Industry Projects

Machine Learning Project

Home Industry Projects Machine Learning Project

The Thomas Elder Institute is partner in the Grains, Research and Development Corporation (GRDC)  funded, University of Adelaide-led project which uses machine learning to extract maximum value from soil and crop variability data. 

At a glance

  • Project name: Machine Learning to Extract Maximum Value from Soil and Crop Variability
  • Partners:
    – The University of Adelaide’s School of Agriculture, Food & Wine (AFW), Australian Plant Phenomics Facility (APPF), Australian Institute for Machine Learning (AIML) and Teletraffic Research Centre (TRC).–  Australian Grain Technologies (AGT)–  Agronomy Solutions

    –  Centre for eResearch and Digital Innovation

    –  (CeRDI) at Federation University Australia

    –  Consilium Technology Pty Ltd

    –  Precision Agriculture Pty Ltd

    –  Riverine Plains

    –  South Australian Research and Development Institute (SARDI)

    –  The University of Queensland 
  • Project commenced: 2019
  • Project ends: 2021
  • Objective: use machine learning to discover how weather and soil affects yield of broadacre cropping.

How the project works

Machine-learning techniques investigate weather and soil constraints contributing to variability in yield from broadacre cropping enterprises.  The Institute is working closely with leading Elders agronomists and their clients to provide real-life data into the machine-learning processes.

aerial-image-of-grain-field-being-harvested

Harvesting a broadacre cop.

Learn about our other industry projects.

Need more information?

For more information including how you can partner with us, please call Dr Michael Wilkes, Head of Thomas Elder Institute on 0438211247.

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