DigiFoods - Digital Food Quality

DigiFoods is developing smart sensors for measuring and digitizing food quality directly in the production line. This information can be used to optimize processes and value chains for increased profitability and reduced food waste. The quality of raw materials in the food industry varies significantly. Measuring this quality in the process is challenging due to the biological variation. Our solutions are based on a fundamental understanding of food quality, processing, and modern optical instrumentation, enabling real-time measurement of raw material variations. We also introduce robotics for automated measurements in challenging processes and field applications. We are studying and developing concepts for using large-scale measurements to improve primary production and differentiate products of varying quality for different consumer segments, reducing waste in the consumer phase. DigiFoods, with its 23 partners, serves as an innovation hub for the food industry, technology providers, and scientific communities. Fourier-transform Infrared Spectroscopy (FTIR) shows promise for measuring protein composition, and there is currently no industrial solution for such measurements. We have demonstrated that FTIR can measure relevant variations in peptide sizes in industrial peptide blends from enzymatic hydrolysis, a crucial quality indicator. A portable FTIR instrument has been built and tested with excellent results, enabling industry measurements, improving the understanding and control of these bioprocesses. Other types of IR technology can be miniaturized, based on new types of LEDs (light-emitting diodes) that produce radiation in the mid-IR region. This allows for small handheld sensor systems for measuring chemical properties in food throughout the value chain. Semiconductor lasers (QCL, quantum cascade lasers) also generate light in the IR range and are suitable for low-cost measurement systems. A prototype system has been developed based on each of these two technologies and are being tested for various food applications. Raman spectroscopy can measure various food quality attributes during processing. We have determined that the method can be used to measure the shares of bone fragments, fat, protein, and collagen in ground poultry by-products directly in an industrial process. Raman is also suitable for measuring EPA and DHA in whole salmon fillets on a conveyor belt, which is of interest to the aquaculture industry. In-line measurement of salmon fillets with Raman may require robotic control that includes machine vision and algorithms to handle the measurement probe optimally. A preliminary demonstrator of such a system has been developed and tested at the center. An important activity in the center is to conduct in-line measurements in industrial processes, and we have worked on the following cases: dry matter in potatoes, dry matter in cheese, core temperature in fish cakes after heat treatment, fat content in sausages, and fat and protein in poultry and salmon by-products, as well as quality attributes in salmon fillets. All these methods are novel and can significantly contribute to process improvement. Companies learn about the process variations, leading to improvements in some processes, with the goal of reducing waste and achieving consistent final quality. In the field of data analysis, we are developing solutions that use food quality measurements to reduce waste and increase profitability in food production. We are working on three strategies to handle variation in food quality: the first involves collecting large datasets that combine food quality with other available farm or production data to identify risk factors and understand underlying causes of variation. The second strategy involves using in-line measurements of food quality to monitor and adjust processes in real-time to ensure quality remains consistent. The third strategy involves product differentiation, developing and marketing products with different qualities for different consumer groups. Some highlights in 2023: - We have developed a new NIR sensor for fast and non-destructive measurement of sugar in strawberries and tomatoes. This was tested on an autonomous robot and the concept will be developed further. The NIR sensor also has great potential in the seafood and meat industry, and a commercialization project has been started. - Within cheese production, we have linked in-line measurements of dry matter in cheese with other process parameters. This has given an increased understanding of the process which has produced lasting innovations that contribute to increased profitability and better utilization of incoming milk. - Hyperspectral camera technology has been developed for industrial measurement of fat, pigment, blood and melanin spots in salmon fillets and the technology will be put into commercial use in 2024. The technology is interesting for several different quality measurements on fish and meat.

The goal of SFI Digital Food Quality (DigiFoods) is to develop inline smart, sensor-driven solutions that deliver the essential food quality information required for successful process optimisation and digitalization of the food industry. Food processes are extremely complex and challenging to measure due to the inherent high level of biological variation in raw materials. The development of advanced solutions that are built on a fundamental understanding of food science, will allow the food industry to effectively measure and handle these variations, enabling a ground-breaking digital transformation of the industry. Effective strategies for real-time analysis and utilization of industrial data at a large scale will optimise processes and reduce waste throughout the value chain. New levels of information flow will also significantly increase productivity. DigiFoods will innovatively combine applied and basic research to generate new basic knowledge, evaluate prototype solutions, and create results for innovation in the following core areas 1) novel sensor systems and food application development, 2) robot and sensor integration, 3) integrated inline sensor solutions, and 4) analysis and utilisation of large-scale process and value chain data. A multi-disciplinary team comprising food companies, technology providers and research institutions is highly motivated to collaborate towards this common goal. The industrial partners will participate in all research tasks, committing essential in-kind contributions to the project. A critical element of this centre is that much of the experimental work will be done in the industrial process lines, which the end-users will make available for research. The centre will educate 9 PhD students and 3 post docs. DigiFoods will be governed by a board with an industrial majority, ensuring relevant research that will build the foundation for a future food industry 4.0.