Hungarian Farmers and the Adoption of Precision Farming

[1] Adrian, A. M., Norwood, S. H. & Mask, P. L. (2005). Producers’ perceptions and attitudes toward precision agriculture technologies. Computers and Electronics in Agriculture 48(3), 256–271. DOI: 10.1016/j.compag.2005.04.004. Search in Google Scholar

[2] Ajzen, I. (1991). The theory of planned behavior. Organizational Behavior and Human Decision Process 50(2), 179–211. DOI: 10.1016/0749-5978(91)90020-T. Search in Google Scholar

[3] Aubert, B. A., Schroeder, A. & Grimaudo, J. (2012). IT as enabler of sustainable farming: An empirical analysis of farmers’ adoption decision of precision agriculture technology. Decision Support System 54(1), 510–520. DOI: 10.1016/j.dss.2012.07.002. Search in Google Scholar

[4] Bai, A., Kovách, I., Czibere, I., Megyesi, B. & Balogh, P. (2022). Examining the Adoption of Drones and Categorisation of Precision Elements among Hungarian Precision Farmers Using a Trans-Theoretical Model Drones 6(8), Article ID. DOI: 10.3390/drones6080200. Search in Google Scholar

[5] Balogh, P., Bujdos, Á., Czibere, I., Fodor, L., Gabnai, Z., Kovách, I., Nagy, J. & Bai, A. (2020). Main Motivational Factors of Farmers Adopting Precision Farming in Hungary. Agronomy, 10(4), Article ID 610. DOI: 10.3390/agronomy10040610. Search in Google Scholar

[6] Balogh, P., Bai, A., Czibere, I., Kovách, I., Fodor, L., Bujdos, Á., Sulyok, D., Gabnai. Z. & Birkner, Z. (2021). Economic and Social Barriers of Precision Farming in Hungary. Agronomy 11(6), Article ID 112. DOI: 10.3390/agronomy11061112. Search in Google Scholar

[7] Barnes, A., De Soto, I., Eory, V., Beck, B., Balafoutis, A., Sánchez, B., Vangeyte, J., Fountas, S., van der Wal, T. & Gómez-Barbero, M. (2019). Influencing factors and incentives on the intention to adopt precision agricultural technologies within arable farming systems. Environmental Science and Policy 93, 66–74. DOI: 10.1016/j.envsci.2018.12.014. Search in Google Scholar

[8] Charatsari, C., Lioutas, E. D. & Koutsouris, A. (2017). Farmers’ motivational orientation toward participation in competence development projects: A self-determination theory perspective. The Journal of Agricultural Education and Extension, 23(2), 105–120. DOI: 10.1080/1389224X.2016.1261717. Search in Google Scholar

[9] Chabot, D., Dillon, C., Shemrock, A., Weissflog, N. & Sager, E. P. (2018). An object-based image analysis workflow for monitoring shallow-water aquatic vegetation in multispectral drone imagery. ISPRS International Journal of Geo-Information 7(8), Article ID 294. DOI: 10.3390/ijgi7080294. Search in Google Scholar

[10] Csurgó, B., Kovách, I. & Megyesi, B. (2018). After a long March: the results of two decades of rural restructuring in Hungary. Eastern European Countryside 24(1), 81–109. DOI: 10.2478/eec-2018-0005. Search in Google Scholar

[11] Drucker, P. (1985). Innovation and Entrepreneurship. New York: Harper and Row Publishers. Search in Google Scholar

[12] Fountas, S., Pedersen, S. M. & Blackmore, S. (2005). ICT in Precision Agriculture – Diffusion of technology. In Gelb, E. & Offer, A., eds., ICT in Agriculture: Perspectives in Technological Innovation. Jerusalem: The Hebrew University. Search in Google Scholar

[13] Gaál, M., Humenyik, N., Illés, I. & Kiss, A.(2020). A precíziós szántóföldi növénytermesztés helyzete és ökonómiai vizsgálata. Budapest: NAIK Agrárgazdasági Kutatóintézet. Search in Google Scholar

[14] Griffin, T. W., Miller, N. J., Bergtold, J., Shanoyan, A., Sharda, A. & Ciampitti, I. A. (2017). Farm’s sequence of adoption of information-intensive precision agricultural technology. Applied Engineering in Agriculture. 33(4), 521–527. DOI: 10.13031/aea.12228. Search in Google Scholar

[15] Hansson, H. & Kokko, S. (2018). Farmers' mental models of change and implications for farm renewal – A case of restoration of a wetland in Sweden. Journal of Rural Studies 60, 141–151. DOI: 10.1016/j.jrurstud.2018.04.006. Search in Google Scholar

[16] Kemény, G., Lámfalusi, I. & Molnár, A. (2017). A precíziós szántóföldi növénytermesztés összehasonlító vizsgálata. Budapest: Agrárgazdasági Kutató Intézet. DOI: 10.7896/ak1703. Search in Google Scholar

[17] Kovách, I., Megyesi, B., Bai, A. & Balogh, P. (2022). Sustainability and agricultural regeneration in the Hungarian agriculture. Sustainability, 14(2), Article ID 969. DOI: 10.3390/su14020969. Search in Google Scholar

[18] Lencsés, E. & Mészáros, K. (2020). Business model innovation with precision farming technology form farmers point of view. Hungarian Agricultural Engineering, 38, 79–84. DOI: 10.17676/HAE.2020.38.79. Search in Google Scholar

[19] Li, W., Clark, B., Taylor, J. A., Kendall, H., Jones, G., Li, Z., Jin, S., Zhao, C., Yang, G., Shuai, C., Cheng, X., Chen, J., Yang, H. & Frewer, L. J. (2020). A hybrid modelling approach to understanding adoption of precision agriculture technologies in Chinese cropping systems. Computers and Electronics in Agriculture, 172, Article ID: 105305. DOI: 10.1016/j.compag.2020.105305. Search in Google Scholar

[20] Lynne, G. D., Franklin Casey, C., Hodges, A., Rahmani, M. (1995). Conservation technology adoption decisions and the theory of planned behavior. Journal of Economic Psychology 16(4), 581–598. DOI: 10.1016/0167-4870(95)00031-6. Search in Google Scholar

[21] Milics, G., Smuk, N., Virág, I. & Neményi, M. (2012). Precision agriculture – technical development for a sustainable agriculture. In: Neményi, M. & Heil, B., eds., The Impact of Urbanization, Industrial and Agricultural Technologies on the Natural Environment: International Scientific Conference on Sustainable Development and Ecological Footprint. (pp. 231–240). Budapest, Nemzeti Tankönyvkiadó; Nyugat-magyarországi Egyetem. ISBN: 978-963-19-7352-5. Search in Google Scholar

[22] Milics, G. (2019). Application of UAVs in Precision Agriculture. In: Palocz-Andresen, M., Szalay, D., Gosztom, A., Sípos, L. & Taligás, T, eds., International Climate Protection (pp. 93–97). Cham: Springer International Publishing. Search in Google Scholar

[23] Milics, G., Igor, M., Magyar, F. & Varga, P. M. (2022). Data-based agriculture in the V4 countries – sustainability, efficiency and safety. Scientia et Securitas 2(4), 491–503. DOI: 10.1556/112.2021.00072. Search in Google Scholar

[24] Morgan, M. & Ess, D. (1997). The Precision-Farming Guide for Agriculturists: The Nuts and Bolts Guide to “Getting up to Speed” Fast and Effectively with This Exciting New Management. Moline, IL: John Deere. Search in Google Scholar

[25] Oláh, J. & Popp, J. (2018). The outlook for precision farming in Hungary. Network Intelligence Studies 6(12), 91–99. Search in Google Scholar

[26] Pino, G., Toma, P., Rizzo, C., Miglietta, P., Peluso, A., Guido, G. (2017). Determinants of farmers’ intention to adopt water saving measures: evidence from Italy. Sustainability 9(1), Article ID 77. DOI: 10.3390/su9010077. Search in Google Scholar

[27] Popp, J., Erdei, E. & Oláh, J. (2018). A precíziós gazdálkodás kilátásai Magyarországon. International Journal of Engineering and Management Sciences, 3(1), 133–147. DOI: 10.21791/IJEMS.2018.1.15. Search in Google Scholar

[28] Regan, A. (2019). ‘Smart farming’ in Ireland: A risk perception study with key governance actors. Wageningen Journal of Life Sciences, 90–91, Article ID 100292. DOI: 10.1016/j.njas.2019.02.003. Search in Google Scholar

[29] Rose, D. C., Sutherland, W. J., Parker, C., Lobley, M., Winter, M., Morris, C., Twining, S., Ffoulkes, C., Amano, T. & Dicks, L.V. (2016). Decision support tools for agriculture: Towards effective design and delivery. Agricultural Systems, 149, 165–174. DOI: 10.1016/j.agsy.2016.09.009. Search in Google Scholar

[30] Shaikh, T. A., Rasool, T. & Lone, F. R. (2022). Towards leveraging the role of machine learning and artificial intelligence in precision agriculture and smart farming. Computers and Electronics in Agriculture, 198(C), Article ID: 107119. DOI: 10.1016/j.compag.2022.107119. Search in Google Scholar

[31] Stræte, E. P., Vik, J., Fuglestad, E. M., Gjefsen, M. D., Melås, A. M. & Søraa, R. A. (2022). Critical support for different stages of innovation in agriculture: What, when, how? Agricultural Systems, 203, Article ID: 103526. DOI: 10.1016/j.agsy.2022.103526. Search in Google Scholar

[32] Takácsné György, K., Lámfalusi, I., Molnár, A., Sulyok, D., Gaál, M., Keményné Horváth, Zs., Domán, Cs., Illés, I., Kiss, A., Péter, K. & Kemény, G. (2018). Precision agriculture in Hungary: assessment of perceptions and accounting records of FADN arable farms. Studies in Agricultural Economics, 120(1), 47–54. DOI: 10.7896/j.1717. Search in Google Scholar

[33] Venkatesh, V. & Davis, F. D. (2000). A theoretical extension of the technology acceptance model: Four longitudinal field studies. Management Science, 46(2), 186–204. DOI: 10.1287/mnsc.46.2.186. Search in Google Scholar

[34] Hadászi, L. (2018). A precíziós eszközök kompatibilitása nélkül elmarad az áttörés. Interjú. Retrieved from https://www.magro.hu/agrarhirek/a-precizios-eszkozok-kompatibilitasa-nelkul-elmarad-azattores/. (Accessed: 2022. 12. 31.) Search in Google Scholar

[35] Jóri, J. I. (2019). A precíziós gazdálkodás gépesítési kérdései [unpublished prezentation]. Retrieved from https://mgi.naik.hu/system/files/uploads/2019-01/dr_jori_j_istvan_a_precizios_gepesitesi_kerdesei.pdf. (Accessed: 2022.12.31.) Search in Google Scholar

[36] Központi Statisztikai Hivatal (KSH) (2021). Agrárcenzus 2020. Előzetes adatok. https://www.ksh.hu/docs/hun/xftp/ac2020/elozetes_adatok/index.html#/cover (2022.12.31). Search in Google Scholar

[37] Nemzeti Agrárkamara (2019). Egyre többen végeznek precíziós gazdálkodást. Retrieved from: http://nak.hu/en/agazati-hirek/mezogazdasag/146-novenytermesztes/99560-egyre-tobbenvegeznek-precizios-gazdalkodast. (Accessed: 2022.12.31.) Search in Google Scholar