Skip to main content

Thank you for visiting You are using a browser version with limited support for CSS. To obtain the best experience, we recommend you use a more up to date browser (or turn off compatibility mode in Internet Explorer). In the meantime, to ensure continued support, we are displaying the site without styles and JavaScript.

On-Farm Experimentation to transform global agriculture


Restructuring farmer–researcher relationships and addressing complexity and uncertainty through joint exploration are at the heart of On-Farm Experimentation (OFE). OFE describes new approaches to agricultural research and innovation that are embedded in real-world farm management, and reflects new demands for decentralized and inclusive research that bridges sources of knowledge and fosters open innovation. Here we propose that OFE research could help to transform agriculture globally. We highlight the role of digitalization, which motivates and enables OFE by dramatically increasing scales and complexity when investigating agricultural challenges.

This is a preview of subscription content, access via your institution

Access options

Rent or buy this article

Prices vary by article type



Prices may be subject to local taxes which are calculated during checkout

Fig. 1: The OFE process.
Fig. 2: OFE designs to capture field-scale variations.
Fig. 3: Examples of OFE initiatives connecting across the world.
Fig. 4: OFE scientific directions.

Data availability

The authors declare that the data supporting the findings of this study are available within the paper and its Supplementary Information (sources of Figs. 13).


  1. Whitfield, S., Challinor, A. J. & Rees, R. M. Frontiers in climate smart food systems: outlining the research space. Front. Sustain. Food Syst. 2, (2018).

  2. Scoones, I. & Thompson, J. (eds) Farmer First Revisited: Innovation for Agricultural Research and Development 1st edn (Practical Action Publishing, 2009).

  3. Stone, G. D. Towards a general theory of agricultural knowledge production: environmental, social, and didactic learning. Cult. Agric. Food Environ. 38, 5–17 (2016).

  4. Hansson, S. O. Farmers’ experiments and scientific methodology. Euro. J. Phil. Sci. 9, 32 (2019).

  5. Maat, H. & Glover, D. in Contested Agronomy: Agricultural Research in a Changing World (eds Sumberg, J. & Thompson, J.) 131–145 (Routledge, 2012).

  6. Šūmane, S. et al. Local and farmers’ knowledge matters! How integrating informal and formal knowledge enhances sustainable and resilient agriculture. J. Rural Stud. 59, 232–241 (2018).

    Article  Google Scholar 

  7. de Janvry, A., Sadoulet, E. & Rao, M. Adjusting Extension Models to the Way Farmers Learn Policy Brief No. 159 (FERDI, 2016).

  8. Cross, R. & Ampt, P. Exploring agroecological sustainability: unearthing innovators and documenting a community of practice in Southeast Australia. Soc. Nat. Resour. 30, 585–600 (2016).

    Article  Google Scholar 

  9. Rickards, L., Alexandra, J., Jolley, C., Farhey, K. & Frewer, T. Review of Agricultural Extension (ACIAR, 2019).

  10. MacMillan, T. & Benton, T. G. Engage farmers in research. Nature 509, 25–27 (2014).

    Article  ADS  CAS  Google Scholar 

  11. Waters-Bayer, A. et al. Exploring the impact of farmer-led research supported by civil society organisations. Agric. Food Secur. 4, 4 (2015).

  12. Berthet, E. T. A., Barnaud, C., Girard, N., Labatut, J. & Martin, G. How to foster agroecological innovations? A comparison of participatory design methods. J. Environ. Plan. Manage. 59, 280–301 (2015).

    Article  Google Scholar 

  13. Cook, S. et al. An on-farm experimental philosophy for farmer-centric digital innovation. In 14th International Conference on Precision Agriculture (ISPA, 2018).

  14. Cook, S. E., Cock, J., Oberthür, T. & Fisher, M. On-farm experimentation. Better Crops 97, 17–20 (2013).

    Google Scholar 

  15. Richardson, M. et al. Farmer research networks in principle and practice. Int. J. Agric. Sustain. (2021).

  16. Thompson, L. J. et al. Farmers as researchers: in‐depth interviews to discern participant motivation and impact. Agron. J. 111, 2670–2680 (2019).

    Article  Google Scholar 

  17. Sewell, A. M. et al. Hatching new ideas about herb pastures: learning together in a community of New Zealand farmers and agricultural scientists. Agric. Syst. 125, 63–73 (2014).

    Article  Google Scholar 

  18. Bramley, R. G. V., Lawes, R. & Cook, S. in Precision Agriculture for Sustainability and Environmental Protection (eds Oliver, M. A., Bishop, T. F. A. & Marchant, B. M.) 205–218 (Routledge, 2013).

  19. Marchant, B. et al. Establishing the precision and robustness of farmers’ crop experiments. Field Crops Res. 230, 31–45 (2019).

    Article  Google Scholar 

  20. Briggs, J. Indigenous knowledge: a false dawn for development theory and practice? Progr. Dev. Stud. 13, 231–243 (2013).

    Article  Google Scholar 

  21. Caron, P., Biénabe, E. & Hainzelin, E. Making transition towards ecological intensification of agriculture a reality: the gaps in and the role of scientific knowledge. Curr. Opin. Environ. Sustain. 8, 44–52 (2014).

    Article  Google Scholar 

  22. Kool, H., Andersson, J. A. & Giller, K. E. Reproducibility and external validity of on-farm experimental research in Africa. Exp. Agric. 56, 587–607 (2020).

  23. de Roo, N., Andersson, J. A. & Krupnik, T. J. On-farm trials for development impact? The organisation of research and the scaling of agricultural technologies. Exp. Agric. 55, 163–184 (2019).

    Article  Google Scholar 

  24. Möhring, N. et al. Pathways for advancing pesticide policies. Nat. Food 1, 535–540 (2020).

    Article  Google Scholar 

  25. Sylvester-Bradley, R. et al. Agronōmics: transforming crop science through digital technologies. Adv. Anim. Biosci. 8, 728–733 (2017).

    Article  Google Scholar 

  26. Ruiz, J., Dumont, A. & Zingraff, V. in Penser le Gouvernement des Ressources Naturelles (eds Busca, D. & Lew, N.) 293–330 (Presses de l’Université Laval, 2019).

  27. Fabregas, R., Kremer, M. & Schilbach, F. Realizing the potential of digital development: the case of agricultural advice. Science (2019).

  28. Dowd, A.-M. et al. The role of networks in transforming Australian agriculture. Nat. Clim. Change 4, 558–563 (2014).

    Article  ADS  Google Scholar 

  29. Klerkx, L., van Mierlo, B. & Leeuwis, C. in Farming Systems Research into the 21st Century: The New Dynamic (eds Darnhofer, I., Gibbon, D. & Dedieu, B.) 457–483 (Springer, 2012).

  30. Ingram, J., Gaskell, P., Mills, J. & Dwyer, J. How do we enact co-innovation with stakeholders in agricultural research projects? Managing the complex interplay between contextual and facilitation processes. J. Rural Stud. 78, 65–77 (2020).

    Article  Google Scholar 

  31. Jackson, L. et al. Biodiversity and agricultural sustainagility: from assessment to adaptive management. Curr. Opin. Environ. Sustain. 2, 80–87 (2010).

    Article  Google Scholar 

  32. Laurent, A., Kyveryga, P., Makowski, D. & Miguez, F. A framework for visualization and analysis of agronomic field trials from on‐farm research networks. Agron. J. 111, 2712–2723 (2019).

    Article  Google Scholar 

  33. Kyveryga, P. M. On‐farm research: experimental approaches, analytical frameworks, case studies, and impact. Agron. J. 111, 2633–2635 (2019).

    Article  Google Scholar 

  34. Tremblay, N. in Precision Agriculture for Sustainability (ed. Stafford, J.) 145–168 (Burleigh Dodds Science Limited, 2019);

  35. Bullock, D. S. et al. The data‐intensive farm management project: changing agronomic research through on‐farm precision experimentation. Agron. J. 111, 2736–2746 (2019).

    Article  Google Scholar 

  36. Wyatt, J., Brown, T. & Carey, S. The next chapter in design for social innovation. Stanford Soc. Innov. Rev. 19, 40–47 (2021).

    Google Scholar 

  37. Griffin, T. W., Fitzgerald, G. J., Lowenberg‐DeBoer, J. & Barnes, E. M. Modeling local and global spatial correlation in field‐scale experiments. Agron. J. (2020).

  38. Coudel, E., Tonneau, J.-P. & Rey-Valette, H. Diverse approaches to learning in rural and development studies: review of the literature from the perspective of action learning. Knowl. Manage. Res. Pract. 9, 120–135 (2017).

    Article  Google Scholar 

  39. Browning, D. M. et al. Emerging technological and cultural shifts advancing drylands research and management. Front. Ecol. Environ. 13, 52–60 (2015).

    Article  Google Scholar 

  40. Maxwell, B. et al. Can optimization associated with on-farm experimentation using site-specific technologies improve producer management decisions? In 14th International Conference on Precision Agriculture (2018).

  41. Kindred, D. et al. Supporting and analysing on-farm nitrogen tramline trials so farmers, industry, agronomists and scientists can learn together. In 14th International Conference on Precision Agriculture (2018).

  42. Oberthür, T. et al. Plantation intelligence applied oil palm operations: unlocking value by analysing commercial data. Planter 93, 339–351 (2017).

    Google Scholar 

  43. Jin, H., Shuvo Bakar, K., Henderson, B. L., Bramley, R. G. V. & Gobbett, D. L. An efficient geostatistical analysis tool for on-farm experiments targeted at localised treatment. Biosys. Eng. 205, 121–136 (2021).

    Article  Google Scholar 

  44. Berthet, E. T., Hickey, G. M. & Klerkx, L. Opening design and innovation processes in agriculture: insights from design and management sciences and future directions. Agric. Syst. 165, 111–115 (2018).

    Article  Google Scholar 

  45. Curley, M. Twelve principles for open innovation 2.0. Nature 533, 315–316 (2016).

    Article  ADS  Google Scholar 

  46. Ryan, S. F. et al. The role of citizen science in addressing grand challenges in food and agriculture research. Proc. Biol. Sci. 285, 20181977 (2018).

  47. Herrero, M. et al. Innovation can accelerate the transition towards a sustainable food system. Nat. Food 1, 266–272 (2020).

    Article  Google Scholar 

  48. Fielke, S. J. et al. Conceptualising the DAIS: implications of the ‘digitalisation of agricultural innovation systems’ on technology and policy at multiple levels. NJAS 90–91, 100296 (2019).

    Google Scholar 

  49. Cook, S., Jackson, E. L., Fisher, M. J., Baker, D. & Diepeveen, D. Embedding digital agriculture into sustainable Australian food systems: pathways and pitfalls to value creation. Int. J. Agric. Sustain. (2021).

  50. van Etten, J. et al. Crop variety management for climate adaptation supported by citizen science. Proc. Natl Acad. Sci. USA 116, 4194–4199 (2019).

    Article  Google Scholar 

  51. Ingram, J. & Maye, D. What are the implications of digitalisation for agricultural knowledge? Front. Sustain. Food Syst. 4, (2020).

  52. McNee, M. Government Support for Farmer-Based Research in the Falkland Islands AAC Agenda 07.11.2019, Item 10 (Agricultural Advisory Committee, Falkland Islands Government, 2019).

  53. Zhang, W. et al. Closing yield gaps in China by empowering smallholder farmers. Nature 537, 671–674 (2016).

    Article  ADS  CAS  Google Scholar 

  54. Lechenet, M., Dessaint, F., Py, G., Makowski, D. & Munier-Jolain, N. Reducing pesticide use while preserving crop productivity and profitability on arable farms. Nat. Plants 3, 17008 (2017).

    Article  Google Scholar 

  55. García, F. et al. La Red de Nutrición de la Región Crea Sur de Santa Fe: Resultados y Conclusiones de los Primeros Diez Años 2000-2009 (AACREA, 2010).

  56. Posner, S. M., McKenzie, E. & Ricketts, T. H. Policy impacts of ecosystem services knowledge. Proc. Natl. Acad Sci. USA 113, 1760–1765 (2016).

    Article  ADS  CAS  Google Scholar 

  57. Moore, M.-L., Riddell, D. & Vocisano, D. Scaling out, scaling up, scaling deep. Strategies of non-profits in advancing systemic social innovation. J. Corp. Citizenship 58, 67–84 (2015).

    Article  Google Scholar 

  58. Payan, J.‐C. & Pichon, L. ApeX‐Vigne, Version 2020: Une Application Mobile Gratuite pour Faciliter le Suivi de la Croissance des Vignes et Estimer la Contrainte Hydrique (Institut Français de la Vigne et du Vin and Institut Agro, Montpellier SupAgro, 2020).

  59. Samberg, L. H. A collaboration worth its weight in grain. Nature 537, 624–625 (2016).

    Article  ADS  CAS  Google Scholar 

Download references


This study was funded by the Premier’s Agriculture and Food Fellowship Program of Western Australia. This Fellowship is a collaboration between Curtin and Murdoch Universities and the State Government. The Fellowship is the centrepiece of the Science and Agribusiness Connect initiative, made possible by the State Government’s Royalties for Regions program. Additional support was provided by the MAK’IT-FIAS Fellowship programme (Montpellier Advanced Knowledge Institute on Transitions – French Institutes for Advanced Study) co-funded by the University of Montpellier and the European Union’s Horizon 2020 Marie Skłodowska-Curie Actions (co-fund grant agreement no. 945408), the Digital Agriculture Convergence Lab #DigitAg (grant no. ANR-16-CONV-0004) supported by ANR/PIA, and the Elizabeth Creak Charitable Trust. Contributions toward enabling workshops were made by the USDA (USDA AFRI FACT Los Angeles 2017), the International Society for Precision Agriculture (ICPA Montreal 2018 OFE-C, On-Farm Experimentation Community), the National Key Research and Development Program of China (2016YFD0201303) and ADAS (Cambridge 2018), the European Conference for Precision Agriculture (ECPA Montpellier 2019) and the OECD Co-operative Research Program for ‘Biological resource management for sustainable agricultural systems – Transformational technologies and innovation’ towards ‘#OFE2021, the first Conference on farmer-centric On-Farm Experimentation – Digital Tools for a Scalable Transformative Pathway’. L. Tresh assisted with the design and preparation of Figs. 2 and 3. Members of the #OFE2021 Working Groups also contributed their experiences and insights.

Author information

Authors and Affiliations



M.L. and S.C. developed the study concept. M.M., D.G., J.I., V.B.-M., T.M., R.S.-B. and A.H. contributed additional concept development. M.L. and D.G. obtained the data and prepared the results. M.L., M.M., L.T., D.K., F.O.G., B.M., V.B.-M., J.R., C.H. and W.Z. contributed data. M.L. wrote the manuscript with input from all other authors.

Corresponding author

Correspondence to Myrtille Lacoste.

Ethics declarations

Competing interests

The authors declare no competing interests.

Additional information

Peer review information Nature Food thanks Carol Shennan, Petro Kyveryga, Nicolas Martin and the other, anonymous, reviewer(s) for their contribution to the peer review of this work.

Publisher’s note Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Supplementary information

Supplementary Information

Sources for Figs. 1–3.

Rights and permissions

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Lacoste, M., Cook, S., McNee, M. et al. On-Farm Experimentation to transform global agriculture. Nat Food 3, 11–18 (2022).

Download citation

  • Received:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI:

This article is cited by


Quick links

Nature Briefing

Sign up for the Nature Briefing newsletter — what matters in science, free to your inbox daily.

Get the most important science stories of the day, free in your inbox. Sign up for Nature Briefing