The four steps are:

● Collection of the right data for all the physical on-farm variables in the required resolution and quality.

● The automatic transfer of data collected to an analytical platform in a safe and timely manner

● Analysis tools that process a succinct answer/solution in a form that is easy for farmers with little or no experience to interpret.

● Autonomous execution of a response, with greater speed and accuracy than traditional execution techniques.

Lead author and Rabobank agricultural analyst Wes Lefroy said initially the benefits would be improved decision-making and increased return on investment in new technologies but over time he believes this approach will be a game changer for agricultural supply chains.

“On farm, the complexity of decision-making has been increasing for some time, driven by factors such as growing farm size, changing climate and increasing regulation,” he said.

“More and more commonly, we’re seeing farmers having to make decisions with a lower level of confidence and, for many, these are complex decisions about situations they haven’t had to face in their entire careers.

“The intellectual power to optimise many on-farm decisions has now moved beyond human capacity and there is greater need for technology to play a central role.”

Mr Lefroy said for many farmers and farm input companies, extracting value from existing technologies required significant investment of funds and time, as well as technical expertise.

“This has seen very few farmers reporting increased financial returns as a result of the use of technology,” he said.

“Two major hurdles have been limiting the capacity of technology to play a fundamental role in farm decision-making.

“Firstly, technologies have lacked the ability to collect data from the required number of variables.

“For example, when farmers are making decisions about nitrogen applications, they are having to estimate current plant nitrogen status and responsiveness to additional applications, as we do not have the tools to measure all the factors that influence those variables in a cost-effective manner at a high spatial resolution.

“Secondly, in many cases, analysis tools do not account for different relationships between these variables.

“The actual process of collecting data, analysing it and acting on it is arduous and complex, which limits return on investment and increases the opportunity cost.”