Drivers and barriers of digitalisation in Hungarian pasture-based beef cattle farming
DOI:
https://doi.org/10.17205/aweth.7196Kulcsszavak:
PLF, digitalisation, agroecology, beef cattleAbsztrakt
This study, conducted within the HORIZON Europe PATH2DEA project, examined the drivers, barriers, trends, and risks of digitalisation in pasture-based beef cattle farming in Hungary, with a focus on its potential to support agroecological practices and Precision Livestock Farming (PLF) approaches. Two stakeholder workshops were held. Workshop 1 mapped current digital tool usage and identified transparency, decision support, and efficiency as main adoption drivers, while highlighting barriers such as vulnerability to suppliers, limited network access, and high costs. Workshop 2 focused on functional gaps at farm and supply chain levels, revealing needs for more reliable sensor technologies, improved interoperability, and streamlined administration. Stakeholder views on the agroecological benefits of digitalisation varied, reflecting differences in context and priorities. The findings provide a concise evidence base for developing integrated, context-specific digital solutions to support sustainable livestock production.
Hivatkozások
Altieri, M.A., Toledo, V.M. (2011): The agroecological revolution in Latin America: rescuing nature, ensuring food sovereignty and empowering peasants. Journal of Peasant Studies, 38(3), 587–612. https://doi.org/10.1080/03066150.2011.582947
Aquilani, C., Confessore, A., Bozzi, R., Sirtori, F., Pugliese, C. (2022): Precision Livestock Farming technologies in pasture-based livestock systems. Animal, 16(1), 100429. https://doi.org/10.1016/j.animal.2021.100429
Bellon-Maurel, V., Lutton, E., Bisquert, P., Brossard, L., Chambaron-Ginhac, S., Labarthe, P., Lagacherie, P., Martignac, F., Molenat, J., Parisey, N., Picault, S., Piot-Lepetit, I., Veissier, I. (2022): Digital revolution for the agroecological transition of food systems: A responsible research and innovation perspective. Agricultural Systems, 203, 103524. https://doi.org/10.1016/j.agsy.2022.103524
Berckmans, D. (2017): General introduction to precision livestock farming. Animal Frontiers, 7(1), 6–11. https://doi.org/10.2527/af.2017.0102
Ditzler, L., Driessen, C. (2022): Automating agroecology: How to design a farming robot without a monocultural mindset? Journal of Agricultural and Environmental Ethics, 35(1), 2. https://doi.org/10.1007/s10806-021-09876-x
Finger, R., Swinton, S.M., El Benni, N., Walter, A. (2019): Precision farming at the nexus of agricultural production and the environment. Annual Review of Resource Economics, 11(1), 313–335. https://doi.org/10.1146/annurev-resource-100518-093929
Giagnocavo, C., Duque-Acevedo, M., Terán-Yépez, E., Herforth-Rahmé, J., Defossez, E., Carlesi, S., Delalieux, S., Gkisakis, V., Márton, A., Molina-Delgado, D., Moreno, J.C., Ramirez-Santos, A.G., Reinmuth, E., Sánchez, G., Soto, I., Van Nieuwenhove, T., Volpi, I. (2025): A multi-stakeholder perspective on the use of digital technologies in European organic and agroecological farming systems. Technology in Society, 81, 102763. https://doi.org/10.1016/j.techsoc.2024.102763
Gliessman, S.R. (2007): Agroecology: the ecology of sustainable food systems. 2nd edition. Boca Raton, USA, CRC Press. 384 pp.
Hopster, H.R.M.B., Bruckmaier, R.M., Van der Werf, J.T.N., Korte, S.M., Macuhova, J., Korte-Bouws, G., Van Reenen, C.G. (2002): Stress responses during milking; comparing conventional and automatic milking in primiparous dairy cows. Journal of Dairy Science, 85(12), 3206–3216. https://doi.org/10.3168/jds.S0022-0302(02)74409-3
Jacobs, J.A., Siegford, J.M. (2012): Invited review: The impact of automatic milking systems on dairy cow management, behavior, health, and welfare. Journal of Dairy Science, 95(5), 2227–2247. https://doi.org/10.3168/jds.2011-4943
Kerr, R.B., Madsen, S., Stüber, M., Liebert, J., Enloe, S., Borghino, N., Parros, P., Mutyambai, D.M., Prudhon, M., Wezel, A. (2021): Can agroecology improve food security and nutrition? A review. Global Food Security, 29, 100540. https://doi.org/10.1016/j.gfs.2021.100540
Klerkx, L., Begemann, S. (2020): Supporting food systems transformation: The what, why, who, where and how of mission-oriented agricultural innovation systems. Agricultural Systems, 184, 102901. https://doi.org/10.1016/j.agsy.2020.102901
Marchegiani, S., Gislon, G., Marino, R., Caroprese, M., Albenzio, M., Pinchak, W.E., Carstens, G.E., Ledda, L., Trombetta, M.F., Sandrucci, A., Pasquini, M., Deligios, P.A., Ceccobelli, S. (2025): Smart technologies for sustainable pasture-based ruminant systems: A review. Smart Agricultural Technology, 100789. https://doi.org/10.1016/j.atech.2025.100789
Neethirajan, S. (2023): Artificial intelligence and sensor technologies in dairy livestock export: charting a digital transformation. Sensors, 23(16), 7045. https://doi.org/10.3390/s23167045
Norton, T., Chen, C., Larsen, M. L. V., Berckmans, D. (2019): Precision livestock farming: Building ‘digital representations’ to bring the animals closer to the farmer. Animal, 13(12), 3009–3017. https://doi.org/10.1017/S175173111900199X
PATH2DEA (2023): Paving the Way towards Digitalisation Enabling Agroecology for European Farming Systems. https://www.path2dea.eu/ (accessed on 19. 08. 2025.)
Petraki, D., Gazoulis, I., Kokkini, M., Danaskos, M., Kanatas, P., Rekkas, A., Travlos, I. (2025): Digital Tools and Decision Support Systems in Agroecology: Benefits, Challenges, and Practical Implementations. Agronomy, 15(1). https://doi.org/10.3390/agronomy15010236
Sharma, B., Koundal, D. (2018): Cattle health monitoring system using wireless sensor network: a survey from innovation perspective. IET Wireless Sensor Systems, 8(4), 143–151. https://doi.org/10.1049/iet-wss.2017.0060
Vikas, Ranjan, R. (2024): Agroecological approaches to sustainable development. Frontiers in Sustainable Food Systems, 8, 1405409. https://doi.org/10.3389/fsufs.2024.1405409
Wezel, A., Bellon, S., Doré, T., Francis, C., Vallod, D., David, C. (2009): Agroecology as a science, a movement and a practice. A review. Agronomy for Sustainable Development, 29, 503–515. https://doi.org/10.1051/agro/2009004
Wolfert, S., Ge, L., Verdouw, C., Bogaardt, M.J. (2017): Big data in smart farming–a review. Agricultural Systems, 153, 69–80. https://doi.org/10.1016/j.agsy.2017.01.023
Yang, Q., Du, X., Wang, Z., Meng, Z., Ma, Z., Zhang, Q. (2023): A review of core agricultural robot technologies for crop productions. Computers and Electronics in Agriculture, 206, 107701. https://doi.org/10.1016/j.compag.2023.107701
Yépez-Ponce, D.F., Salcedo, J.V., Rosero-Montalvo, P.D., Sanchis, J. (2023): Mobile robotics in smart farming: current trends and applications. Frontiers in Artificial Intelligence, 6, 1213330. https://doi.org/10.3389/frai.2023.1213330
Zhang, C., Kovacs, J.M. (2012): The application of small unmanned aerial systems for precision agriculture: a review. Precision Agriculture, 13, 693–712. https://doi.org/10.1007/s11119-012-9274-5
Letöltések
Megjelent
Folyóirat szám
Rovat
License
Copyright (c) 2025 Miklós Biszkup, Petra Balogh, Éva Stibinger, Valéria Csonka, Dániel Bori, Dóra Drexler, Aliz Márton

This work is licensed under a Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License.
A folyóirat a nyílt hozzáférés elvei szerint működik, cikkeire ugyanakkor a Creative Commons 4.0 standard licenc alábbi típusa vonatkozik: CC-BY-NC-ND-4.0. Ennek értelmében a mű szabadon másolható, terjeszthető, bemutatható és előadható, azonban nem használható fel kereskedelmi célokra (NC), továbbá nem módosítható és nem készíthető belőle átdolgozás, származékos mű (ND). A licenc alapján a szerző vagy a jogosult által meghatározott módon fel kell tüntetni a szerző nevét és a szerzői mű címét (BY).