Experience versus expectation: farmers’ perceptions of smart farming technologies for cropping systems across Europe

Technological innovations are changing mechanisation in agriculture. The most recent wave of innovations referred to as smart farming technologies (SFT), promise to improve farming by responding to economic, ecological, and social challenges and thereby sustainably develop agriculture throughout Europe. To better understand the relevance of ongoing technological progress for farming systems across Europe, 287 farmers were surveyed in 7 EU countries and in 4 cropping systems, alongside 22 in-depth semi-structured interviews with experts from the agricultural knowledge and innovation system. Of the surveyed farmers, about 50% were SFT adopters and 50% were non-adopters. The number of adopters increased with farm size, and there were more adopters among arable cropping systems than in tree crops. Although all farmers broadly perceive SFT as useful to farming and generally expect SFT to continue to be so, when it comes to specific on-farm challenges, farmers are less convinced of SFT potential. Moreover, farmers’ perceptions of SFT vary according to SFT characteristics and farming context. Interestingly, both adopter and non-adopter groups are hesitant regarding SFT adoption, such that adopters are somewhat disillusioned about the SFT that they have experience with, and non-adopters because they are not convinced that the appropriate technologies are available and accessible. About 60% of all farmers surveyed have a number of suggestions for SFT to become more relevant to a broader range of farms. Both farmers and experts generally consider peer-to-peer communication as important sources of information and deplore a lack of impartial advice. Experts are generally more convinced of SFT advantages, and are positive regarding the long-term trends of technological development. The findings support previous findings on using farmers’ perceptions in innovation processes, and provide insight to the recent trends regarding SFT application to diverse cropping systems across Europe. This suggests that differences related to agricultural structures and farming systems across Europe have to be considered if SFT development and dissemination should be improved.

[1]  Helen Newing,et al.  Conducting Research in Conservation: Social Science Methods and Practice , 2010 .

[2]  R Core Team,et al.  R: A language and environment for statistical computing. , 2014 .

[3]  G. Williamson Introduction to Social Research Quantitative and Qualitative Approaches, 2nd edn , 2006 .

[4]  D. Pannell,et al.  Predicting farmer uptake of new agricultural practices: A tool for research, extension and policy , 2017 .

[5]  Spyros Fountas,et al.  Farm management information systems: Current situation and future perspectives , 2015, Comput. Electron. Agric..

[6]  Jenny C. Aker,et al.  Dial 'A' for Agriculture: A Review of Information and Communication Technologies for Agricultural Extension in Developing Countries , 2011 .

[7]  R. Burton The influence of farmer demographic characteristics on environmental behaviour: a review. , 2014, Journal of environmental management.

[8]  S. Blackmore,et al.  Agricultural Robots Applications and Economic Perspectives , 2008 .

[9]  A. Maffioli,et al.  Improving technology adoption in agriculture through extension services: evidence from Uruguay , 2013 .

[10]  Frank Vanclay,et al.  Farmer rationality and the adoption of environmentally sound practices; A critique of the assumptions of traditional agricultural extension , 1994 .

[11]  P. Mayring Qualitative content analysis: theoretical foundation, basic procedures and software solution , 2014 .

[12]  John W. Creswell,et al.  Research Design: Qualitative, Quantitative, and Mixed Methods Approaches , 2010 .

[13]  M. Carolan Publicising Food: Big Data, Precision Agriculture, and Co-Experimental Techniques of Addition , 2017 .

[14]  M. Reichardt,et al.  Adoption and future perspective of precision farming in Germany: results of several surveys among different agricultural target groups , 2009, Precision Agriculture.

[15]  Aysha Fleming,et al.  Is big data for big farming or for everyone? Perceptions in the Australian grains industry , 2018, Agronomy for Sustainable Development.

[16]  P. Zander,et al.  Sustaining Farming on Marginal Land: Farmers’ Convictions, Motivations and Strategies in Northeastern Germany , 2017 .

[17]  Volker Hoffmann,et al.  Handbook: Rural extension, Volume 1: Basic issues and concepts , 2009 .

[18]  K. Poppe On markets and government: property rights to promote sustainability with market forces , 2013 .

[19]  Stan G. Daberkow,et al.  Farm and Operator Characteristics Affecting the Awareness and Adoption of Precision Agriculture Technologies in the US , 2003, Precision Agriculture.

[20]  C. Laurent,et al.  Pluralism of agricultural advisory service providers – Facts and insights from Europe , 2017 .

[21]  Liisa Pesonen,et al.  A four nation survey of farm information management and advanced farming systems , 2011 .

[22]  Sue Oreszczyn,et al.  The role of networks of practice and webs of influencers on farmers' engagement with and learning about agricultural innovations , 2010 .

[23]  Yeong Sheng Tey,et al.  Factors influencing the adoption of precision agricultural technologies: a review for policy implications , 2012, Precision Agriculture.

[24]  T. Kutter,et al.  The role of communication and co-operation in the adoption of precision farming , 2011, Precision Agriculture.

[25]  Achim Walter,et al.  Opinion: Smart farming is key to developing sustainable agriculture , 2017, Proceedings of the National Academy of Sciences.

[26]  Thorsten Dresing,et al.  Praxisbuch Interview, Transkription & Analyse , 2015 .

[27]  S. Wolfert,et al.  Big Data in Smart Farming – A review , 2017 .

[28]  Bruno Basso,et al.  Environmental and economic benefits of variable rate nitrogen fertilization in a nitrate vulnerable zone. , 2016, The Science of the total environment.

[29]  Ludwig Theuvsen,et al.  Adoption of precision agriculture technologies by German crop farmers , 2016, Precision Agriculture.

[30]  E. Rogers Diffusion of Innovations , 1962 .

[31]  Dayton M. Lambert,et al.  Profiles of US farm households adopting conservation-compatible practices , 2007 .

[32]  Thomas B. Long,et al.  Barriers to the adoption and diffusion of technological innovations for climate-smart agriculture in Europe: evidence from the Netherlands, France, Switzerland and Italy , 2016 .

[33]  Earl R. Babbie,et al.  The practice of social research , 1969 .

[34]  C. Mircioiu,et al.  A Comparison of Parametric and Non-Parametric Methods Applied to a Likert Scale , 2017, Pharmacy.

[35]  P. Verburg,et al.  Opportunities for sustainable intensification in European agriculture , 2018 .

[36]  Katrin Prager,et al.  The AKIS Concept and its Relevance in Selected EU Member States , 2015 .

[37]  Peter J. Thorburn,et al.  A Conceptual Framework for Guiding the Participatory Development of Agricultural Decision Support Systems , 2010 .

[38]  Keith Punch,et al.  Introduction to Social Research: Quantitative and Qualitative Approaches , 1998 .