PRECISE

ongoing

A freshness sensor for meat and fish It will soon be possible to determine the exact shelf life of meat and fish with a sensor, thus saving tons of food to be thrown out. In the Precise project, a consortium of researchers in the German-Danish border region is working on such a sensor for different types of fish and meat. Meat and fish production contributes greatly to CO2 emissions and not sustainable food consumption. On the other hand, meat/fish production is important regional economic activities. Precise proposes a model to reduce the carbon footprint of meat/fish consumption by eliminating unnecessary food waste. Today, restaurants and food stores rely on the printed “best before” date for meat and fish products, which is based on shelf life estimation curves for meat and fish degradation. For cuts of pork at 5 °C, the curve shows a shelf life of 8 ± 3 days. To be on the safe side, the shelf life date is set at 5 days, leading to a huge food waste of 48.000 tonnes per year in Schleswig-Holstein/South Denmark/Sjælland combined. Meat/fish pieces are purchased with a ‘best before’ date and dealers/restaurants can legally extend this date if the product is still fit for consumption. Today, the only possible way to do so in this part of the value chain is to use the human senses to evaluate freshness, and doubt leads to waste. An instrument is needed to provide an objective and reliable measurement of the freshness of food and eliminate doubt and waste. Collaboration leads to database for different types of fish and meat In order to improve the treatment and consumption of these raw materials, we propose to implement a sensor that enables PRÆCIS to measure meat and fish shelf life, which can prevent 50 % of meat and fish waste. Our starting point is the current meat freshness sensor developed by the partners. This solution can measure product refreshness indices, but due to limitations in sensor elements, databases and AI algorithms, it currently only works for 4 types of meat/fish types. Precision will maximise the impact of such a solution by expanding the library of meat/fish types. It requires innovative expertise to implement a new type of sensor element, to perform advanced AI data analysis, and to calibrate the sensors with accredited quality methodology. Our composition of network partners who are responsible for the sale of meat and fish in the food value chain will continuously assess our results. The project aims to achieve the following objectives: Databases for beef and chicken measurements 50 different sensors provide exactly the same measurement Measurements on fresh meat Databases for measurements of 11 different kinds of meat and fish Intelligent electronic nose that can be used in restaurants and shops

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