Growers urged to share data
A digital revolution in agriculture is well under way, even if farmers are uncertain how to benefit from the big data at hand.
But it is a matter that researchers behind WA’s Centre for Digital Agriculture hope to change.
The centre, headed by Premier’s Fellow in Agriculture and Food Simon Cook, is a collaboration between academics from Murdoch and Curtin universities.
They are hoping to harness the natural curiosity of growers, and their keenness to experiment on farm, as part of a new big data approach to agriculture research.
Professor Cook said the aim of the On-Farm Experimentation project was for researchers to learn alongside growers.
“In a digital world, we need to find a different approach to agriculture research,” he said.
“This is a business development approach rather than a scientist telling growers what to do.”
Data can be analysed to reveal patterns, trends and associations that can be used to improve on-farm practices.
In the OFE project, participating growers carry out and analyse their own farm-scale experiments using yield data collected annually by their harvesters.
Professor Cook said the project also aimed to form networks for on-farm experimenters to share results with their fellow farmers, thereby building bigger datasets for use in tackling problems.
“We have found that more than 90 per cent of farmers experiment, and roughly 100 per cent have the technology to record it but only about 20 per cent capture the data,” Professor Cook said.
“So we are putting those two things together — the natural curiosity of growers and their keenness to experiment with the technology that’s in their header and not largely used.”
Professor Cook said the aim was for growers to alter one aspect of their farming system, such as their fertiliser, chemical, crop variety or cultivation practice, and measure the yield response.
The OFE project, which is preparing for its second year, recently finalised results from its first trial in 2018, the result being an alteration to the rate of fertiliser being applied.
“The trial results showed great variation in soil nutrition in the paddock and allowed farmers to better understand their land and how treatment can improve their soils,” Professor Cook said.
The researchers are also keen to build third parties into their experimentation network.
“What we are trying to develop are business models, whereby farmers and their advisers or suppliers learn how to get the system working better with the data,” Professor Cook said. “So we are talking to bodies such as CSBP, NGIS and the Department of Primary Industries and Regional Development, growers groups and those who might want to work with growers to get value out of the data.
“But the key point is the data starts with the grower, so we are always careful the data does not flow out of the control of growers and that they are involved in this process the whole way.”
The CDA is not the only body weighing into the future in big data, with the Grains Research and Development Corporation also investing in research projects that involve machine learning.
GRDC enabling technologies senior manager Tom Giles said machine learning could be a powerful way for the grains sector to analyse data.
“It can help tackle previously intractable problems such as providing accurate establishment, growth stage, head count or crop health estimates for broadacre crops,” he said.
It can also be used by growers to estimate in-crop frost damage in real time and manage fertiliser application rates.
“The GRDC has identified machine learning as a foundational technology with the potential to deliver value to Australian grain growers,” he said.
For more information on the OFE project, or to participate, email email@example.com.
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