Neue Publikation in MDPI processes [05.09.22]
Christian Krupitzer und Tanja Noack und Christine Borsum vom Fachgebiet für Lebensmittelinformatik ist Co-Autor der Publikation "Digital Food Twins Combining Data Science and Food Science: System Model, Applications, and Challenges" in MDPI processes (Impact Factor: 3.352 (2021)).
Die Publikation "Digital Food Twins Combining Data Science and Food Science: System Model, Applications, and Challenges" von Christian Krupitzer (Food Informatics Department & Computational Science Lab, Universität Hohenheim, Stuttgart, Germany) mit den Co-Autoren, Tanja Noack (Food Informatics Department & Computational Science Lab, Universität Hohenheim, Stuttgart, Germany), Christine Borsum (Food Informatics Department & Computational Science Lab, Universität Hohenheim, Stuttgart, Germany) wurde im MDPI processes, Multidisciplinary Digital Publishing Institute (Impact Factor: 3.352 (2021)) veröffentlicht.The production of food is highly complex due to the various chemo-physical and biological processes that must be controlled for transforming ingredients into final products. Further, production processes must be adapted to the variability of the ingredients, e.g., due to seasonal fluctuations of raw material quality. Digital twins are known from Industry 4.0 as a method to model, simulate, and optimize processes. In this vision paper, we describe the concept of a digital food twin. Due to the variability of the raw materials, such a digital twin has to take into account not only the processing steps but also the chemical, physical, or microbiological properties that change the food independently from the processing. We propose a hybrid modeling approach, which integrates the traditional approach of food process modeling and simulation of the bio-chemical and physical properties with a data-driven approach based on the application of machine learning. This work presents a conceptual framework for our digital twin concept based on explainable artificial intelligence and wearable technology. We discuss the potential in four case studies and derive open research challenges.Die Publikation ist in www.mdpi.com/2227-9717/10/9/1781 abrufbar.
