This project was completed in February 2024. Read the final report.
This project has made significant progress in developing and refining Soli, providing a valuable platform for reporting and actioning spatial soil data and variable rate amelioration.
It has also provided regional soil data insights using aggregated data, and has contributed to the on-going research on SOC, its measurement and management.
Soil management is complex and farmers need intelligence to improve the health of their soil. Furthermore, farmers wishing to be involved in carbon markets are unable to easily provide an evidence base.
Precision Agriculture wanted to improve and optimise the way in which reports and mapping tools are created by bringing together all the information into one platform (Soli™️). This project aimed to provide a timely and simplified, minimal manual intervention process to generate soil health reports from multiple data sources and insight tools.
Research aimed to provide new analytical insights previously unavailable in the industry, as well as relevant recommendations to facilitate meaningful customer discussions.
By developing new analytical insights that allows current datapoints to be compatible with one another, Precision Agriculture will be able to streamline its reporting process to provide customers a better understanding of their soil health.
This includes understanding a farm’s potential for carbon storage, an emerging industry in Australia’s approach to managing the impact of climate change.
One of the key industry metrics for the project was the ability to generate spatial soil reports and variable rate soil amelioration recommendations in a timely fashion.
Three key reports are now automatically generated by Soli™️ providing significant value to farmers in the interpretation of their data as well as value to Precision Agriculture in being able to quickly generate the reports.
These reports were:
The project also conducted regional benchmarking, leveraging the extensive Precision Agriculture dataset that includes detailed sub-paddock variation data through grid soil sampling. Key findings revealed significant pH variation within paddocks and across the study region.
The project investigated SOC at the sub-paddock scale and its correlations with other surface soil characteristics. Results showed significant within-paddock variation in SOC, with inconsistent relationships between SOC and other soil characteristics across different paddocks.
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