Embedded Files
Research Focus
Research Focus
The core focus of our research projects centers on advancing sustainability across the entire spectrum, from the production of raw food materials to the consumption of the final food product. We employ two distinctive approaches: AI-Coupled Food Process Design & Modeling and Upcycling of Food Material. Finally, the economic viability is evaluated through conducting TEA (Techno-Economic Analysis)
- AI-Coupled Process Design & Modeling
The design of a unique food manufacturing process offers the opportunity to minimize resources, energy, costs, and waste generation. To facilitate the practical application of the system from bench-scale to pilot/industrial scale, a comprehensive understanding of the proposed system is essential. In this context, mathematical modeling and simulation prove useful, enabling a clear understanding of the newly proposed system. Currently, our research group has incorporated AI and Machine Learning to develop a process and a model to improve the sustainability of food processing
1.1. Real-time processing monitoring system based on ultrasound sensor with machine learning and AI
1.1. Real-time processing monitoring system based on ultrasound sensor with machine learning and AI
Ultrasound (US) technology offers significant potential for monitoring and improving food manufacturing and distribution processes. One notable application is detecting the cleanliness of food-contact surfaces. Cleaning operations, including Clean-in-Place (CIP) systems, are vital in food processing but often result in substantial use of water and cleaning agents due to the absence of a sensitive, real-time monitoring system. To address this, a US-based sensor system is being developed to evaluate the cleaning status of these surfaces effectively.
Looking ahead, this ultrasound technology could be expanded to assess food quality and detect adulteration during various stages such as harvesting, storing, thawing, and freezing. This broader application would ensure better quality control and safety in the food supply chain.
1.2. AI-based predictive system for the key hazard factors
1.2. AI-based predictive system for the key hazard factors
Every year, a substantial amount of food products is imported, necessitating effective evaluation and detection of risks and hazards. Currently, this is achieved through random sampling of the products. Our research group is collaborating with Dr. Joon Goo Lee's lab and the Korea Food Information Institute to develop an AI-based system designed to predict key hazard factors in imported food products in advance. We expect this system to be an efficient tool that will significantly enhance food safety control
1.3. Digital Twin-based Early-Detection model for shelf-life
1.3. Digital Twin-based Early-Detection model for shelf-life
Due to confusion over the current labeling system for shelf-life, a significant amount of food products is being discarded, many of which are still edible. This misunderstanding leads to unnecessary food waste. To address this issue, our research groups are collaborating with research groups at Ewha Womans University to develop an AI-based early detection model. This model, utilizing various Omics data, aims to provide real-time shelf-life indicators. Such a system could significantly reduce food waste by offering more accurate and understandable shelf-life information
2. Upcycling Food Material
2. Upcycling Food Material
2.1. Novel Food Material (e.g. Cultivated Meat)
2.1. Novel Food Material (e.g. Cultivated Meat)
The design of novel food presents an opportunity to establish a new paradigm not previously in existence. This unique approach involves proposing an entirely new type of food, potentially serving as a game-changer in food production. A key project in our lab focuses on developing scaffolds and serum-free media to support the proliferation and differentiation of animal cells.
2.2. Active Coating / Edible Film
2.2. Active Coating / Edible Film
Through the upcycling of by-products from food manufacturing, the environmental impact of food manufacturing can be minimized. Many by-products are characterized by high protein and carbohydrate contents, which can be utilized to develop edible films and antimicrobial coatings.
3. Techno-Economic Analysis (TEA)
3. Techno-Economic Analysis (TEA)
To facilitate the practical applications of the process system and novel food materials developed by our lab, economic viability should be assessed. In this context, one of the major research projects involves conducting Techno-Economic Analysis (TEA) for novel food and manufacturing processes.
Page updated
Google Sites
Report abuse