Perceptions and Attitudes of Greek Farmers Towards Adopting Precision Agriculture: Case Study Region of Central Greece

  • Evagelia KoutridiEmail author
  • Olga Christopoulou
  • Marie-Noëlle Duquenne
Part of the Multiple Criteria Decision Making book series (MCDM)


Modern scientific community after years of intensification of agricultural resources (soil, water, etc.) management, and with the actual risk of their depletion or degradation, is called to redefine standard agricultural practices with an environmentally friendly approach, focusing on their preservation, their enrichment and perpetuity of their yields. Also the nutritional stakes and environmental threats are high, brought about by the continuous growth of the world population which is expected to reach 10 billion in 2050 compared to 7.1 in 2013. In this context, the present study explores to what extent those directly involved, the crop producers, perceive the necessity of sustainable management of agricultural resources through the emerging practice of Precision Agriculture regarding the management of smaller parts of the fields according to the needs of each of them, while reducing inputs. This research aims to examine the concepts of crop producers regarding the prospects that arise through the adoption of Precision Agriculture in Greece, a country with problematic primary sector, with particular climatic conditions and varied micro-climates while compete countries of low labour costs. The methodological approach is based on field research using questionnaires concerning a representative sample of crop producers in the Region of Central Greece. The choice of variables assessed as necessary for the adoption of the Precision Agriculture techniques by the producers, was based on empirical observations, as well as the use of literature sources. Then, an exploratory factor analysis is carried out on parameters that are considered necessary by producers to adopt new technologies and how they perceive the successive situation that will be shaped by the new digital revolution in agricultural practice. Finally, the possibility of restarting primary production is being discussed, now that, due to the economic recession, many young people more familiar with technology are returning to the province and undertake to cultivate the land in the absence of any other employment.


Sustainable agricultural resources management Crop production New technologies and techniques Precision agriculture Factor analysis 


  1. Anthopoulou, T., & Goussios, D. (2007). Rural geography. In T. Terkenlis, T. Iosifidis, I. Chorianopoulos, & Ι. Χωριανόπουλος (Eds.), Anthropography (pp. 234–274). Athens: Kritiki AE.Google Scholar
  2. Auernhammer, H. (2001). Precision farming—the environmental challenge. Computing Electronic Agriculture, 31, 43–30.Google Scholar
  3. Chalkos, G. (2013). Economy and environment, methods of valuation and management. Athens: Publications Liberal Books.Google Scholar
  4. Chen, C., Pan, J., & Lam, S. K. (2014). A review of precision fertilization research. Environmental Earth Sciences, 71, 4073–4080. Berlin: Springer.CrossRefGoogle Scholar
  5. Cronbach, L. J., & Shavelson, R. J. (2004). My current thoughts on coefficient alpha and successor procedures. Educational and Psychological Measurement, 64(3), 391–418. Scholar
  6. Duquenne, M. N. (2016). Course notes spatial analysis of Master’s studies program in “Spatial Analysis and Environmental management”.Google Scholar
  7. European Parliament Department B Structural and Cohesion Policies. (2014). Study: “Precision Agriculture An Opportunity For EU Farmers- Potential Support with the CAP 2014–2020”. Brussels: European Parliament. Retrieved from
  8. EUROSTAT. (2014). Rural Development Report 2014.
  9. FAO. (2010, November 3–5). Report of International Scientific Symposium on Biodiversity and Sustainable Diets, Rome.Google Scholar
  10. Fountas, S., & Gemtos, T. (2015). Precision agriculture. Athens: Publications Hellenic Academic EBooks SEAB.CrossRefGoogle Scholar
  11. Gebbers, R., & Adamchuk, V. I. (2010). Precision agriculture and food security. Science, 327(5967), 828–831. Sciences. ISSN: 0975-8585.CrossRefGoogle Scholar
  12. Geiger, F., Bengtsson, J., Berendese, F., et al. (2010). Persistent negative effects of pesticides on biodiversity and biological control potential on European farmland. Basic and Applied Ecology, 11(2), 97–105.CrossRefGoogle Scholar
  13. Gerakis, P. A., Veresoglou, D. S., & Kalmpourtzi, K. L. (2008). Sustainable development of agricultural resources. Thessaloniki: Modern Education Publications.Google Scholar
  14. Goussios, D., & Duquenne, M. N. (2003). L’exploitation agricole a` distance en Grece: mobilite, pluriactivite et ruralisation (Note). In Mediterranee, tome 100, 1-2-2003. Recherches recentes en geographie aixoise. pp. 45–48.CrossRefGoogle Scholar
  15. Headley, C. (2014). The role of precision agriculture for improved nutrient management on farms. Journal of the Science of Food and Agriculture, 95, 12–19.CrossRefGoogle Scholar
  16. Hellenic Statistical Authority (ELSTAT). (2014). Census of Agriculture and Livestock 2009 – Structure survey of agricultural and livestock farms of Greece – Single format of metadata-SIMS2014. Retrieved from
  17. Hogan, T. P., & Cannon, B. (2007). Psychological testing: A practical introduction (2nd ed.). Hoboken, NJ: Wiley. ISBN 978-0-471-73807-7.Google Scholar
  18. International Assessment of Agricultural Knowledge, Science and Technology for Development (IAASTD). (2009). Agriculture at a crossroads. In B. Mclntyre, H. R. Herren, J. Wakhungu, & R. T. Watson (Eds.), Synthesis report. Washington, DC: Island Press.Google Scholar
  19. Katter, T., Tiemann, S., Siebert, R., & Fountas, S. (2009). The role of communication and co-operation in the adoption of precision farming. Precision Agriculture.
  20. Kountios, G. (2014). Precision agriculture and information and communication technologies: Research of young farmers educational needs in Central Macedonia. PhD Thesis, Aristotle University of Thessaloniki. Retrieved from
  21. Kountios, G., Ragkos, A., Bournaris, T., Papadavid, G., & Michailidis, A. (2017). Educational needs and perceptions of the sustainability of Precision Agriculture: Survey evidence from Greece. Precision Agriculture.
  22. Kurth, T., Gocke, A., Wagner, K., & Corsini, L. (2015). Crop Farming 2030. The reinvention of the sector. USA: Boston Consulting Group.Google Scholar
  23. Lawson, L. G., Pedersen, S. M., Sorensen, C. G., Pesonen, L., Fountas, S., Werner, A., Oudshoorn, F. W., Herold, L., Chatzinikos, T., Kirketerp, I. M., & Blackmore, S. (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, 7–20.CrossRefGoogle Scholar
  24. Lei, P.-W., & Wu, Q. (2007). CTTITEM: SAS macro and SPSS syntax for classical item analysis. Behaviour Research Methods, 39(3), 527–530. PMID 17958163.CrossRefGoogle Scholar
  25. Michailidis, A., Samathrakis, B., Xatzitheodoridis, F., & Loizou, E. (2010). Adoption-diffusion of precision agriculture: Comparative analysis among the Greek regions. In M. Arambatzis, et al. (Eds.), Innovative applications of information technology in the agricultural sector and the environment (pp. 123–138). 3rd volume of scientific papers of the Hellenic Association for Information and Communication Technologies in Agriculture Food and Environment (HAICTA), Branch of Northern and Central Greece, Thessaloniki.Google Scholar
  26. Mourtzinis, S., Fountas, S., & Gemtos, T. (2007). Perspective of Greek farmers for precision agriculture (Vol. 185, pp. 850–857). Proceedings of the 5th National Congress of Agricultural Engineering.Google Scholar
  27. National Research Council. (1997). Precision agriculture in the 21st century. Washington, DC: National Academy Press.Google Scholar
  28. Oliver, M. (2013). An overview of precision agriculture. In M. Oliver, T. Bishop, & B. Marchant (Eds.), Precision Agriculture for sustainability and environmental protection (pp. 3–12). Abingdon: Routledge.Google Scholar
  29. Pannell, D. J., Marshall, G. R., Barr, N., Curtis, A., Vanclay, F., & Wilkinson, R. (2006). Understanding and promoting adoption of conservation practices by rural landholders. Australian Journal of Experimental Agriculture, 46, 1407–1424.CrossRefGoogle Scholar
  30. Pearson, K. (1900). X. On the criterion that a given system of deviations from the probable in the case of a correlated system of variables is such that it can be reasonably supposed to have arisen from random sampling. Philosophcal Magazine Series 5, 50(302), 157–175. Retrieved from Scholar
  31. Pison, G., Rousseeuw, J. P., Filzmozer, P., & Croux, C. (2003). Robust factor analysis. Journal of Multivariate Analysis, 84, 145–172.CrossRefGoogle Scholar
  32. Rogers, E. (2003). Diffusion of innovations (5th ed.). Simon and Schuster. ISBN 978-0-7432-5823-4. Google Scholar
  33. Rogerson, P. (2001). Statistical methods for geography. London: Sage.CrossRefGoogle Scholar
  34. World Bank. (2007). World Development Report 2008 “Agriculture for Development”. Washington DC: World Bank/Oxford University Press.CrossRefGoogle Scholar

Copyright information

© Springer International Publishing AG, part of Springer Nature 2018

Authors and Affiliations

  • Evagelia Koutridi
    • 1
    Email author
  • Olga Christopoulou
    • 2
  • Marie-Noëlle Duquenne
    • 2
  1. 1.LamiaGreece
  2. 2.VolosGreece

Personalised recommendations