A review of precision technologies in pasture-based dairying systems
Open accessAbstract
The promised benefits of precision technologies (PTs) include improved efficiency, quality, animal health and welfare and reduced environmental impacts. To date, PTs (including sensors, algorithms, big data, decision-support tools, etc.) have had a relatively modest impact in pasture-based dairying systems in comparison with other agricultural sectors such as arable production. The areas animals roam and graze in pasture-based systems and the associated connectivity challenges may, in part at least, explain the comparatively reduced use of PTs in those systems. Thus, there are very few technologies designed specifically to increase pasture utilisation with the exception of global positioning systems (GPS) and Bluetooth-enabled Plate Meters. Terrestrial and satellite-based spectral analysis of pasture biomass and quality is still in the development phase. Therefore, one of the key drivers of efficiency in pasture-based systems has only been marginally impacted by PTs. In contrast, technological development in the area of fertility and heat detection has been important and offers significant potential value to dairy farmers. In general PTs can be described as good at measurement, data collection and storage but fall down around interpretation and providing useful outputs to end users. As a result, it is unclear if farm management is being sufficiently improved to justify widespread adoption of PTs. A needs-driven development of PTs and decision-support tools are required for the succesful integration within agriculture. Further cost/benefit analysis is also required to determine the efficiency of investing in PTs and what, if any, factors affect the variation in the returns.
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The general consensus in Irish studies is that adoption rates of practices in grassland management and reproductive performance are relatively low, notably due to information constraints.
“To date, the general consensus in Irish studies is that adoption rates of practices in the areas of grassland management and reproductive performance are relatively low, notably due to information constraints (Hyland et al., 2018;Regan et al., 2021;Shalloo et al., 2021Shalloo et al., , 2018)).”
From Extension and management pathways for enhanced farm sustainability: evidence from Irish dairy farms (2023) · cites this paper as Shalloo et al., 2021
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“While the drivers of good returns from technology investment are relatively unknown, there is a wealth of literature on the motivations of farmers to invest in a technology or adopt specific management practices (Garforth et al., 2006; Rehman et al., 2007; Garforth, 2010; Jones et al., 2016).”
BackgroundShortall, J. G., Shalloo, L., Foley, C., Sleator, R. D., & O’Brien, B. (2016) · Journal of Dairy Science · doi:10.3168/jds.2016-11256 · Cited by 40 · see citing works
Ungar, E. D., Nevo, Y., Baram, H., & Arieli, A. (2017) · Journal of Neuroscience Methods · doi:10.1016/j.jneumeth.2017.06.001 · Cited by 40 · see citing works
The economics of reseeding on a dairy farm
Shalloo, L., Creighton, P., & O’Donovan, M. (2011) · Arrow@dit (Dublin Institute of Technology) · Cited by 38 · see citing works
The emergence, development and effectiveness of decision rules for pasture based dairy systems
MacDonald, K., Glassey, C. B., & Rawnsley, R. (2010) · eCite Digital Repository (University of Tasmania) · Cited by 37 · see citing works
An analysis of the factors associated with technical and scale efficiency of Irish dairy farms
Kelly, E., Shalloo, L., Geary, U., Kinsella, A., Thorne, F. S., & Wallace, M. (2013) · International Journal of Agricultural Management · doi:10.5836/ijam/2013-03-04 · Cited by 34 · cited 9× · see citing works
“Dairy cattle breeding objectives combining yield, survival and calving interval for pasture-based systems in Ireland under different milk quota scenarios.”
BackgroundInfluentialBewley, J. M., Boehlje, Gray, A. W., Hogeveen, H., Kenyon, S. J., Eicher, S. D., & Schutz, M. M. (2010) · Agricultural Finance Review · doi:10.1108/00021461011042675 · Cited by 31 · cited 2× · see citing works
“More generally, as it is difficult for farmers and researchers alike to discern good and poor investments, cost/benefit analysis of novel technologies is required, in particular, on the areas with greatest potential financial impact (Bewley et al., 2010).”
BackgroundRutten, C. J., Steeneveld, W., Vernooij, J. C. M., Huijps, K., Nielen, M., & Hogeveen, H. (2016) · Journal of Dairy Science · doi:10.3168/jds.2016-10935 · Cited by 31 · cited 1× · see citing works
“Several DSS have been developed around reproductive management on dairy farms (Giordano et al., 2011; Rutten et al., 2016), and some have focussed on pasture-based production systems (Beukes et al.”
BackgroundBeukes, P. C., Burke, C. R., Levy, G., & Tiddy, R. M. (2010) · Animal Reproduction Science · doi:10.1016/j.anireprosci.2010.04.191 · Cited by 29 · cited 1× · see citing works
“, 2016), and some have focussed on pasture-based production systems (Beukes et al., 2010; Fenlon et al., 2017).”
BackgroundEvaluation of an activity and rumination monitor in dairy cattle grazing two types of forages
Molfino, J., Clark, C., Kerrisk, K. L., & Garcia, S. C. (2017) · Animal Production Science · doi:10.1071/an16514 · Cited by 29 · see citing works
Geary, U., Lopez-Villalobos, N., O’Brien, B., Garrick, D. J., & Shalloo, L. (2014) · Journal of Dairy Research · doi:10.1017/s0022029914000053 · Cited by 23 · cited 1× · see citing works
“The data is generally entered manually by the farmer or the advisor and they do not rely on precision agriculture or big data (Geary et al., 2014).”
MethodAli, I., Barrett, B., Cawkwell, F., Green, S., Dwyer, E., & Neumann, M. (2017) · IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing · doi:10.1109/jstars.2017.2679761 · Cited by 23 · see citing works
Fenlon, C., O’Grady, L., Doherty, M. L., Dunnion, J., Shalloo, L., & Butler, S. T. (2017) · Journal of Dairy Science · doi:10.3168/jds.2016-11830 · Cited by 17 · cited 1× · see citing works
“, 2016), and some have focussed on pasture-based production systems (Beukes et al., 2010; Fenlon et al., 2017).”
BackgroundMOTIVATING FARMERS: INSIGHTS FROM SOCIAL PSYCHOLOGY
Garforth, C. (2010) · Cited by 16 · see citing works
Assessing individual activity levels in two broiler lines using an ultra-wideband tracking system
van der Sluis, M., de Klerk, B., Ellen, E. D., de Haas, Y., Hijink, T., & Rodenburg, T. B. (2019) · Utrecht University Repository (Utrecht University) · doi:10.3965/j.ijabe.20120503.00 · Cited by 13 · see citing works
McSweeney, D., Foley, C. P., Halton, P., & O’Brien, B. (2015) · Grassland and forages in high output dairy farming systems. Proceedings of the 18th Symposium of the European Grassland Federation, Wageningen, The Netherlands, 15-17 June 2015 · Cited by 7 · see citing works
Wagner-Storch, A. M., & Palmer, R. W. (2002) · The Professional Animal Scientist · doi:10.15232/s1080-7446(15)31542-4 · Cited by 3 · cited 1× · see citing works
“Another example includes automated cow drafting systems using integrated information to autonomously separate cows that need specific attention and which adds significant value to many other sensors installed on farms (Wagner-Storch & Palmer, 2002).”
BackgroundMeasuring progesterone from the milk line
Dobson, H. (2016) · Veterinary Record · doi:10.1136/vr.i1453 · Cited by 3 · cited 1× · see citing works
“The system is able to measure lactate dehydrogenase for detection of (subclinical) mastitis, milk urea to assess the efficiency of protein feed rations and β-hydroxybutyrate to indicate (subclinical) ketosis and/or secondary metabolic disorders (Dobson, 2016).”
BackgroundFarmer attitudes predictive of profitabilityPreprint
O’Leary, N., Tranter, R., & Bennett, R. (2017) · RePEc: Research Papers in Economics · doi:10.22004/ag.econ.258638 · Cited by 3 · see citing works
Why not investing in sensors is logical for dairy farmers
Steeneveld, W., Rutten, C. J., Lansink, A. O., & Hogeveen, H. (2017) · Socio-Environmental Systems Modeling · Cited by 3 · see citing works
Establishing a health monitoring system for cattle in Austria
Egger-Danner, C., Fuerst‐Waltl, B., Holzhacker, W., Janacek, R., Lederer, J., Miesenberger, M., Obritzhauser, W., & Winkler, M. (2007) · Wageningen Academic Publishers eBooks · doi:10.3920/9789086865932_050 · Cited by 3 · see citing works
Flagged first, then by citations
1 of the 89 references couldn’t be matched to a known paper.
Research works printed but not linked: 3
- Finneran, E., Crosson, P., Wallace, M., O'Kiely, P., Forristal, P.D. and Shalloo, L. 2010 Simulation modelling of the cost of production and utilizing feeds for ruminants on Irish farms. Journal of Farm Management 14: 95-116.
- O'Leary, N., Tranter, R. and Bennett, R. 2017b. Farmer Personality and Farm Profitability. Proceedings of the International Farm Management Association Congress 21, Edinburgh, pages 1-17.
- Shalloo, L., O'Donnell, S. and Horan, B. 2007. Profitable dairying in an increased EU milk quota scenario. In: Exploiting the Freedom to Milk. Proceedings of the National Dairy Conference, Lyrath Hotel Kilkenny, Breaffy House Hotel Castlebar, 21-22-Nov-2007, pages 20-44. Available online: https://www.teagasc.ie/media/website/ publications/2007/53_NationalDairyConf2007.pdf.
Cited by
Sorted by citations
Riaboff, L., Shalloo, L., Smeaton, A. F., Couvreur, S., Madouasse, A., & Keane, M. T. (2021) · Computers and Electronics in Agriculture · doi:10.1016/j.compag.2021.106610 · Cited by 192 · see citing works
Palma-Molina, P., Hennessy, T., O’Connor, A. H., Onakuse, S., O’Leary, N., Moran, B., & Shalloo, L. (2023) · Journal of Dairy Science · doi:10.3168/jds.2021-21503 · Cited by 57 · see citing works
Integrating Artificial Intelligence in dairy farm management − biometric facial recognition for cows
Mahato, S., & Neethirajan, S. R. (2024) · Information Processing in Agriculture · doi:10.1016/j.inpa.2024.10.001 · Cited by 38 · see citing works
Lussem, U., Bolten, A., Kleppert, I., Jasper, J., Gnyp, M. L., Schellberg, J., & Bareth, G. (2022) · Remote Sensing · doi:10.3390/rs14133066 · Cited by 36 · see citing works
Extension and management pathways for enhanced farm sustainability: evidence from Irish dairy farms
Balaine, L., Läpple, D., Dillon, E. J., & Buckley, C. (2023) · European Review of Agricultural Economics · doi:10.1093/erae/jbac033 · Cited by 18 · see citing works
Kenny, E. M., Ruelle, E., Keane, M. T., & Shalloo, L. (2024) · Computers and Electronics in Agriculture · doi:10.1016/j.compag.2024.108805 · Cited by 14 · see citing works
Leddin, C. M., Morse-McNabb, E. M., Smith, K. F., Ho, C. K. M., & Jacobs, J. L. (2023) · Agricultural Systems · doi:10.1016/j.agsy.2023.103755 · Cited by 11 · see citing works
Measuring Herbage Mass: A Review
Susruthan, V., Donaghy, D. J., Kenyon, P. R., Sneddon, N., & Cartmill, A. D. (2025) · Agronomy · doi:10.3390/agronomy15102264 · Cited by 10 · see citing works
Palma-Molina, P., Hennessy, T., Dillon, E., Onakuse, S., Moran, B., & Shalloo, L. (2023) · Journal of Dairy Science · doi:10.3168/jds.2022-23111 · Cited by 9 · see citing works
Berdos, J. I., Ncho, C. M., Son, A.-R., Lee, S., & Kim, S.-H. (2023) · Sustainability · doi:10.3390/su152014988 · Cited by 8 · see citing works
Calculating the matrix profile from noisy data
Hehir, C., & Smeaton, A. F. (2023) · PLoS ONE · doi:10.1371/journal.pone.0286763 · Cited by 5 · see citing works
“Improving efficiency in the area of animal management and livestock welfare has resulted in the emergence and use of precision agriculture technologies [31].”
Optimisation of livestock routing on farms
Corcoran, P., & Lewis, R. (2024) · Computers & Industrial Engineering · doi:10.1016/j.cie.2024.109882 · Cited by 3 · see citing works
Identification of the Best Accelerometer Features and Time-Scale to Detect Disturbances in Calves
Dissanayake, O. I., Mcpherson, S. E., Kennedy, E., Sugrue, K., Conneely, M., Shalloo, L., Cunningham, P., & Riaboff, L. (2023) · Lecture notes in computer science · doi:10.1007/978-3-031-24378-3_11 · Cited by 2 · see citing works
Prediction of Behavioral Movement of Cattle Using Accelerometer and Gyro Sensors
Majumdar, S., Ghosh, D., Layek, S., Ray, H., Ghosh, A., & Sinha, A. K. (2023) · International Conference on Emerging Frontiers in Electrical and Electronic Technologies (ICEFEET) · doi:10.1109/icefeet59656.2023.10452242 · Cited by 2 · see citing works
Verdon, M., & Beggs, D. S. (2024) · Animal Production Science · doi:10.1071/an23385 · Cited by 3 · see citing works
Nickmilder, C., Tedde, A., Dufrasne, I., Lessire, F., Glesner, N., Tychon, B., Bindelle, J., & Soyeurt, H. (2023) · Remote Sensing · doi:10.3390/rs15071890 · Cited by 2 · see citing works
Precíziós technológiák alkalmazása a gyepgazdálkodásban
Kiss, T. (2024) · Gradus · doi:10.47833/2024.1.agr.002
“Emellett létfontosságú annak biztosítása, hogy a szabályozás összhangban álljon a fenntarthatósági célokkal [19].”
Towards Secure Semantic Interoperability in Dairy Farming Systems
Rajput, Q., Breslin, J. G., & Asghar, M. N. (2025) · Cyber Research Conference - Ireland (Cyber-RCI) · doi:10.1109/cyber-rci68134.2025.11384807
“It is essential to have a comprehensive set of ontologies to cover a broader range of concepts and properties specific to applications needed in the dairy farm system of systems, including soils, fertilisers, pasture [21], livestock, and milking systems.”
Developing a methodology to identify personalities in farmed red deer
Thompson, B. R., Stevens, D. R., Gordon, I. J., Maxwell, T. M. R., Zydenbos, S. M., Dodds, K. G., Triadis, D., & Gregorini, P. (2026) · Applied Animal Behaviour Science · doi:10.1016/j.applanim.2026.107011
Parce, L., Palma-Molina, P., & Loughrey, J. (2026) · Frontiers in Animal Science · doi:10.3389/fanim.2026.1896469
- Authors
- Shalloo, L., Byrne, T., Leso, L., Ruelle, E., Starsmore, K., Geoghegan, A., Werner, J., & O’Leary, N.
- Affiliations
- Teagasc - The Irish Agriculture and Food Development Authority (IE)
- University of Hohenheim (DE)
- Venue
- Irish Journal of Agricultural and Food Research
- Publisher
- Compuscript, Ltd.
- Published
- 2021
- Volume
- 59
- Issue
- 2
- ISSN
- 0791-6833 (ISSN-L)
- 2009-9029
- OpenAlex
- W3128066367
- Cited by
- 20
- References
- 89
- Citations by year
- 2026: 2 · 2025: 2 · 2024: 5 · 2023: 8 · 2022: 2 · 2021: 1
- FWCI
- 2.40
- Type
- journal article
- Language
- en
- Open access
- diamond
- doi.org
- Licence
- Locations
- Irish Journal of Agricultural and Food Research (publishedVersion, cc-by-nc-nd)
- DOAJ (DOAJ: Directory of Open Access Journals) (submittedVersion)
- Nova Science Publishers (Nova Science Publishers, Inc.) (submittedVersion, other-oa)
- T-Stór (Teagasc) (submittedVersion, cc-by-nc-sa)
- Funders
- Science Foundation Ireland (13/IA/1977, 16/RC/3835)
- Topics
- Life Sciences › Agricultural and Biological Sciences › Plant Science › Smart Agriculture and AI
- Life Sciences › Agricultural and Biological Sciences › Forestry › Pasture and Agricultural Systems
- Physical Sciences › Engineering › Mechanical Engineering › Agricultural Engineering and Mechanization
- Keywords
- precision technology, dairy farming, pasture use, decision support system, estrus detection, GPS, spectral analysis, technology adoption, farm management, cost-benefit analysis
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