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The Manufacturing Technology Centre has built a learning robot that could benefit agriculture


landscape, via firms such as Fotenix and Cambridge, UK-based agri-tech start-up, Outfield Technologies. It was established by co-founders Jim McDougall and Oli Hilbourne to build systems that help fruit growers be more productive, more sustainable and more environmentally friendly. Having collaborated with Cambridge University’s Machine Intelligence Laboratory, the company now offers a yield-measurement and orchard- management system for high-value fruit crops. One of the key issues Outfield helps


to address is accurate yield estimation in orchards. McDougall, who is also commercial director, explained: ‘Te ability for growers to manually manage the number of apples, for example, is not an easy task.’ Yield management based on manual


estimation can be affected by a number of factors; apple trees can be unpredictable. ‘If a grower has an orchard with 10,000 apple trees, that is a lot of variability and estimates can often be out by around 20 per cent,’ McDougall added. ‘Tis results in lost income and inefficient operations for the growers. It can also produce substantial food waste.’ Outfield’s technology can help by


analysing images taken in orchards, counting how many blossoms there are on the trees and estimating fruit yields. ‘We can manage the number of apples more precisely, depending on the amount of apple blossom, for example,’ said McDougall. Te images are captured by off-the-shelf


drones, and Outfield analyses the imagery using machine learning to provide detailed maps of fruit loading and fruit counts, to helps growers visualise and track the parameters that matter to their particular orchard or farm. ‘Te drones are very cool,’ enthused


McDougall. ‘We don’t think anyone else is currently doing it. You can tell them where to fly, and they capture the aerial view images of orchards, and the secret sauce is


www.imveurope.com | @imveurope vision.vieworks.com vision@vieworks.com


our online platform that looks at the image to detect each blossom or piece of fruit, to calculate how many there are.’ Bringing this kind of technology from the


research environment to the commercial arena is not without its challenges. McDougall explained: ‘A lot of early agri- tech companies struggle finding the right skillset, because it is so specialist. Ten there are the challenges associated with getting the technology onto the farm. Something that works in a laboratory may not work in an agricultural environment. ‘Tere are some great growers in the UK,


C M Y


but every farm is different in terms of scale, market and crops. ‘But then, that’s why agri-tech drives


CM MY technology. If something works on a farm,CY


‘Tat’s why agri-tech drives technology. If something works on a farm, it will work anywhere’


CMY K


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17 & 31 Megapixel Cameras


it will work anywhere, and people are really keen to see things like this work.’ McDougall agrees that the fourth


agricultural revolution will see robotic and machine vision technology implemented quickly. ‘Tere will be a huge acceleration in the


coming years,’ he said, ‘which will lead to a confluence of different things that we can do, and growers will be able to take a more strategic view.’ He also concurs that the fourth


agricultural revolution has its part to play in helping reduce some of the chemical damage caused during the third iteration. ‘We will certainly see more precision- spraying robots,’ he said. ‘Tis type of technology can help to reduce any further damage to the planet, and not before time. We’ve got to sort this out now, and technology is the only way.’ O


(Sony IMX 342) VC-31MC/X


MTC


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