Investment
Investment
GRDC Code: UOS2002-002RTX
Machine learning to map soil constraint variability and predict crop yield
This project will use a variety of Machine Learning techniques to bring together previously underutilised on-farm, satellite, and weather data and better predict expected crop outcomes. Tools to map fine-scale 3D-variability of agronomically important soil properties (such as depth to chemical/physical barriers and plant-available water-content) and to forecast crop yield variability in-season will be developed, improving management and profitability.
- Project start date:
- 17/02/2020
- Project end date:
- 31/10/2021
- Crop type:
-
- Wheat, (Cereal)
- Organisation
- University of Sydney
- Region:
- North, South, West
- Project status
- Completed
GRDC News
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