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Aberdeen University and Angus Soft Fruits team up on yield forecasting tool

The tool will help growers better predict soft fruit yields.
The tool will help growers better predict soft fruit yields.

A new soft fruit yield forecasting system is being developed by Aberdeen University in collaboration with a leading Scottish fruit company.

Data scientists from the university have teamed up with Arbroath-based Angus Soft Fruits Ltd and The Data Lab – Scotland’s innovation centre for data and artificial intelligence (AI) – to build an AI system to help growers more accurately predict soft fruit yields.

The system will bring together a range of information – including historical yield and weather data, weather forecasts and satellite imaging, and expert knowledge from growers – to develop algorithms that accurately forecast production.

The project’s partners say the tool could potentially save Scotland’s soft fruit industry – which produces more than 2,900 tonnes of raspberries and 25,000 tonnes of strawberries annually – millions of pounds every year.

Angus Soft Fruits Ltd’s technical director, Jan Redpath, said accurate forecasting was crucial at a time when growers are facing tight margins.

“On the one hand we have soaring costs in particular labour and fertilisers, and on the other our biggest ability to influence price comes from being able to accurately match supply with demand, or at least to better pre-empt the scale and timing of flushes and dips in crop production,” said Mr Redpath.

Rising labour costs are hitting fruit growers.

“Research into more accurate forecasting is required more than ever, and we are excited to work with the University and The Data Lab on what we see as a vitally important project, that has the potential to bring lasting benefits to our growers.”

George Leontidis, director of Aberdeen University‘s Interdisciplinary Centre for Data and Artificial Intelligence, said the forecasting tool could be a game-changer for the industry.

He said: “Over the three-year lifespan of this project we will work with growers to understand the flaws in current forecasting systems, develop advanced machine learning models that harness high quality data, and seek expert input from growers that can further enhance these models.

Georgios Leontidis from Aberdeen University.

“The ultimate aim is to produce an inexpensive yield forecasting system that brings all of this high-quality data together, providing maximum advantage for growers and helping them to stay in profit and protect jobs.”

Heather Thomson, head of skills at The Data Lab, said it was more important than ever to better understand crop performance as growers work to increase yields while limiting waste and their impact on the environment.

She added: “AI will play a significant role in this and projects like this one will reinforce Scotland as a leader in implementing innovative AI solutions.”

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