Produce Processors May Soon Reap The Fruits Of Automation
By Isaac Fletcher, contributing writer, Food Online
Through various stages of robotic machinery, a new pick and pack system may soon allow produce processors to automate packaging, inspection, and other production tasks by overcoming the automation challenges faced in the past
Researchers at Wageningen University and Research Center in the Netherlands are contributing to the ongoing effort to bring automation to more parts of the food processing industry. The research has been focused on developing an automated machine that can work with products that vary greatly in shape and size, as is the case with many food products. The PicknPack, as it has been named, will be able to package, inspect, and classify produce, as well as be adapted to accommodate a wide range of produce and batch sizes.
An important element of the system is its ability to create plastic packages on site as part of the production process. This ability will provide food processors a boost in efficiency as they will no longer be forced to order and store various unique packages for each of retail customers. The packaging system functions by using a vision-controlled robot to pick produce from a harvest bin and place it into a package that has been molded from a flexible molding concept piece.
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Once filled, the packages will be moved to an inspection station where sensors will image each item and evaluate the quality, size, color, shape, and maturity of the produce and then classify them with grades. Because color is an important measure of the ripeness of produce, the inspection sensors will employ a four band RGBi (red, blue, green, near infra-red) camera and two hyperspectral imagers to acquire data on color, color changes, water content, and fat or protein content.
In addition to the inspection sensors, the system is also equipped with a triangulation-based laser scanner, allowing it to capture three-dimensional images of the produce. Using these images, the system can evaluate the uniformity of the produce and identify any deformities. As an added benefit, the 3-D data can also be used to calculate the volume and weight of the produce. To identify any internal defects, such as air spaces, the inspection station will also use X-ray technology to find any defects or contaminants.
After successfully passing inspection, the packages of produce are ready to be sealed, which is done by a robotic system placing a sheet of plastic film over the package and sealing it with a laser. Once sealed, a label is placed on each package indicating its weight, quality, and any other retailer-specific information that may be needed.
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The researchers hope to have the PicknPack system completed by Sept 2016. Currently, there are no plans to commercialize the system, but the research results will be able to provide important insights as to how this type of technology could shape the future of food inspection and packaging. Indeed, with systems like the PicknPack, food producers would be better equipped to overcome the various hurdles encountered when working toward automated processes.