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
status icon Completed

GRDC News

Resources