestock farming is quite a recent innovation. As per Lenain et al. [27], in 2020, the automatic feed-pushing technology in dairy farms was at the stage of early commercial sales. Historically, despite the need for digitalization, agriculture has been slow to react to this; such difficulty in applying innovative technologies (such as those of precision agriculture) relates to the complex decision-making problems farming operators must face, which are ascribable to the multifaceted activity of farming and to the institutional setup farmers operate in [28]. Although the diffusion rate of these robotic solutions in the Italian territory is still low, the farmers’ experience is satisfactory as most would repeat the purchase of an AFS at the same or different stage of development.
As expected from the recent introduction of AFSs, almost 1/3 of the surveyed farmers did not have a robotic technology for TMR cattle rationing; however, their willingness to acquire was relatively high as most of them (75%) would invest between 500 and 1500 euros per head. Such a willingness to invest relates to the desire to improve feeding accuracy and animal welfare, achieve improved production performances, reduce the workload, and introduce more flexibility in working hours, as proven by Grothman et al. [29], Pezzuolo et al. [30], and Abhijeet et al. [31], who considered the adoption of robotic feed pushers.
The reasons for adopting an AFS were corroborated by the study of Kauppinen et al. [32], who highlighted that farmers’ consideration of taking care of their well-being is, on the one hand, weakly but positively linked with animal welfare indicators, but not with increased production.
In the study of Bisaglia et al. [26], the dairy farmers who transitioned to mechanized feeding experienced significant energy savings and increases in milk production, perceiving this as resulting from the increased frequency of ration administration and feed-pushing activity by AFS wagons. Specifically, the surveyed farmers reported over 60% energy savings, a daily increase of 2.50 kgfresh weight of ingested ration per cow, and a daily milk production increase of 2.94 kg per cow. According to farmers’ observations, robotically fed animals tend to spend less time waiting to consume their ration, with an increased frequency of visits to the milking area and resting activity, which benefits bovine feet and limb health, preventing cows from experiencing difficulties in walking, lying down, and standing up [33].

4. Cattle Feeding Precision by Automatic Feeding Systems

4.1. Economic Assessment

Reducing production costs, the difficulty in finding specialized personnel, and the increasing size of herds have driven the development and diffusion of specific automated solutions in the dairy and beef sector. In particular, from a technological point of view, automatic concentrate dispensers and milking robots (AMSs) have been used for several years, while the AFS has entered the market only recently.
Concerning the latter, the reasons for their success among breeders can be explained by (i) the high amount of time spent preparing and distributing the feed ration, (ii) the need to prepare a balanced and quality ration to optimize the cows’ production performance, and (iii) the possibility of feeding the ration more frequently than once/twice a day, to provide animals with fresh feed [34]. Increasing the feeding frequency increases the visits to the feeding trough over 24 h; this leads to longer feeding times and increased dry matter intake, with positive effects on cow health and production [35].
However, the adoption of an AFS results not only in an increased number of animal visits to the feeding trough but also considerably affects the organization of the daily workload, combining the reduction in labor requirements with an improvement in the quality of work if compared to the current technique based on the use of self-propelled or trailed mixing wagons. Bisaglia et al. [36] and Pezzuolo et al. [30] have shown a 50–60% reduction in the time needed to produce the total mixed ration (TMR) by switching from a conventional system consisting of a tractor-coupled mixing wagon to a stage II AFS equipped with a stationary chopping–mixing wagon positioned in the kitchen room and a rail-suspended distributor wagon.

4.2. Animal Welfare

AFSs improve feed administration procedures, animal health, and animal welfare [37][38]. The human–animal relationship benefits livestock; however, there might be working conditions causing it to be even more damaging for the animals [39]. In such situations, using an AFS is potentially beneficial because it reduces the interactions between cattle and the stockperson.
The desirable management of the feed bunk decreases the feeding competition, which results in negative animal interactions (e.g., pushing, head butting). In particular, the frequent passage of wagons suggests to animals that there is continuous availability of feed, inhibiting the aggressiveness of dominant animals and relaxing the submissive ones, with a subsequent increase in animals’ voluntary ingestion over 24 h [38]. Schneider et al. [40] assessed some parameters of fattening bulls fed with an AFS (e.g., body condition score, individual behavioral observations, and carcass weights), pointing out the significance of providing animals with a TMR six times in 24 h.
Assessing cattle behavior involves observing several activities at different moments of the day (e.g., when resting in cubicles, milking parlor, and watering places). Concerning the feeding stage specifically, Brito et al. [38] recognized a dual role of the AFSs: firstly, the AFSs improve dairy cattle welfare; secondly, the AFSs can also record many animal behaviors according to Foris et al. [41], who found the AFSs helpful to assess the dominance relationship in dairy cattle.
To ensure adequate access to the feed and to prevent the animals from competing with each other, guaranteeing a desirable ratio between herd size and the feed bunk length is also fundamental. In addition, an optimal feed bunk per head is strategic to ensure a good animal welfare standard. However, the kind of feed bunk, the type of feeding, the feed distribution system, and the feed management are among the factors that, in turn, affect the optimal number of available places [42].
Currently, there are two types of feed bunks: (i) those with delimited places, equipped with self-capture systems (either with or without anti-suffocation systems), and (ii) those with two horizontal tubes, commonly used for fattening cattle. The first one, albeit of simple technology, allows routine operations on dairy cows and, therefore, requires the number of available feed bunks to match the number of housed animals [43]. Lactating cows, characterized by a longer productive life, require careful attention and feeding, which the single manger ensures. On the other hand, the shorter housing of fattening cattle does not require obligatory spaces in the feed bunk as treatments on a single fattening animal do not occur frequently. According to our best knowledge, on the one hand, AFSs are rarely used in beef systems, despite their technology meeting the needs of fattening cattle farms; on the other, their occurrence in dairy cattle farms is becoming quite widespread, although not ubiquitous [28].
Concerning feeding administration, in the case of simultaneous feeding, the number of optimum places should match 100% of the animals because all of them go to the feed bunk simultaneously at the time of distribution. It lowers to 70% of the reared animals in the case of continuous feeding because the barn’s design considers the presence of a feeder that makes the feed available 18 h per day, causing animals to alternate to access the feed bunk.
The feed distribution system and management play a crucial role as feeding is a predominant behavior in dairy cattle; dairy cows spend 3 to 5 h day−1 feeding, consuming 9 to 14 meals daily [44]. Traditionally, housed dairy cows are provided with fresh feed twice or only once daily, mechanically. In this case, animals receive small quantities of fresh feed several times daily. Distributing feed in several daily meals limits competition at the feed bunk and improves the digestive function of each head [45], confirming the findings of Robles et al. [46], who highlighted that a high feeding frequency improves the ruminal condition and the digestive performances [46].
Effectively and carefully managing the feed at the feed bunk is a principal issue. Dairy cows tend to discard/sort feed in search of the most palatable ingredients, pushing it away from the feeder [18]. For this reason, it is necessary to push it closer again. When performed automatically by feed-pusher-type robotic units, the increase in the daily feed approach has been associated with increased milk yield [47]. Studying farms equipped with automatic milking systems, Siewert et al. [48], Deming et al. [49], and King et al. [50] highlighted the benefits of increased feed-pushing frequency, which resulted from improved feed access, decreased sorting, and less time spent searching for feed and increased time spent lying down, which all have positive effects on milk yield.

5. Conclusions

AFSs represent the evolution of the TMR preparation technology with subsequent advantages regarding workload, animal nutrition, and animal welfare optimization. The market offers farmers quite a wide choice of machinery that can adapt to the animals’ needs and the constraints resulting from the farming site’s peculiarities.
In particular, the chosen feeding system should fully match the farm’s needs, being able to cope with the needs of the various groups of animals (all must receive the same amount of feed; the system components should guarantee adequate autonomy) and the operators’ needs (suitable loading and unloading solutions; provision of an alternative feeding method in case of equipment failure).
Concerning the cow shed, the AFS arrangement should match the farm work cycles, and its placement (external, eaves side, or gable side development) should consider the path the wagons follow and the need for protection that the kitchen room requires to prevent TMR components from deterioration. Already in the planning phase, the paving of the barn needs accurate consideration. Whether newly built or not, the paving of the shed must have an appropriate design (suitable slope, smooth surface, silage effluent, and cleaning water draining systems). The building structure (particularly its load-bearing capacity) and the feed alley width should match the characteristics of the AFS to achieve maximum efficiency from the machine.
AFSs are easy to use, making them fundamental for the involvement of younger generations in animal farming and increasing the inclusivity of such an activity with the subsequent fostering of female entrepreneurship. However, there are also some warnings: running an AFS does not free farmers from complying with good feeding procedures because the ingredients’ quality and the management’s appropriateness affect the feed quality and animal production (Figure 2). Healthy animals fed balanced diets and provided with abundant supplies of fresh water are the most productive, the most profitable to the farmer, and the most efficient users of nutrients.
Figure 2. Result of assessing AFS position (SWOT analysis) at the current diffusion stage.

References

  1. Hansen, B.G.; Bugge, C.T.; Skibrek, P.K. Automatic Milking Systems and Farmer Wellbeing–Exploring the Effects of Automation and Digitalization in Dairy Farming. J. Rural. Stud. 2020, 80, 469–480.
  2. Lovarelli, D.; Bacenetti, J.; Guarino, M. A Review on Dairy Cattle Farming: Is Precision Livestock Farming the Compromise for an Environmental, Economic and Social Sustainable Production? J. Clean. Prod. 2020, 262, 121409.
  3. Bragaglio, A.; Romano, E.; Brambilla, M.; Bisaglia, C.; Lazzari, A.; Giovinazzo, S.; Cutini, M. A Comparison between Two Specialized Dairy Cattle Farms in the Upper Po Valley. Precision Agriculture as a Strategy to Improve Sustainability. Clean. Environ. Syst. 2023, 11, 100146.
  4. Rodrigues, A.R.F.; Maia, M.R.G.; Miranda, C.; Cabrita, A.R.J.; Fonseca, A.J.M.; Pereira, J.L.S.; Trindade, H. Ammonia and Greenhouse Emissions from Cow’s Excreta Are Affected by Feeding System, Stage of Lactation and Sampling Time. J. Environ. Manag. 2022, 320, 115882.
  5. Harshbarger, K.E. Self-Feeding a Ground Hay and Grain Ration to Dairy Cows. J. Dairy Sci. 1952, 35, 501.
  6. Schingoethe, D.J. A 100-Year Review: Total Mixed Ration Feeding of Dairy Cows. J. Dairy Sci. 2017, 100, 10143–10150.
  7. McCoy, G.C.; Thurmon, H.S.; Olson, H.H.; Reed, A. Complete Feed Rations for Lactating Dairy Cows. J. Dairy Sci. 1966, 49, 1058–1063.
  8. Vegricht, J.; Miláček, P.; Ambrož, P.; Machálek, A. Parametric Analysis of the Properties of Selected Mixing Feeding Wagons. Res. Agric. Eng. 2007, 53, 85–93.
  9. DeVries, T.J.; von Keyserlingk, M.A.G.; Beauchemin, K.A. Frequency of Feed Delivery Affects the Behavior of Lactating Dairy Cows. J. Dairy Sci. 2005, 88, 3553–3562.
  10. Mäntysaari, P.; Khalili, H.; Sariola, J. Effect of Feeding Frequency of a Total Mixed Ration on the Performance of High-Yielding Dairy Cows. J. Dairy Sci. 2006, 89, 4312–4320.
  11. Mikhailichenko, S.M. Feeding System for Cattle Based on a Wheeled Robotic Feeder. Tract. Agric. Mach. 2023, 90, 83–90.
  12. Kudrna, V. Effect of Different Feeding Frequency Employing Total Mixed Ration (TMR) on Dry Matter Intake and Milk Yield in Dairy Cows during the Winter. Acta Vet. Brno 2003, 72, 533–539.
  13. Gümüș, H.; Bayram, I. The Effects of Physically Effective Neutral Detergent Fibre Content on Growth Performance and Digestibility in Beef Cattle Fed with Total Mixed Ration. Kafkas Univ. Vet. Fak. Derg. 2019, 26, 157–163.
  14. Arzola-Álvarez, C.; Bocanegra-Viezca, J.A.; Murphy, M.R.; Salinas-Chavira, J.; Corral-Luna, A.; Romanos, A.; Ruíz-Barrera, O.; Rodríguez-Muela, C. Particle Size Distribution and Chemical Composition of Total Mixed Rations for Dairy Cattle: Water Addition and Feed Sampling Effects. J. Dairy Sci. 2010, 93, 4180–4188.
  15. Tangorra, F.M.; Agazzi, A.; Perricone, V.; Costa, A. Precision Feeding e Automazione. In Manuale di Nutrizione dei Ruminanti da Latte; Ronchi, B., Savoini, G., Trabalza Marinucci, M., Eds.; Edises Università: Milan, Italy, 2020; pp. 365–374.
  16. Heinrichs, A.J.; Buckmaster, D.R.; Lammers, B.P. Processing, Mixing, and Particle Size Reduction of Forages for Dairy Cattle. J. Anim. Sci. 1999, 77, 180.
  17. Sova, A.D.; LeBlanc, S.J.; McBride, B.W.; DeVries, T.J. Accuracy and Precision of Total Mixed Rations Fed on Commercial Dairy Farms. J. Dairy Sci. 2014, 97, 562–571.
  18. Miller-Cushon, E.K.; DeVries, T.J. Feed Sorting in Dairy Cattle: Causes, Consequences, and Management. J. Dairy Sci. 2017, 100, 4172–4183.
  19. Bisaglia, C.; Brambilla, M.; Cutini, M.; Assirelli, A. Adoption of Automatic Feeding Systems in Bovine Livestock Farms: An On-Farm Survey on Italian Situation. In Proceedings of the European Conference on Agricultural Engineering AgEng2018; Groot Koerkamp, P.W.G., Lokhorst, C., Ipema, A.H., Kempenaar, C., Groenestein, C.M., Van Oostrum, C.G., Ros, N.J., Eds.; Wageningen University and Research: Wageningen, The Netherlands, 2018; pp. 128–133.
  20. Calcante, A. Automatic Systems for Cattle Feeding. Available online: https://www.mondomacchina.it/en/automatic-systems-for-cattle-feeding-c3278 (accessed on 12 May 2023).
  21. Bisaglia, C.; Brambilla, M. Automazione Dell’unifeed: Casi Concreti in Italia (Automation of TMR: Tangible Cases in Italy). Inf. Agrar. 2017, 36, 35–38.
  22. Tangorra, F.M.; Calcante, A. Energy Consumption and Technical-Economic Analysis of an Automatic Feeding System for Dairy Farms: Results from a Field Test. J. Agric. Eng. 2018, 49, 228–232.
  23. Reger, M.T.A.J.; Stumpenhausen, J.; Bernhardt, H. Lidar and Radar Enable the Next Generation of Dairy Cattle Feeding. Appl. Eng. Agric. 2022, 38, 207–217.
  24. Haidn, B.; Leicher, C. Automatisches Füttern—Neues Aus Praxis Und Forschung. In Automatische Grundfuttervorlage für Rinder; Institut für Landtechnik und Tierhaltung, Ed.; Automatische Grundfuttervorlage für Rinder; Bayerische Landesanstalt für Land-wirtschaft: Freising, Germany, 2017; pp. 47–49.
  25. Haidn, B. Automatisches Füttern Bei Milchkühen—Verfahrenstechnik, Arbeitswirtschaft Und Kosten. In Proceedings of the Automatisches Füttern im rinderhaltenden Betrieb. Tagungsband mit den Beiträgen der Referenten zu Verfahrenstechnik und Kosten, dem Fress- und Liegeverhalten von Milchkühen sowie einem Bericht aus der Praxis; Bayerische Landesanstalt für Landwirtschaft: Grub, Germany, 2014; pp. 7–20.
  26. Bisaglia, C.; Lazzari, A.; Giovinazzo, S.; Brambilla, M. Automatic Feeding Systems for Cattle in Italy: State of the Art and Perspectives. In AIIA 2022: Biosystems Engineering Towards the Green Deal. Lecture Notes in Civil Engineering; Ferro, V., Giordano, G., Orlando, S., Vallone, M., Cascone, G., Porto, S.M.C., Eds.; Springer: Cham, Switzerland, 2023; Volume 337, pp. 373–381.
  27. Lenain, R.; Peyrache, J.; Savary, A. Agricultural Robotics: Part of the New Deal? FIRA 2020 Conclusions: With 27 Agricultural Robot Information Sheets; Quae: Versailles, France, 2021; ISBN 9782759233823.
  28. Bucci, G.; Bentivoglio, D.; Finco, A.; Belletti, M. Exploring the Impact of Innovation Adoption in Agriculture: How and Where Precision Agriculture Technologies Can Be Suitable for the Italian Farm System? In Proceedings of the IOP Conference Series: Earth and Environmental Science; Institute of Physics Publishing: Bristol, UK, 2019; Volume 275.
  29. Grothmann, A.; Nydegger, F.; Häußermann, A.; Hartung, E. Automatic Feeding Systems (AFS)-Potential for Optimisation in Dairy Farming How Automatic Feeding Systems Work. Landtechnik 2010, 65, 129–131.
  30. Pezzuolo, A.; Chiumenti, A.; Sartori, L.; Da Borso, F. Automatic Feeding System: Evaluation of Energy Consumption and Labour Requirement in North-East Italy Dairy Farm. In Proceedings of the 15th International Scientific Conference Engineering for Rural Development, Jelgava, Latvia, 25–27 May 2016; pp. 882–887.
  31. Abhijeet, K.; Prasanna, S.B.; Mahesh, P.S.; Gouri, M.D.; Vivek, M.P.; Bhandekar, S.K.; Ali, S.M.; Masood, K.D.; Karan, P. Comparative Study of Automation and Conventional System on Production Performance in Dairy Farms. Asian J. Dairy. Food Res. 2021, 40, 25–29.
  32. Kauppinen, T.; Valros, A.; Vesala, K.M. Attitudes of Dairy Farmers toward Cow Welfare in Relation to Housing, Management and Productivity. Anthrozoos 2013, 26, 405–420.
  33. Cook, N.B.; Nordlund, K.V. The Influence of the Environment on Dairy Cow Behavior, Claw Health and Herd Lameness Dynamics. Vet. J. 2009, 179, 360–369.
  34. Oberschätzl, R.; Bayerische, B.H.; Bayerische, K.R.; Oberschätzl-Kopp, R.; Haidn, B.; Peis, R.; Reiter, K.; Bernhardt, H. Effects of an Automatic Feeding System with Dynamic Feed Delivery Times on the Behaviour of Dairy Cows. In Proceedings of the CIGR-AgEng 2016 Conference, Aarhus, Denmark, 26–29 June 2016; pp. 1–8.
  35. Mattachini, G.; Riva, E.; Pompe, J.C.A.M.; Provolo, G. Automatic Monitoring Cow Behaviour to Assess the Effects of Variations in Feeding Delivery Frequency. In Proceedings of the 7th European Conference on Precision Livestock Farming—Precision Livestock Farming’15, Milan, Italy, 15–18 September 2015; pp. 40–47.
  36. Bisaglia, C.; Belle, Z.; Van Den Berg, G.; Pompe, J.C.A.M. Automatic vs. Conventional Feeding Systems in Robotic Milking Dairy Farms: A Survey in The Netherlands. In Proceedings of the International Conference of Agricultural Engineering CIGRAgEng 2012, Valencia, Spain, 8–12 July 2012; pp. 100–104.
  37. Cornou, C. Automation Systems for Farm Animals: Potential Impacts on the Human—Animal Relationship and on Animal Welfare. Anthrozoos 2009, 22, 213–220.
  38. Brito, L.F.; Oliveira, H.R.; McConn, B.R.; Schinckel, A.P.; Arrazola, A.; Marchant-Forde, J.N.; Johnson, J.S. Large-Scale Phenotyping of Livestock Welfare in Commercial Production Systems: A New Frontier in Animal Breeding. Front. Genet. 2020, 11, 793.
  39. Adler, F.; Christley, R.; Campe, A. Invited Review: Examining Farmers’ Personalities and Attitudes as Possible Risk Factors for Dairy Cattle Health, Welfare, Productivity, and Farm Management: A Systematic Scoping Review. J. Dairy Sci. 2019, 102, 3805–3824.
  40. Schneider, L.; Volkmann, N.; Kemper, N.; Spindler, B. Feeding Behavior of Fattening Bulls Fed Six Times per Day Using an Automatic Feeding System. Front. Vet. Sci. 2020, 7, 43.
  41. Foris, B.; Thompson, A.J.; von Keyserlingk, M.A.G.; Melzer, N.; Weary, D.M. Automatic Detection of Feeding- and Drinking-Related Agonistic Behavior and Dominance in Dairy Cows. J. Dairy Sci. 2019, 102, 9176–9186.
  42. Greter, A.M.; Westerveld, R.S.; Duffield, T.F.; McBride, B.W.; Widowski, T.M.; DeVries, T.J. Short Communication: Effects of Frequency of Feed Delivery and Bunk Space on the Feeding Behavior of Limit-Fed Dairy Heifers. J. Dairy Sci. 2013, 96, 1803–1810.
  43. CRPA—Centro Ricerche Produzioni Animali. Disciplinare per La Valutazione Degli Allevamenti Di Bovini Da Latte (Guidelines for the Assessment of Dairy Cattle Holdings); Gastaldo, A., Magnavacchi, A., Rossi, P., Valli, L., Soffiantini, S., Eds.; Regione Emilia Romagna: Bologna, Italy, 2021.
  44. Grant, R.J.; Albright, J.L. Effect of Animal Grouping on Feeding Behavior and Intake of Dairy Cattle. J. Dairy Sci. 2001, 84, E156–E163.
  45. Sova, A.D.; LeBlanc, S.J.; McBride, B.W.; DeVries, T.J. Associations between Herd-Level Feeding Management Practices, Feed Sorting, and Milk Production in Freestall Dairy Farms. J. Dairy Sci. 2013, 96, 4759–4770.
  46. Robles, V.; González, L.A.; Ferret, A.; Manteca, X.; Calsamiglia, S. Effects of Feeding Frequency on Intake, Ruminal Fermentation, and Feeding Behavior in Heifers Fed High-Concentrate Diets1. J. Anim. Sci. 2007, 85, 2538–2547.
  47. Matson, R.D.; King, M.T.M.; Duffield, T.F.; Santschi, D.E.; Orsel, K.; Pajor, E.A.; Penner, G.B.; Mutsvangwa, T.; DeVries, T.J. Benchmarking of Farms with Automated Milking Systems in Canada and Associations with Milk Production and Quality. J. Dairy Sci. 2021, 104, 7971–7983.
  48. Siewert, J.M.; Salfer, J.A.; Endres, M.I. Factors Associated with Productivity on Automatic Milking System Dairy Farms in the Upper Midwest United States. J. Dairy Sci. 2018, 101, 8327–8334.
  49. Deming, J.A.; Bergeron, R.; Leslie, K.E.; DeVries, T.J. Associations of Housing, Management, Milking Activity, and Standing and Lying Behavior of Dairy Cows Milked in Automatic Systems. J. Dairy Sci. 2013, 96, 344–351.
  50. King, M.T.M.; Crossley, R.E.; DeVries, T.J. Impact of Timing of Feed Delivery on the Behavior and Productivity of Dairy Cows. J. Dairy Sci. 2016, 99, 1471–1482.
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