Theme 5

Smart technologies in farming and food systems


Laurens Klerkx (

Andrew Wilcox (

Pierre Labarthe (

Julie Ingram (


Smart Farming indicates application of different forms of digitalisation in the agriculture sector, such as sensor driven agriculture (e.g. Precision Farming), the use of Big Data for analytical purposes to inform decision making, application of the Internet of Things (e.g. in quality control, producer-consumer relationships), and (autonomous) devices such as robots and drones. Digitalisation is not only a technological matter. It is also associated with new actors from outside agriculture (SMEs, upstream and downstream, service firms, etc.) and with new relations between actors. Whilst the potential benefits of these technologies are very easy to understand at a local scale, their potential impacts on farming systems have not been fully evaluated. Digitalisation is likely to affect and possibly disrupt the agricultural sector beyond the farm gate, influencing supply chain processes, logistics or consumer related information, knowledge and innovation systems, and can have pervasive social, economic, ecological and ethical consequences.

Objectives and orientations for abstracts

This theme provides an opportunity to engage in a constructive dialogue between farmers, educators, scientists and industry about the systemic impacts of Smart Farming within social, political and environmental contexts, from different (inter-)disciplinary angles.  It will also explore the questions that Smart Farming raises for agricultural policy and research and innovation policy and agricultural practice and will address questions such as the one listed below. This topic will be present at IFSA for the second time. In this edition, communication with strong empirical content about the actual implementation of smart farming technologies for different actors: farmers, advisors, researchers, retailers, policy makers…

Smart Farming in practice:

  • How are smart farming technologies actually used by farmers and advisors? Does it change decision making processes and Communities of Practices?
  • What are the business models of actors developing smart farming technologies?


Smart Farming and farm diversity:

  • Who are the beneficiaries and losers following the adoption of Smart Farming technologies in agriculture?  How can this be qualitatively understood and quantified this in a meaningful way?
  • What are the effects of farming scale on the uptake and application Smart Farming? What are the relationships with Smart Food Chains?
  • Are there any common themes regarding barriers and facilitators of Smart Farming technologies between different types of farmers?
Smart Farming and sustainable development:

  • Will Smart Farming make agriculture more or less sustainable or will it improve food security?
  • How does Smart Farming interact with different models of agriculture (i.e. sustainable intensification, agro-ecology, vertical farming, etc.) and with relations between these models: convergence or divergence?
  • To what extent can we effectively model the impacts of Smart Farming? Are the same models applicable for a range of Smart Farming technologies?
  • What significant changes will Smart Farming facilitate (positively and negatively)  within rural societies and their structures and affect factors such as employment opportunities, income, social cohesion etc.?


Smart farming and knowledge and innovation systems:

  • What are the implications for land managers’ learning and experiential knowledge production following wide scale adoption of Smart Farming?
  • How does Smart Farming affect organisations that support learning and innovation in agriculture such as research and advisory systems?
  • How is Smart Farming integrated in new policy or governance models supporting innovation in agriculture?


Smart farming and ethics

  • What are ethical implications of Smart Farming in terms of for example organisation of farm work, animal rights and welfare, power structures in value chains?  How do human and animal systems respond to artefacts such a sensors and drones and how do they co-evolve?
  • How are issues such as data ownership, data sharing and data protection organised?  What novel organisational forms emerge around Big Data and the Internet of Things? How localised or global are such data networks and how do they influence decision making in value chains?
  • What are farming systems researchers’ responsibilities with respect to smart farming and digitisation?