Global competition, high production costs and a lack of subsidisation are just some reasons proponents of digital agriculture feel Australian farmers need to embrace new technologies in order to remain competitive.
Speaking at the Grains Research Development GRDC update at Goondiwindi, Qld, University of Sydney, Associate Professor Brett Whelan said there were huge resources of data and information available which could be used by farmers to inform their decisions.
"The cost to get this data has come down, so the ability to access it from third party providers is really cheap these days," he said.
"There is a pool of available off-farm data that can be combined with the data farmers have already been gathering," he said.
The cost to get this data has come down, so the ability to access it from third party providers is really cheap.
- Brett Whelan
"It is this combination that really provides value."
Assoc. Prof Whelan said simple products such as Google Earth imagery could be used to help farmers investigate what was constraining production on their farm, while other publicly available data included vegetative indexes, gamma radiation and soil data.
"Elevation data we get off navigation systems can be used in broadacre agriculture, and its fantastic high quality information, the way water moves around the landscape, the way soils move around the landscape.
"Combining all this information with your yield data provides insights into the relationships between the environment and our yield.
"I still don't know why yield data is not more utilised, it is a bench marking tool, it is a diagnosis tool, it tells you how well you operate as a business or as an advisor, it is just crucial."
Assoc. Prof Whelan said increasing public access to data sets could help farmers in tangible ways, such as increasing the accuracy of weather forecast models.
"There is obviously a whole raft of rainfall data stored on peoples farms,we need a mechanism for the industry to get rainfall data into a system" he said.
Assoc. Prof Whelan said he was involved in a project funded by the GRDC that was looking to take this data to the next level, by incorporating machine learning and data exploration tools.
"We have computer power and models to predict what is going to happen, to help us diagnose issues and to help us think about the future," he said.
