Potential of Artificial Intelligence and Machine Learning in Determining Vitamin C Stability in Foods during Processing and Storage

Food stability prediction is important to assess the safety and quality of foods. This project will target to develop prediction models to determine the stability of nutrients and bioactive components considering mechanistic approach based on the reaction kinetics, water activity and glass transition concepts based on micro-region state diagram. Vitamin C stability will be considered as a case study. First, an Excel based database will be developed based on the literature review and selected experimental data carried out in the labs. This database will be used to develop the mechanistic models and then Artificial Intelligence (AI) techniques, such as Principal Component Analysis (PCA), Cluster Analysis, Artificial Neural Network (ANN), Decision Tree and datamining techniques will be used to develop knowledge base, generic rules, and classification. Scientific and research base of Oman in the area of material science and Artificial Intelligence (AI) will be enhanced by developing advanced prediction models in the area of food processing and preservation. Emphasis will be given to train the graduate students, technicians, and research assistants. High quality scientific and conference papers will be targeted to disseminate the developed knowledge. An attempt will be taken to develop computer program for the prediction models. In addition, scientific as well as training workshops or conferences will be organized by this research group for the local and international scientific and professional communities. Popular articles will be published to aware the industry and community on the beneficial effects of the developed prediction models.