• Charles Sturt University and industry research partners SunRice and Food Agility CRC deliver online tool to assist farmers to make better crop and pasture management decisions
• Researchers developed the new CLOWD apps to provide easily accessible historical data, cumulative rainfall data and ‘growing degree-days’
• CLOWD is free to use and requires no sign-up

A Charles Sturt University postdoctoral researcher has developed apps to put historical and recent climate data and analysis at the touch of a button for farmers.

The Combined Location Online Weather Data (CLOWD) apps for both computer and mobile phone  enable farmers and growers to analyse recent and historic weather for any location in Australia at the touch of a map.

Researcher Dr Darren Yates graduated in 2021 and is a postdoctoral scientist in the Charles Sturt School of Computing, Mathematics and Engineering and in the Charles Sturt Gulbali Institute of Agriculture, Water and Environment. He is based in Bathurst NSW.

It is part of a Food Agility CRC collaborative research project with Charles Sturt University, SunRice and AgriFutures Australia.

The data used by the apps is from publicly available sites such as the Queensland ‘long paddock’ historical climate data.

“Our goal for CLOWD is to provide farmers and growers with targeted weather analysis in a form they can use wherever they are,” Dr Yates said.

“What we have done is make the data more accessible, and we’re working with industry partner SunRice to test it with farmers.

“There’s a wealth of historical weather data available but it’s difficult for farmers to access for their locations, as you often need to know the precise latitude and longitude for your farm.

“We developed a web-based app whereby a farmer can click on a map to bring up historical and recent data, but it also has data such as cumulative rainfall and growing degree days which are extra features that farmers can use to help make better crop and pasture management decisions.”

Dr Yates explained that after he and colleagues completed another project task ahead of schedule the project lead Professor in Food Science Chris Blanchard in the Charles Sturt School of Dentistry and Medical Sciences encouraged them to look at other potential areas where they could help rice growers.

He said the idea for CLOWD came from a discussion with Charles Sturt PhD student in the project Mr Allister Clarke who developed the machine-learning model that predicts rice/whole grain yield using rice phenology (growth stage) data and weather data.

The researchers examined the Queensland Department of Environment and Science service called SILO (Scientific Information for Land Owners), a weather database for Australia dating back to 1889 which records temperature, rainfall, humidity and a range of other daily observations from weather stations around the country. While some SILO weather data is interpolated (meaning it is derived mathematically from results of surrounding locations), interpolated data can still hold value for the farming community.

“One parameter that SILO doesn’t provide is ‘growing degree-days’ (GDD), which is like a heat-odometer for plants – it’s a temperature-based mathematical calculation and that was the start of what became CLOWD,” Dr Yates said.

“But we also realised there was potential for CLOWD beyond rice, as GDD is calculated differently for different crops; rice is the default crop setting for CLOWD, but the user can custom-select from a range of crops, including barley, peanuts, wheat, cotton, fruits and more.

“From there, one idea led to another; we started with creating analysis and comparison of the current season’s weather observations against other seasons or a rolling five-year average.

“However, because a number of the measurements can be cumulative (such as rainfall and GDD), we added the ability to ‘zero’ or start that analysis from any calendar date ─ the growing season rarely starts on the first of January.”

Dr Yates said because not everyone is good with charts, they included the option to turn the charts into plain-English text using a software concept called ‘natural language generation’.

“That led to another feature that combines the analysis charts and text into a summary PDF report users can create on-demand on their device,” he said.

“Then, as some crops, such as rice, can be adversely affected by cooler temperatures, we added an auto-alert system that warns the user the next time they use the app.

“Charles Sturt University colleagues Professor Zahidul Islam and Dr Sabih Rehman provided invaluable feedback on the technical data side, SunRice and Mr Russell Ford provided excellent feedback on our design and encouraged us to create a version for smartphones, which we did.”

CLOWD is free to use and requires no sign-up.

Food Agility CRC chief scientist, Professor David Lamb, said it is an example of the substantial uplift that can be given to already-existing databases and products, to deliver even more effective services to growers.

“It isn’t about re-inventing the wheel,” Professor Lamb said. “The team listened to producers and SunRice and focussed on filling the gaps, in this case ‘growing degree days’.”