DESIGN OF NOVEL FOODS WITH HEALTHY BENEFITS: ADVANCING AN EVIDENCE-BASED FRAMEWORK

The overall goal of this project is to advance a mechanism-based classification framework to identify variations in food breakdown during digestion that can be utilized in processing and design of novel foods with healthy benefits. This objective will be accomplished through the following specific objectives:1. Identify the relationship between initial food properties to the changes that occur when novel foods processed with ultrasound are subjected to the chemical environment of gastric digestion within the Food Breakdown Classification System (FBCS) framework.2. Identify breakdown mechanisms of novel foods processed with ultrasound when exposed to the simulated gastric environment for each of the FBCS classes.3. Develop deep learning model to predict FBCS class of novel foods processed with ultrasound using initial composition and structure.The results from the proposed work will inform the expansion of a framework that can be utilized to advance design of novel food products with healthy benefits to promote the US food manufacturing industry. This framework will focus on identifying breakdown mechanisms during digestion of foods processed with ultrasound and developing an initial deep learning model to connect food properties to FBCS class. As such, it will be applicable to many processed foods, providing a powerful tool for the US food manufacturing industry.