According to a study by the environmental organization WWF Germany, ten million metric tons of food are thrown in the garbage every year in Germany. This, although they might be still edible. A mobile food scanner will allow consumers and supermarket employees in to test whether food items have gone bad. The small, pocket-size device uses near-infrared measurements to determine the ripeness of the product. It shows the results via an software interface. Fraunhofer researchers developed the system, which exists in demonstrator form, together with partners in a project commissioned by the Bavarian Ministry of Food, Agriculture and Forestry.
Is this yoghurt still good? Are those vegetables still edible? When there is doubt, people tend to chuck food into the garbage. Many products are thrown out simply because they no longer look appetizing or have superficial blemishes, or because they are past their best-before date. In Bavaria alone, 1.3 million tons of food wind up in the garbage unnecessarily every year. Through the “We Rescue Food” alliance, the Bavarian Ministry of Food, Agriculture and Forestry wants to combat waste by means of 17 initiatives. One of the projects concerns a food scanner designed to help reduce waste at the end of the value chain – in stores and in the homes of consumers. In future, the inexpensive pocket-size device will determine the actual freshness of food, whether packaged or unpackaged. Researchers at the Fraunhofer Institute for Optronics, System Technologies and Image Exploitation IOSB, the Fraunhofer Institute for Process Engineering and Packaging IVV, the Deggendorf Institute of Technology and the Weihenstephan-Triesdorf University of Applied Sciences are developing the compact food scanner, which has been built as a demonstrator with data for two foodstuffs and also permits the shelf life of products to be estimated.
Infrared light to determine the authenticity of food
The heart of the mobile scanner is a near-infrared (NIR) sensor that measures the ripeness of the food and identifies the amount and composition of its contents. “Infrared light is beamed with high precision at the product to be checked and then the scanner measures the spectrum of the reflected light. The absorbed wavelengths allow us to make inferences about the chemical composition of the food,” explains Dr. Robin Gruna, project manager and scientist at Fraunhofer IOSB.
“In the laboratory, we’ve long been able to quantify individual components using near-infrared spectroscopy. What’s new is that this can now be done with small, low-cost sensors,” adds Julius Krause, a member of Gruna’s team. “Foodstuffs are often counterfeited – for example, salmon trout is sold as salmon. Once suitably trained, our device can determine the authenticity of a product. It can also identify whether products such as olive oil have been adulterated,” says the physicist. But there are limits to the system, too: It can only evaluate the product quality of homogeneous foods. At present, it struggles to inspect heterogeneous products containing different ingredients such as pizza. To this end, the scientists are investigating high-spatial-resolution technologies such as hyperspectral imaging and fusion-based approaches using color images and spectral sensors.
To be able to determine the quality of food based on the sensor data and the measured infrared spectra and compute the shelf life predictions, the research teams are developing intelligent algorithms that search for telling patterns and regularities in the data. “Through machine learning, we can increase the recognition potential. In our tests, we studied tomatoes and ground beef,” says Gruna. For example, we used statistical techniques to correlate the measured NIR spectra of ground beef with the rate of microbial spoilage and derived the remaining shelf life of the meat from the results. Extensive storage tests, whereby the research teams measured microbiological quality and other chemical parameters under various storage conditions, showed good correlation between the computed and actual total germ counts.
Source: Frauenhofer Institute, Germany | Picture: Frauenhofer Institute
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