On-Farm Experimentation

This project will develop new data analytics methods for farmer implemented trials that account for spatial variability across paddocks and generate value through data driven decisions.

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 Solution

This project aims to unlock the value of collected data by placing it in the hands of producers through on-farm experimentation (OFE). OFE is a grower-centric process to test management practices on farms at large scale. It represents an opportunity to overcome the disconnect between growers and researchers by embedding growers and their advisors throughout the research process and by developing research questions directly relevant to their farm at the scale at which they make management decisions (i.e. paddock scale).

Engagement by everyone involved is critical to the success of OFE. It also represents an opportunity to make use of currently under-utilised existing on-farm digital technology at little to no extra cost to growers.

This project applies the principles of OFE in the context of the Western Australian grains industry. The project team will build systems to help connect growers and their data, so that they may interpret trial results with confidence and use these to make more informed management decisions.

This will be achieved through three focused areas of activity: research capacity building, method development using data analytics (demonstration of application), and high-throughput analysis capability (platform development with NGIS).

By building this system collaboratively and from the ground up, growers will be empowered in their management of farm inputs and resources, resulting in improved economic and sustainability outcomes across the Western Australian grains sector. The rollout will mimic growers’ own principles of continuous improvement by informing decisions progressively through our partnership with key stakeholders across the value chain.

The image above shows on-farm trial analysis for a simple nitrogen application trial:

a) Top LHS: Treatment strips (Flexi-Napplied l/ha)

b) Top RHS: Crop yield following resampling at 10x10m grid

c) Bottom LHS: Response of crop yield (kg) increase with every litre of Flexi-N applied, as generated by geographically weighted regression analysis, and

d) Bottom RHS: gross margin (ROI of fertiliser applied) based on predicted yield for each treatment ($/ha)   

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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