Digitalization of food waste valorization: Application of machine learning tools in optimizing the composition of functional food products (DigitFoodWVal)

The digitalization of food waste valorization represents an innovative and multidisciplinary approach that connects food technology, data analytics and sustainable production. Using advanced technologies such as membrane filtration, NIR spectroscopy, chemometrics, artificial neural networks (ANN) and 3D food printing, the project enables the transformation of by-products such as whey and fruit/vegetable peels into high-value functional food ingredients. Membrane processes enable the isolation of whey proteins while preserving functional properties, while NIR spectroscopy and chemometrics enable rapid, non-destructive and precise real-time quality control.

The proposed research promotes the circular bioeconomy and digital transformation of the food industry, addressing challenges such as waste reduction, food safety and personalized nutrition through the application of advanced technologies and sustainable solutions.