On-Farm Experimentation

Grower driven experimentation and development of a new tool that accounts for spatial variability across paddocks to generate value through data driven decisions.
Project complete

In Partnership With:

Curtin University of Technology
WA Department of Primary Industries and Regional Development
NGIS Australia Pty Ltd
Grower Group Alliance

On-Farm Experimentation

The Challenge

Grain farmers have access to large amounts of their own data, are aware of its value but are often unable to realise the value of their own data. While digital technologies and data management systems offer great promise for the future of on-farm decision making, there are currently many barriers to adoption, including the digital divide.

Currently, many farmers make management decisions based on strip trials and yield monitor data. Growers have always trialled altering input rates or frequencies for specific plots, but have lacked the means to precisely analyse the data that comes from these trials, which does not account for the spatial variability of crop production.

The Outcomes

Farmers, agronomists, researchers, and technologists worked hand-in-hand in this three-year project to develop grower-driven experimentation and test the On-Farm Experimentation Platform. The OFE Platform, developed by NGIS, uses new spatial analytics methods that help farmers translate outcomes from experiments on small plots across the paddock to maximise return on investment for fertiliser.

Using this platform, team supported farmers to run 50 paddock-scale trials focussing mostly on fertiliser inputs. This provided an estimate on the return on investment of input costs and seasonal risk, giving farmers and their agronomists greater confidence to implement new fertiliser strategies.

Key outcomes include:

• The grains industry will be able to undertake trials with minimum input from specialist researchers through the adoption of the OFE Platform

• The partnership between researchers and industry has confirmed interest in using on-farm experimentation in conjunction with robust statistical analysis to reduce the risks associated with on-farm innovation.

The team is working on the next stage to develop the analytics capability, refine the platform and make it more widely available through NIGIS.

Final Report

Download the final report (PDF)

Case Study Booklet

Download the booklet here (PDF)

To get involved

Contact Food Agility or Project Lead, Julia Easton.

meet the team

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Fiona H. Evans, Angela Recalde Salas, Suman Rakshit, Craig Scanlan and Simon Cook, Assessment of the use of Geographically Weighted Regression (GWR) for analysis of large on-farm experiments and implications for practical application. Agronomy  10  (11). (DOI  10.3390/agronomy10111720)

Simon Cook, Elizabeth L. Jackson, Myles J. Fisher (In Memoriam), Derek Baker, Dean Diepeveen. Embedding digital agriculture into sustainable Australian food systems: pathways and pitfalls to value creation, International Journal of Agricultural Sustainability. (DOI: 10.1080/14735903.2021.1937881).

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