Bühler’s NIR Multi Online Analyser monitors moisture, protein and gluten in grains and flours, as well as ash content, water absorption and starch damage

deliver food to supermarkets that meets quality requirements and that won’t be wasted because it’s left unsold. Wilson commented that food

production projects Scorpion Vision is involved with are continuing during lockdown, but that social distancing is causing some practical problems. He said: ‘There are definitely more discussions around automation. I think there was always a high level of interest, but implementing something is another story. I think there will be a rapid growth in automation for food production once we all get to grips with our new normal.’ Lambrecht said that there

are many more applications where vision can be used to process fruit and vegetables. She said that the development and improvement of neural | @imveurope

networks will make a big difference, especially for processing vegetables like broccoli, cauliflower and mushrooms that are more difficult to automate. ‘We see major benefits to

combining neural networks with 3D image processing,’ Wilson said. ‘There are lots of areas where this is really good for us and many not so obvious benefits which will have a real impact. I think food production is going to be one of the biggest winners in this regard.’ There are also advances being made in imaging outside of the visible spectrum. Mike Grodzki, a product manager at Teledyne Dalsa, said the firm has had customers in food production asking for SWIR cameras for a while for detecting foreign contaminants in food. Teledyne Dalsa now

supplies its Linea SWIR InGaAs line scan camera. ‘Sticks and stones might be difficult to visibly distinguish from raisins, for example, when they’re flying down a chute. In the visible spectrum they might all just be brown, but not so in the SWIR,’ Grodzki said. ‘SWIR cameras are also great for detecting bruising in fruit. Those ugly, bruised fruits aren’t wasted – they get used for things like jams, and preserves, or they get chopped up and sold in frozen packs of fruit.’ There are also vision

systems employed in packing food for supermarkets. The UK supermarket Morrison’s installed two Brillopak robotic potato loading cells at its fresh produce depot in Rushden, Northamptonshire. The two UniPaker robot cells can load 75 packs of potatoes per

minute into crates ready for distribution. Vision is used to identify the location of each pack for the robot arms to pick them up.

‘Vision is a strategic focus

for Brillopak,’ the company’s director, David Jahn, told Imaging and Machine Vision Europe. Brillopak has now developed its own vision system and is involved in a number of development projects using vision and robotics. The firm also has a new QA

vision system to support its UniPaker robotic apple packing solution. The vision system identifies and rejects packs of apples containing cut apples, or those with the incorrect number of apples. It also reads information like the use-by date. Brillopak expects to roll out this system across all its sectors shortly, Jahn said.



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