Funded by the Potato Council UK, the University of Lincoln and Sutton Bridge Crop Storage Research (SBCSR) have utilised consumer-grade computer systems to develop an intuitive technology that uses artificial intelligence algorithms to learn visual cues such as size, colour, texture and shape in real-time.
“This autonomous technology is able to identify conditions such as Black dot, Silver scurf, Common scab and greening, which will without a doubt have a significant impact on the future of potato packing, distribution and ultimately the end product purchased by the consumer,” said Ausveg spokesperson Felicity Powell.
Following the success of the prototype system, the UK Technology Strategy Board (TSB) has agreed to fund a project to develop commercially viable systems. The researchers are also exploring opportunities to adapt the software for crops other than potatoes.
Potato Council UK pathologist, Dr Glyn Harper, hopes that the technology would be further developed for different image types and other sensor data such as colour images, X-ray and 3D scanning to extend the scope of defect and disease identification.
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