Machine learning to extract maximum value from soil and crop variability

Ongoing

Project Timeline: 2019 - 2021

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University of Adelaide
CerDi logo
CerDi

By 30 June 2023, Australian grain growers have access to Machine Learning models of crop/soil variability, drawing upon multiple data layers. Improved decision-support arising from this technology leads to a benefit-cost-ratio of at least 4:1 returned from GRDC investment. The project outcomes will inform growers, pre-breeders and breeders about which mapping data layers are of most value for a particular environment and the minimal number and type of layers to prioritise for maximum return on investment. This will assist with the collection of mapping layers in the future, including projects funded by GRDC, by helping to minimise unnecessary data collection for traits found to provide no additional value to outcomes.

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