US00087 - A platform to interpret soil attributes to support profitable farming systems

Project Summary

Project Start Date
10 June 2017
Project End Date
30 June 2020
Supervisor Name
Alex McBratney
University of Sydney
This innovation will deliver platforms for fine scale mapping of soil attributes to provide reliable real-time information to growers to support their decision making processes. Profitable farming systems depend on high quality data, including soil data, to manage annual agronomic decisions affecting crop performance. This good soil management will also secure soil production potential into the future, reducing long term risk. Developing this system requires soil and its related data to be measured at a finer scale than is currently feasible for farming systems relying on data derived from traditional soil laboratory techniques. The reduced cost of generating this data will increase the growers' ability to assess variability in the field and support precision agriculture approaches to reach their full potential. While a number of sensors have been developed to measure soil properties quickly, cheaply and in situ, the current investigations have focused on a single or small number of properties, or developed calibrations that are only suitable for a given region or soil type. There has also been no explicit linkage to any interpretation of the agronomic impacts of the measured properties. This research will fill these gaps by developing calibrations for proximal soil sensor measurements and connecting sensor derived properties with the wealth of information held in pedotransfer functions through the use of a spectral inference system. Much of this work will be automated and will culminate in the production of a standardised report presenting key soil attributes in an easily interpretable way.
Published Date
14 February 2018

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