IP3: Impulsprojekt 3: Datenanlyse und autonome Prognostik zur Verbesserung der Transparenz und Sicherheit von Lebensmitteln
Individual risks of spoilage and exposure to harmful substances arise from natural fluctuations in raw material quality and changing environmental conditions during the production process of food. The best before date, however, is determined by the manufacturer in very general terms for the production process based on a recipe. Batch- or even product-specific shelf life specifications cannot be implemented with the methods currently utilised in industrial practice because they involve lengthy storage trials. Even checks for contamination are generally not carried out individually on all products, because laboratory analyses are time-consuming and costly. This project will explore innovative modelling technologies based on rapid data acquisition and analysis for more accurate prediction of the best before date. Low-cost sensor technologies are utilised to provide comprehensive results of the condition for each individual product.
Innovative technologies using information fusion and machine learning can help to reduce food waste by accurately predicting the best before date printed on food packaging. Furthermore, the for this purpose necessarily integrated real-time quality control systems make a valuable contribution to food safety during production.