228
Views
0
CrossRef citations to date
0
Altmetric
Research Article

Digital transformation of fruit farming in Germany: Digital tool development, stakeholder perceptions, adoption, and barriers

ORCID Icon, ORCID Icon & ORCID Icon
Article: 2349544 | Received 12 Oct 2023, Accepted 25 Apr 2024, Published online: 12 May 2024

References

  • Aceto, G., Persico, V., Pescapé, A., & Member, S. (2019). A survey on information and communication technologies for industry 4.0: State-of-the-art, taxonomies, perspectives, and challenges. IEEE Communications Surveys & Tutorials, 21(4), 3467–34.
  • Adarsch, A., Pranav, P. M., Manjunath, C. R., & Soumya, K. N. (2018). Fruit farm surveillance using drones. International Journal of Trend in Scientific Research and Development, 2(4), 351–357. https://doi.org/10.31142/ijtsrd12973
  • Ajzen, I. (1991). The theory of planned behavior. Organizational Behavior and Human Decision Processes, 50(2), 179–211. https://doi.org/10.1016/0749-5978(91)90020-T
  • Aravind, K. R., Raja, P., & Pérez-Ruiz, M. (2017). Task-based agricultural mobile robots in arable farming: A review. Spanish Journal of Agricultural Research, 15, e02R01. 15(1).https://doi.org/10.5424/sjar/2017151-9573
  • Arvanitis, K. G., & Symeonaki, E. G. (2020). Agriculture 4.0: The role of innovative smart technologies towards sustainable farm management. The Open Agriculture Journal, 14(1), 130–135. https://doi.org/10.2174/1874331502014010130
  • Bacco, M., Brunori, G., Ferrari, A., Koltsida, P., & Toli, E. (2020a). IoT as a digital game changer in rural areas: The DESIRA conceptual approach. GIoTS 2020 - Global Internet of Things Summit, Proceedings (pp. 0–5). https://doi.org/10.1109/GIOTS49054.2020.9119674
  • Bacco, M., Paolo, B., Brunori, G., Debruyne, L., Ferrari, A., Gotta, A., Panagiota, K., Lepore, F., Orsini, A., Rolandi, S., Ivano, S., & Toli, E. (2020b). Deliverable 1.3: Synthesis report on the taxonomy and inventory of digital game changers. https://desira2020.eu/wp-content/uploads/2020/11/D1.3-Taxonomy-inventory-Digital-Game-Changers.pdf
  • Balafoutis, A. T., Beck, B., Fountas, S., Tsiropoulos, Z., Vangeyte, J., van der Wal, T., Soto-Embodas, I., & Gómez-Barbero Manuel Pedersen, S. M. (2017). Smart farming technologies – description, taxonomy and economic impact. In S. M. Pedersen & K. M. Lind (Eds.), Progress in precision agriculture (pp. 21–77). Springer.
  • 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(January), 66–74. https://doi.org/10.1016/j.envsci.2018.12.014
  • Barnes, A. P., Soto, I., Eory, V., Beck, B., Balafoutis, A., Sanchez, B., Vangeyte, J., Fountas, S., van der Wal, T., & Gomez-Barbero, M. (2019). Exploring the adoption of precision agricultural technologies: A cross regional study of EU farmers. Land Use Policy, 80, 163–174. https://doi.org/10.1016/j.landusepol.2018.10.004
  • Benyam, A. A., Soma, T., & Fraser, E. (2021). Digital agricultural technologies for food loss and waste prevention and reduction: Global trends, adoption opportunities and barriers. Journal of Cleaner Production, 323(September), 129099. https://doi.org/10.1016/j.jclepro.2021.129099
  • Bhakta, I., Phadikar, S., & Majumder, K. (2019). State-of-the-art technologies in precision agriculture: A systematic review. Journal of the Science of Food and Agriculture, 99, 4878–4888. https://doi.org/10.1002/jsfa.9693
  • Bhat, S. A., & Huang, N. F. (2021). Big data and AI revolution in precision agriculture: Survey and challenges. IEEE Access, 9, 110209–110222. https://doi.org/10.1109/ACCESS.2021.3102227
  • Bijker, W. E., & Pinch, T. J. (1987). The social construction of facts and artefacts: Or how the sociology of science and the sociology of Technology might benefit each other. Social Studies of Science, 14(3). https://doi.org/10.1177/030631284014003004
  • Birner, R., Daum, T., & Pray, C. (2021b). Who drives the digital revolution in agriculture? A review of supply-side trends, players and challenges. Applied Economic Perspectives and Policy, 43(4), 1260–1285. https://doi.org/10.1002/aepp.13145
  • Bitkom, D. B., & Rentenbank. (2020). Schon 8 von 10 Landwirten Setzen Auf Digitale Technologien. https://www.bitkom.org/Presse/Presseinformation/Schon-8-von-10-Landwirten-setzen-auf-digitale-Technologien
  • Blasch, J., van der Kroon, B., van Beukering, P., Munster, R., Fabiani, S., Nino, P., & Vanino, S. (2020). Farmer preferences for adopting precision farming technologies: A case study from Italy. European Review of Agricultural Economics, 49(1), 33–81. https://doi.org/10.1093/erae/jbaa031
  • BMEL), B. für E. und L. (2020). Glossar zur Erklärung wesentlicher Begriffe der Digitalisierung. https://www.bmel.de/SharedDocs/Downloads/DE/Broschueren/handreichung-digitalisierung.html
  • Bryman, A. (2012). Social research methods (Vol. 4). Oxford University Press.
  • Bucci, G., Bentivoglio, D., & Finco, A. (2018). Precision agriculture as a driver for sustainable farming systems: State of art in litterature and research. Quality - Access to Success, 19(S1), 114–121.
  • Bundesministerium für Ernährung und Landwirtschaft (BMEL). (2016). Der Gartenbau in Deutschland: Auswertung des Gartenbaumoduls der Agrarstrukturerhebung 2016. Der Gartenbau in Deutschland. https://www.bmel.de/SharedDocs/Downloads/Broschueren/Gartenbauerhebung.pdf?__blob=publicationFile
  • Busse, M., Doernberg, A., Siebert, R., Kuntosch, A., Schwerdtner, W., König, B., & Bokelmann, W. (2014). Innovation mechanisms in German precision farming. Precision Agriculture, 15(4), 403–426. https://doi.org/10.1007/s11119-013-9337-2
  • Coteur, I., Marchand, F., Debruyne, L., Dalemans, F., & Lauwers, L. (2016). A framework for guiding sustainability assessment and on-farm strategic decision making. Environmental Impact Assessment Review, 60, 16–23. https://doi.org/10.1016/j.eiar.2016.04.003
  • Coulibaly, S., Kamsu-Foguem, B., Kamissoko, D., & Traore, D. (2022). Deep learning for precision agriculture: A bibliometric analysis. Intelligent Systems with Applications, 16(April), 200102. https://doi.org/10.1016/j.iswa.2022.200102
  • Das Grüne Lexikon Hortipendium. (2021). Gemüseanbau: Bio oder Konventionell. https://hortipendium.de/Gemüseanbau:_Bio_oder_Konventionell
  • Das, V. J., Sharma, S., & Kaushik, A. (2019). Views of Irish farmers on smart farming technologies: An observational study. AgriEngineering, 1(2), 164–187. https://doi.org/10.3390/agriengineering1020013
  • Davis, F. D. (1989). Perceived usefulness, perceived ease of use, and user acceptance of information technology. MIS Quarterly: Management Information Systems, 13(3), 319–339. https://doi.org/10.2307/249008
  • DESIRA. (2019). The project: About DESIRA. https://desira2020.eu/the-project/
  • Ferrari, A., Bacco, M., Gaber, K., Jedlitschka, A., Hess, S., Kaipainen, J., Koltsida, P., Toli, E., & Brunori, G. (2022). Rethinking sustainability requirements: Drivers, barriers and impacts of digitalisation in rural areas from the viewpoint of experts. Information and Software Technology, 145, 145.
  • Fishbein, M., & Azjen, I. (1975). Belief, attitude, intention, and behaviour: An introduction to theory and research (pp. 578). Addison-Wesley Publishing Company.
  • Gallardo, R. K., & Sauer, J. (2018). Adoption of labor-saving technologies in agriculture. Annual Review of Resource Economics, 10, 185–206. https://doi.org/10.1146/annurev-resource-100517-023018
  • Goodman, L. A. (1961). Snowball sampling. The Annals of Mathematical Statistics, 32(1), 148–170. https://doi.org/10.1214/aoms/1177705148
  • Griliches, Z. (1957). Hybrid corn: An exploration in the economics of technological change. Econometrica, 25(4), 501–522.
  • Grimminger, R., Krawutschke, M., & Berger, S. (2018). Mehr Bio vom Bodensee durch Tradition und Innovation. https://www.bodenseekreis.de/fileadmin/03_umwelt_landnutzung/landwirtschaft/downloads/bio-musterregion/fb_musterregion_bodensee.pdf.
  • Groher, T., Heitkämper, K., & Umstätter, C. (2020). Nutzung digitaler technologien in der schweizer landwirtschaft. Agrarforschung Schweiz, 11(6), 59–67. https://doi.org/10.34776/afs11-59
  • Hicks, J. (1932). The theory of wages. Macmillan.
  • Hilbert, M. (2011). The end justifies the definition: The manifold outlooks on the digital divide and their practical usefulness for policy making. Telecommunications Policy, 35, 715–736. https://doi.org/10.1016/j.telpol.2011.06.012
  • Inwood, S. E. E., & Dale, V. H. (2019). State of apps targeting management for sustainability of agricultural landscapes: A review. Agronomy for Sustainable Development, 39(8), 15.
  • Karunathilake, E. M. B. M., Le, A. T., Heo, S., Chung, Y. S., & Mansoor, S. (2023). The path to smart farming: Innovations and opportunities in precision agriculture. Agriculture (Switzerland), 13(8), 1–26. https://doi.org/10.3390/agriculture13081593
  • Kernecker, M., Knierim, A., & Wurbs, A. (2016). Report on farmers’ needs, innovative ideas and interests. https://www.smart-akis.com/wp-content/uploads/2017/02/D2.2.-Report-on-farmers-needs.pdf
  • Kernecker, M., Knierim, A., Wurbs, A., Kraus, T., & Borges, F. (2020). Experience versus expectation: Farmers’ perceptions of smart farming technologies for cropping systems across Europe. Precision Agriculture, 21(1), 34–50. https://doi.org/10.1007/s11119-019-09651-z
  • King, W. R., & He, J. (2006). A meta-analysis of the technology acceptance model. Information and Management, 43(6), 740–755. https://doi.org/10.1016/j.im.2006.05.003
  • Knierim, A., Borges, F., Lee Kernecker, M., Kraus, T., & Wurbs, A. (2018, july 14). What drives adoption of smart farming technologies? Evidence from a cross-country study. European IFSA Symposium. http://www.smart-akis.eu
  • Knierim, A., Kernecker, M., Erdle, K., Kraus, T., Borges, F., & Wurbs, A. (2019). Smart farming technology innovations – insights and reflections from the German smart-AKIS hub. NJAS - Wageningen Journal of Life Sciences, 90-91, 1–10. https://doi.org/10.1016/j.njas.2019.100314
  • Köhler, D. H. (2018). Digitalisierung im Obstbau – Anwendungen und Aussichten. Rheinhessischer Obstbautag, 1–3. https://www.gb-profi.de/fileadmin/user_upload/GBP/Obstbautag_Rheinhessen_2018.pdf
  • Lan, Y., De Bin Chen, S., & Fritz, B. K. (2017). Current status and future trends of precision agricultural aviation technologies. International Journal of Agricultural and Biological Engineering, 10(3), 1–17. https://doi.org/10.3965/j.ijabe.20171003.3088
  • Landkreis Konstanz, & Landratsamt Bodenseekreis. (2017). Bewerbung als “Bio-Musterregion Bodensee” beim Ministerium für Ländlichen Raum und Verbraucherschutz Baden-Württemberg. https://www.biomusterregionen-bw.de/,Lde/Startseite/Bio-Musterregion+Bodensee
  • Landwirtschaftliches Technologiezentrum Augustenberg (LTZ). (2023). Integrierter Pflanzenschutz 2023: Erwerbsobstbau. 104.
  • LEL Schwäbisch Gmünd. (2017). Obstanbau. https://lel.landwirtschaft-bw.de/pb/,Lde/Startseite/Unsere+Themen/Obstanbau
  • Liakos, K. G., Busato, P., Moshou, D., Pearson, S., & Bochtis, D. (2018). Machine learning in agriculture: A review. Sensors (Switzerland), 18(8), 1–29. https://doi.org/10.3390/s18082674
  • Lowenberg-Deboer, J., & Erickson, B. (2019). Setting the record straight on precision agriculture adoption. Agronomy Journal, 111(4), 1552–1569. https://doi.org/10.2134/agronj2018.12.0779
  • Madushanki, A. A. R., Halgamuge, M. N., Wirasagoda, W. A. H. S., & Syed, A. (2019). Adoption of the Internet of Things (IoT) in agriculture and smart farming towards urban greening: A review. International Journal of Advanced Computer Science and Applications, 10(4), 11–28. https://doi.org/10.14569/ijacsa.2019.0100402
  • Marinoudi, V., Lampridi, M., Kateris, D., Pearson, S., Sørensen, C. G., & Bochtis, D. (2021). The future of agricultural jobs in view of robotization. Sustainability, 13(21), 12109. https://doi.org/10.3390/su132112109
  • Mayring, P. (2000). Qualitative content analysis. Forum: Qualitative Social Research, 1(2), 10. http://file:///C:/Users/nn2120/Downloads/1089-3455-2-PB.pdf
  • Michels, M., Fecke, W., Feil, J. H., Mußhoff, O., Pigisch, J., & Krone, S. (2019). An empirical study of internet use intensity in German agriculture. German Journal of Agricultural Economics, 68(1), 1–14. https://doi.org/10.22004/ag.econ.319804
  • Michels, M., Fecke, W., Feil, J. H., Musshoff, O., Pigisch, J., & Krone, S. (2020). Smartphone adoption and use in agriculture: Empirical evidence from Germany. Precision Agriculture, 21(2), 403–425. https://doi.org/10.1007/s11119-019-09675-5
  • Miranda, J. C., Gené-Mola, J., Zude Sasse, M., Tsoulias, N., Escolà, A., Arnó, J., Rosell-Polo, J. R., Sanz-Cortiella, R., Martínez-Casasnovas, J. A., & Gregorio, E. (2023). Fruit sizing using AI: A review of methods and challenges. Postharvest Biology and Technology, 206(September), 112587. https://doi.org/10.1016/j.postharvbio.2023.112587
  • Miranda, J., Ponce, P., Molina, A., & Wright, P. (2019). Sensing, smart and sustainable technologies for agri-food 4.0. Computers in Industry, 108, 21–36. https://doi.org/10.1016/j.compind.2019.02.002
  • Navarro, E., Costa, N., & Pereira, A. (2020). A systematic review of iot solutions for smart farming. Sensors, 20(4231), 1–29. https://doi.org/10.3390/s20154231
  • Noack, P. (2019). Digitalisierung und Smart Farming: Bedeutung und Nutzen für die heutige Landwirtschaft. Getreidemagazin, 6, 8–11.
  • Ossevoort, Robert, Cor, Verdouw, Peter Frans De Jong, Wil Hennen En, and Robbert Robbemond (2016). Fruit 4.0: De Vruchten van Meer Technologie Technologie-Roadmap. http://library.wur.nl/WebQuery/wurpubs/fulltext/385030
  • Pathak, H. S., Brown, P., & Best, T. (2019). A systematic literature review of the factors affecting the precision agriculture adoption process. Precision Agriculture, 20(6), 1292–1316. https://doi.org/10.1007/s11119-019-09653-x
  • Patrício, D. I., & Rieder, R. (2018). Computer vision and artificial intelligence in precision agriculture for grain crops: A systematic review. Computers and Electronics in Agriculture, 153(June), 69–81. https://doi.org/10.1016/j.compag.2018.08.001
  • Paustian, M., & Theuvsen, L. (2017). Adoption of precision agriculture technologies by German crop farmers. Precision Agriculture, 18(5), 701–716. https://doi.org/10.1007/s11119-016-9482-5
  • Philadelphia Orchard Project. (2021). Summary of orchard care. Philadelpha Orchard Project: Resources. https://www.phillyorchards.org/wp-content/uploads/2015/07/orchard_care.pdf
  • Pierpaoli, E. (2013). Scienze e Tecnologie Agrarie, Ambientali e Alimentari. http://amsdottorato.unibo.it/6623/1/Pierpaoli_Emauele_Tesi.pdf
  • POPA, C. (2011). Adoption of artificial intelligence in agriculture. Bulletin of University of Agricultural Sciences and Veterinary Medicine Cluj-Napoca Agriculture, 68(1), 284–293. https://doi.org/10.15835/buasvmcn-agr:6454
  • Porter, M. E., & Heppelmann, J. E. (2014). How smart, connected products are transforming competition. Harvard Business Review, November 2014.
  • Purcell, W., & Neubauer, T. (2023). Digital twins in agriculture: A state-of-the-art review. Smart Agricultural Technology, 3(January 2022), 100094. https://doi.org/10.1016/j.atech.2022.100094
  • Rijswijk, K., Bulten, E., Klerkx, L., Dessein, J., Debruyne, L., Brunori, G., Scotta, I., Bacco, M., Currie, M., Bartolini, F., van der Velden, D., Rolandi, S., & Metta, M. (2020). Digital transformation of agriculture, forestry and rural areas: developing a futureproof socio-cyber-physical system. 1(1).
  • Roldán, J. J., Del Cerro, J., Garzón‐Ramos, David Garcia‐Aunon, P., Garzón, M., de León, & Jorge Barrientos, A. (2017). Robots in agriculture: State of art and practical experiences. In Service robots (pp. 67–90). InTechOpen. http://www.asociatiamhc.ro/wp-content/uploads/2013/11/Guide-to-Hydropower.pdf
  • Rothwell, R., & Zegveld, W. (1985). Reindustrialization and technology. M.E. Sharp.
  • Saviotti, P. P., & Pyka, A. (2013). The co-evolution of innovation, demand and growth. Economics of Innovation & New Technology, 22(5), 461–482. https://doi.org/10.1080/10438599.2013.768492
  • Schleicher, S., & Gandorfer, M. (2018). Digitalisierung in der Landwirtschaft: Eine Analyse der Akzeptanzhemmnisse. In Digitale Marktplätze und Plattformen (pp. 203–206). Gesellschaft für Informatik. https://dl.gi.de/handle/20.500.12116/23158
  • Shi, X., An, X., Zhao, Q., Liu, H., Xia, L., Sun, X., & Guo, Y. (2019). State-of-the-art internet of things in protected agriculture. Sensors, 19(1833), 24. https://doi.org/10.3390/s19081833
  • Statistisches Bundesamt. (2019a). 69. Anbau, Ertrag und Ernte von Obst. Statistisches Bundesamt (BMEL).
  • Statistisches Bundesamt. (2019b). Verwendung der Obsternte. Statistisches Bundesamt (BMEL).
  • Statistisches Bundesamt (DESTATIS). (2017). Landwirtschaftliche Bodennutzung - Baumobstflächen. https://www.statistik-bw.de/Landwirtschaft/Agrarstruktur/Betriebe-LFGK.jsp
  • Stefas, N., Bayram, H., & Isler, V. (2016). Vision-based UAV navigation in orchards. International Federation of Automatic Control (IFAC)- Papers Online, 49(16), 10–15. https://doi.org/10.1016/j.ifacol.2016.10.003
  • Sunding, D., & Zilberman, D. (2001). Chapter 4 the agricultural innovation process: Research and technology adoption in a changing agricultural sector. Handbook of Agricultural Economics, 1(PART A), 207–261. https://doi.org/10.1016/S1574-0072(01)10007-1
  • Talavera, J. M., Tobón, L. E., Gómez, J. A., Culman, M. A., Aranda, J. M., Parra, D. T., Quiroz, L. A., Hoyos, A., & Garreta, L. E. (2017). Review of IoT applications in agro-industrial and environmental fields. Computers and Electronics in Agriculture, 142(118), 283–297. https://doi.org/10.1016/j.compag.2017.09.015
  • Tardaguila, J., Stoll, M., Gutiérrez, S., Proffitt, T., & Diago, M. P. (2021). Smart applications and digital technologies in viticulture: A review. Smart Agricultural Technology, 1(July), 100005. https://doi.org/10.1016/j.atech.2021.100005
  • Templier, M., & Paré, G. (2015). A framework for guiding and evaluating literature reviews. Communications of the Association for Information Systems, 37, 112–137. https://doi.org/10.17705/1cais.03706
  • Tey, Y. S., & Brindal, M. (2012). Factors influencing the adoption of precision agricultural technologies: A review for policy implications. Precision Agriculture, 13(6), 713–730. https://doi.org/10.1007/s11119-012-9273-6
  • Thomasson, J. A., Baillie, C. P., Antille, D. L., Lobsey, C. R., & Mccarthy, C. L. (2019). Autonomous Technologies in agricultural equipment: A review of the state of the art. ASABE Distinguished Lecture Series, Tractor Design No, 40, 1–17. https://doi.org/10.13031/913
  • Uwe, D., Aparajita, G., & Mishr, D. (2016). Will digital technologies transform agriculture in developing countries? https://hvtc.edu.vn/Portals/0/files/636104758652860273WillDigitalTechnologiesTransformAgricultureinDevelopingCountries.pdf
  • Van Haarlem, L. (2020). The future of fruit farming. [Waginengen University & Research]. https://edepot.wur.nl/531601
  • Vik, J., Melås, A. M., Stræte, E. P., & Søraa, R. A. (2021). Balanced readiness level assessment (BRLa): A tool for exploring new and emerging technologies. Technological Forecasting & Social Change, 169(November 2020). https://doi.org/10.1016/j.techfore.2021.120854
  • Villa-Henriksen, A., Edwards, G. T. C., Pesonen, L. A., Green, O., & Sørensen, C. A. G. (2020). Internet of things in arable farming: Implementation, applications, challenges and potential. Biosystems Engineering, 191, 60–84. https://doi.org/10.1016/j.biosystemseng.2019.12.013
  • Zambon, I., Cecchini, M., Egidi, G., Saporito, M. G., & Colantoni, A. (2019). Revolution 4.0: Industry vs. agriculture in a future development for SMEs. Processes, 7(1), 1–16. https://doi.org/10.3390/pr7010036
  • Zhang, Q., Karkee, M., & Tabb, A. (2019). The use of agricultural robots in orchard management. In J. Billingsley (Ed.), Robotics and automation for improving agriculture (pp. 187–214). Burleigh Dodds Science Publishing. https://doi.org/10.19103/as.2019.0056.14
  • Zhang, C., Valente, J., Kooistra, L., Guo, L., & Wang, W. (2021). Orchard management with small unmanned aerial vehicles: A survey of sensing and analysis approaches. In Precision agriculture. Springer US. https://doi.org/10.1007/s11119-021-09813-y
  • Zoth, M. (2018). Technische Entwicklungen im Obstanbau und Perspektiven: am Beispiel DARWIN-SmaArt, BigApple, u.a. BIOLAND Seminar 2018- Nals/Südtirol, 75.