Skip to main content

Advertisement

Log in

Innovation mechanisms in German precision farming

Precision Agriculture Aims and scope Submit manuscript

Abstract

In the precision farming (PF) literature on innovation activities, it becomes apparent that only individual aspects of the entire PF innovation process chain are considered, namely, the knowledge transfer and the adoption of PF applications. Therefore, this study seeks to analyze the innovation mechanisms in the entire PF innovation process chain. The paper identifies potentials, barriers and challenges for PF innovations in Germany and the respective agricultural subsector plant production. An in-depth understanding of innovation mechanisms is required to enhance innovation capabilities, overcome obstacles and bring further innovations to the agricultural field. A mix of qualitative and quantitative methods was applied—including interviews, an expert workshop and a Delphi survey—to explore innovation mechanisms and the role of heterogeneous actors. The research is based on the analytical framework of the sectoral innovation system approach. Key results are the identification of barriers in the later stages of the innovation processes (including validation, serial production and adoption), a gap in the knowledge transfer between science and practice, insufficient communication and co-operation between actors and the important influence of political and legal conditions. Furthermore, this study showed that farmers play an important role in the generation of innovations. For example, farmers are not only adopters or demanders but also impulse providers or co-developers. In conclusion, this study moves the PF innovation debate forward not only by providing adoption facts but also by presenting explanations for the complex interactions between actors throughout the innovation process chain.

This is a preview of subscription content, log in via an institution to check access.

Access this article

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Institutional subscriptions

Fig. 1
Fig. 2
Fig. 3
Fig. 4

Similar content being viewed by others

References

  • Adrian, A. M., Norwood, S., & Mask, P. (2005). Producers’ perceptions and attitudes toward precision agriculture technologies. Computers and Electronics in Agriculture, 48(3), 256–271.

    Article  Google Scholar 

  • Ammon, U. (2005). Delphi-Befragung. [Delphi survey]. In S. Kuehl & P. Strodtholz (Eds.), Methoden der Organisationsforschung. Ein Handbuch [Methods of organisational research. A handbook] (pp. 115–117). Reinbek: Rohwolt.

  • Ancev, T., Whelan, B., & McBratney, A. (2005). Evaluating the benefits from precision agriculture: The economics of meeting traceability requirements and environmental targets. In J. V. Stafford (Ed.), Proceedings of the 5th ECPA (pp. 985–992). Uppsala: Wageningen Academic Publishers.

    Google Scholar 

  • Auernhammer, H. (2001). Precision farming—The environmental challenge. Computers and Electronics in Agriculture, 30(1–3), 31–43.

    Article  Google Scholar 

  • Batte, M., & Arnholt, M. (2003). Precision farming adoption and use in Ohio: Case studies of six leading-edge adopters. Computers and Electronics in Agriculture, 38(2), 125–139.

    Article  Google Scholar 

  • Breschi, S., Malerba, F., & Orsenigo, L. (2000). Technological regimes and Schumpeterian patterns of innovation. The Economic Journal, 110(463), 388–410.

    Article  Google Scholar 

  • Chaminade, C., & Edquist, C. (2010). Rationales for public policy intervention in the innovation process: Systems of innovation approach. In. R. E. Smits, S. Kuhlmann & P. Shapira (Eds.). The theory and practice of innovation policy. An international research handbook. Cheltenham: Edward Elgar.

  • Daberkow, S., & McBride, W. (2003). Farm and operator characteristics affecting the awareness and adoption of precision agriculture technologies in the US. Precision Agriculture, 4(2), 163–177.

    Article  Google Scholar 

  • European Commission. (2012). Communication from the Commission to the European Parliament and the Council on the European Innovation Partnership ‘Agricultural productivity and sustainability’. http://ec.europa.eu/agriculture/eip/pdf/com2012-79_en.pdf. Accessed June 1, 2012.

  • Fountas, S., Blackmore, S., Ess, D., Hawkins, S., Blumhoff, G., Lowenberg-Deboer, J., et al. (2005). Farmer experience with precision agriculture in Denmark and the US Eastern Corn Belt. Precision Agriculture, 6(2), 121–141.

    Article  Google Scholar 

  • Gulbrandsen, M. (2009). The role of basic research in innovation. In W. Østreng (Ed.), Confluence. Interdisciplinary communications 2007/2008 (pp. 55–58). Oslo: Norwegian Academy of Science and Letters, Centre for Advanced Study.

  • Gunnesch-Luca, G., Moser, K., & Kloeble, U. (2010). Adoption und Weiterempfehlung neuer Technologien: Die Bedeutung von Trendsetting. [Adoption and recommendation of new technologies: The meaning of trendsetting]. Der Markt, 49(1), 53-64. doi:10.1007/s12642-010-0026-7.

  • Häder, M. (2009). Delphi-Befragungen. Ein Arbeitsbuch [Delphi survey. A workbook] (2nd ed.). Wiesbaden: Verlag für Sozialwissenschaften.

    Book  Google Scholar 

  • Hatfield, J. (2000). Precision agriculture and environmental quality: Challenges for research and education. Resource document. The National Arbor Day Foundation. http://www.arborday.org/programs/papers/PrecisionAg.html. Accessed June 1, 2012.

  • Havlin, J., & Heiniger, J. (2009). A variable-rate decision support tool. Precision Agriculture, 10(4), 356–369.

    Article  Google Scholar 

  • Hayami, Y., & Ruttan, V. W. (1985). Agricultural development: An international perspective (2nd ed.). Baltimore: Johns Hopkins University Press.

  • Heiniger, R., Havlin, J., Crouse, D., Kvien, C., & Knowles, T. (2002). Seeing is believing: The role of field days and tours in precision agriculture education. Precision Agriculture, 3(4), 309–318.

    Article  Google Scholar 

  • Hekkert, M. P., Suurs, R. A. A., Negro, S. O., Kuhlmann, S., & Smits, R. E. H. M. (2007). Functions of innovation systems: A new approach for analysing technological change. Technological Forecasting and Social Change, 74(4), 413–432.

    Article  Google Scholar 

  • Isermeyer, F. (2003). Für eine leistungsfähige Agrarforschung in Deutschland. Manuskript. [For a powerful agricultural research in Germany. Manuscript]. Braunschweig: FAL-Bundesforschungsanstalt für Landwirtschaft.

  • ISO—International Organisation for Standardization. (2009). ISO 11783 Tractors and machinery for agriculture and forestry—Serial control and communications data network, parts 1–14, Geneva.

  • Kitchen, N., Snyder, C., Franzen, D., & Wiebold, W. (2002). Educational needs of precision agriculture. Precision Agriculture, 3(4), 341–351.

    Article  Google Scholar 

  • Kline, S. J., & Rosenberg, N. (1986). An overview of innovation. In R. Landau & N. Rosenberg (Eds.), The positive sum strategy. Harnessing technology for economic growth (pp. 275–305). Washington D.C.: National Academy Print.

  • Knickel, K., Brunori, G., Rand, S., & Proost, J. (2009). Towards a better conceptual framework for innovation processes in agriculture and rural development: From linear models to systemic approaches. Journal of Agricultural Education and Extension, 15(2), 131–146.

    Article  Google Scholar 

  • Koschatzky, K., Baier, E., Kroll, H., & Stahlecker, T. (2009). The spatial multidimensionality of sectoral innovation: The case of information and communication technologies. Working Papers Firms and Region, R4. Karlsruhe: Fraunhofer ISI.

  • Kroulík, M., Kvíz, Z., Kumhála, F., Hůla, J., & Loch, T. (2009). Procedures of soil farming allowing to reduce compaction. Precision Agriculture, 12(3), 317–333.

    Article  Google Scholar 

  • KTBL. (2010). Automatisierung und Roboter in der Landwirtschaft. [Automatisation and roboter in agriculture]. KTBL-Tagung vom 21.-22. April 2010 in Erfurt, Germany: KTBL—Kuratorium für Technik und Bauwesen in der Landwirtschaft.

  • Kutter, T., Tiemann, S., Siebert, R., & Fountas, S. (2011). The role of communication and co-operation in the adoption of precision farming. Precision Agriculture, 12(1), 2–17.

    Article  Google Scholar 

  • Lawson, L., Pedersen, S., Sørensen, C., Pesonen, L., Fountas, S., Werner, A., et al. (2011). A four nation survey of farm information management and advanced farming systems: A descriptive analysis of survey responses. Computers and Electronics in Agriculture, 77(1), 7–20.

    Article  Google Scholar 

  • Liebold, R., & Trinczek, R. (2002). Experteninterview. [Interviews with experts]. In S. Kühl & P. Strodtholz (Eds.), Methoden der Organisationsforschung. Ein Handbuch [Methods and organisational research. A handbook] (pp. 33–71). Reinbek: Rohwolt.

  • Linstone, H., & Turoff, M. (1975). The Delphi method: Techniques and applications. Reading, MA: Addison-Wesley.

    Google Scholar 

  • Maclaurin, W. R. (1953). The sequence from invention to innovation and its relation to economic growth. Quarterly Journal of Economics, 67(1), 97–111.

    Article  Google Scholar 

  • Malerba, F. (2002). Sectoral systems of innovation and production. Research Policy, 31(2), 247–264.

    Article  Google Scholar 

  • Malerba, F. (2004). Sectoral systems of innovation. Concepts, issues and analysis of six major sectors in Europe. Cambridge: Cambridge University Press.

    Book  Google Scholar 

  • Mayring, P. (1997). Qualitative InhaltsanalyseGrundlagen und Techniken. [Qualitative content analysis—Basics and techiques]. Weinheim: Beltz.

  • Meuser, M., & Nagel, U. (2005). ExpertInneninterviews—vielfach erprobt, wenig bedacht. Ein Beitrag zur qualitativen Methodendiskussion. [Interviews with experts - Often used, seldom discussed. A contribution to debates on qualitative methods]. In A. Bogner, B. Littig & W. Menz (Eds.), Das Experteninterview. Theorie, Methode, Anwendung [The expert interview. Theory, method, application] (2nd Ed., pp. 71–93). Wiesbaden: Verlag für Sozialwissenschaften.

  • Meuser, M., & Nagel, U. (2009). Das Experteninterview—konzeptionelle Grundlagen und methodische Anlage. [The expert interview—conceptual basics and methodological design]. In S. Pickel, G. Pickel, H.-J. Lauth & D. Jahn (Eds.), Methoden der vergleichenden Politik- und Sozialwissenschaft - Neue Entwicklungen und Anwendungen [Methods in comparative political and social science – New developments and applications] (pp. 465–479). Wiesbaden: Verlag für Sozialwissenschaften. doi:10.1007/978-3-531-91826-6_23.

  • Nagaoka, S., Motohashi, K., & Goto, A. (2010): Patent statistics as an innovation indicator. In B. H. Hall & N. Rosenberg (Eds.), Handbook of the economics of innovations (Vol. 2, pp. 1083–1127). Amsterdam (i.a.): Elsevier North-Holland.

  • Oliver, M., & Stafford, J. (2009). Editorial for special issue of papers on the German Preagro project. Precision Agriculture, 10(6), 488–489.

    Article  Google Scholar 

  • Pardey, P. G., Alston, J. M., & Ruttan, V. W. (2010). The economics of innoavtion and technical change in agriculture. In B. H. Hall & N. Rosenberg (Eds.), Handbook of the economics of innovations (Vol. 2, pp. 939–984). Amsterdam (i.a.): Elsevier North-Holland.

  • Patton, M. Q. (2002). Qualitative research and evaluation methods. Thousand Oaks: Sage Publications.

    Google Scholar 

  • Pedersen, S., Ferguson, R., & Lark, M. (2001). A multinational survey of precision farming early adopters. Farm Management, 11(3), 147–162.

    Google Scholar 

  • Pedersen, S., Fountas, S., Blackmore, S., Gylling, M., & Pedersen, J. (2004). Adoption and perspective of precision farming in Denmark. Acta Agriculturae Scandinavica Section B. Soil and Plant Science, 54(1), 2–6.

    Article  Google Scholar 

  • Pedersen, S., & Kirketerp Scavenius, I. (2011). Environmental impact with environmental indicators—with precision farming and controlled traffic systems. Resource document. FutureFarm report. http://www.futurefarm.eu/system/files/FFD5.6_Environmental_impact_final.pdf. Accessed June 1, 2012.

  • Pill, J. (1971). The Delphi method: Substance, context, a critique and an annotated bibliography. Socio-Economic Planning, 5(1), 57–71.

    Article  Google Scholar 

  • Reetz, H. F. (2002). Using conferences and workshops for technology training. Precision Agriculture, 3(4), 319–325.

    Article  Google Scholar 

  • Reichardt, M., & Jürgens, C. (2009). Adoption and future perspective of precision farming in Germany: Results of several surveys among different agricultural target groups. Precision Agriculture, 10(1), 73–94.

    Article  Google Scholar 

  • Reichardt, M., Jürgens, C., Kloeble, U., Hueter, J., & Moser, K. (2009). Dissemination of precision farming in Germany: Acceptance, adoption, obstacles, knowledge transfer and training activities. Precision Agriculture, 10(6), 525–545.

    Article  Google Scholar 

  • Robertson, M. J., Llewellyn, R. S., Mandel, R., Lawes, R., Bramley, R. G. V., Swift, L., et al. (2012). Adoption of variable rate fertiliser application in the Australian grains industry: Status, issues and prospects. Precision Agriculture, 13(2), 181–199.

    Article  Google Scholar 

  • Rogers, E. M. (2003). Diffusion of innovations (5th ed.). New York: Free Press.

    Google Scholar 

  • Sattler, C., & Nagel, U. (2010). Factors affecting farmers’ acceptance of conservation measures—A case study from north-eastern Germany. Land Use Policy, 27(1), 70–77.

    Article  Google Scholar 

  • SCAR—Standing Committee on Agricultural Research. (2012). Agricultural knowledge and innovation systems in transition—a reflection paper. http://ec.europa.eu/research/bioeconomy/pdf/ki3211999enc_002.pdf. Accessed March 25, 2013.

  • Shockley, J., Dillon, C. R., Stombaugh, T., & Shearer, S. (2012). Whole farm analysis of automatic section control for agricultural machinery. Precision Agriculture, 13(4), 411–420.

    Article  Google Scholar 

  • Smith, K. (2005). Measuring innovation. In J. Fagerberg, D. C. Mowery, & R. R. Nelson (Eds.), Handbook of innovation (pp. 148–177). Oxford: Oxford University Press.

    Google Scholar 

  • Sørensen, C. G., Fountas, S., Nash, E., Pesonen, L., Bochtis, D., Pedersen, S. M., et al. (2010). Conceptual model of a future farm management information system. Computers and Electronics in Agriculture, 72(1), 37–47.

    Article  Google Scholar 

  • Stafford, J., & Werner, A. (Eds.). (2002). Precision agriculture. Wageningen: Academic Publishers.

    Google Scholar 

  • Sunding, D., & Zilberman, D. (2001). The agricultural innovation process: Research and technology adoption in a changing agricultural sector. In B. L. Gardner & G. C. Rausser (Eds.), Handbook of agricultural economics (Vol 1A Agricultural Production, pp. 207–261). Amsterdam (i.e.): Elsevier North-Holland.

  • Theuvsen, L., Janze, C., & Heyer, M. (2010). Agribusiness in Deutschland 2010. Unternehmen auf dem Weg in neue Märkte! Ernst &Young (Eds.). [Agribusiness in Germany 2010. Companies on the way to new markets!]. http://www.bv-agrar.de/bvagrar/agrarwelt/ausbildung/studie_agribusiness_2010.pdf. Accessed June 3, 2012.

  • Tohidi, H., & Jabbari, M. M. (2012). Different stages of innovation process. Procedia Technology, 1(1), 574–578.

    Article  Google Scholar 

  • Trott, P. (2002). Innovation management and new product development. Edinburgh Gate, Harlow: Financial Times Prentice Hall.

    Google Scholar 

  • Wang, Y.-P., Chen, S.-H., Chang, K.-W., & Shen, Y. (2012). Identifying and characterizing yield limiting factors in paddy rice using remote sensing yield maps. Precision Agriculture, 13(5), 553–567.

    Article  CAS  Google Scholar 

  • Wissenschaftsrat. (2006). Empfehlungen zur Entwicklung der Agrarwissenschaften in Deutschland im Kontext benachbarter Fächer (Gartenbau-, Forst- und Ernährungswissenschaften). [Recommendations for the development of agricultural sciences in Germany in the context of neighbouring scientific areas]. Koeln. http://www.wissenschaftsrat.de/download/archiv/agrarwissenschaften.pdf. Accessed June 1, 2012.

  • Yu, M., Segarra, E., Lascano, R., & Booker, J. (2003). Economic impacts of precision farming in irrigated cotton production. The Texas Journal of Agriculture and Natural Resource, 16(1), 1–14.

    Google Scholar 

  • Zhang, N., Wang, M., & Wang, N. (2002). Precision agriculture—a worldwide overview. Computers and Electronics in Agriculture, 36(2–3), 113–132.

    Article  Google Scholar 

Download references

Acknowledgments

This paper presents selected results from a comprehensive study regarding the German Agricultural innovation system. The study received funding from the Innovation Support Program of the German Federal Ministry of Food, Agriculture and Consumer Protection (BMELV) based on a German Parliament resolution (Grant 123-02.05-20.0076/10-H). This study included a Delphi survey, in which 150 experts from plant production, live stock farming and horticulture were contacted. The results from these three groups were quite comparable. The authors would like to thank Dr. Sven Lundie (Doeninghaus, Walker & Partner, moderator of the workshops), Judith Emmerling (student assistant at the Humboldt-University of Berlin, Department of Agricultural Economics) and all experts for participating in interviews, workshops and the survey.

Author information

Authors and Affiliations

Authors

Corresponding author

Correspondence to M. Busse.

Rights and permissions

Reprints and permissions

About this article

Cite this article

Busse, M., Doernberg, A., Siebert, R. et al. Innovation mechanisms in German precision farming. Precision Agric 15, 403–426 (2014). https://doi.org/10.1007/s11119-013-9337-2

Download citation

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s11119-013-9337-2

Keywords

Navigation