ENHANCING FUNCTIONALITY OF PLANT PROTEINS: ENGINEERING NOVEL STRUCTURES AND DEVELOPING A PREDICTIVE FRAMEWORK FOR FOOD PRODUCT DEVELOPMENT

The proposed research brings together an interdisciplinary and comprehensive approach that addresses the broader goals of: (a) extracting, fractionating, and characterizing protein fractions from diverse plant sources (pea, almond, oat, and algae); (b) formulation engineering of sub-micron protein structures (e.g., microgels and nanoparticles) to improve the functionality of the protein fractions, such as dispersibility and stability with thermal processing; (c) translation of these protein fractions to develop model liquid beverages and semi-solid foods and characterization of their stability, texture, and digestibility; and (d) development of a machine learning predictive framework to reduce empirical testing for future food product development using plant-based proteins.Ultimately,the overall goal of this project is to provide this information to the US food manufacturing industry to streamline development of novel foods using plant proteins that will have improved quality. This overall goal will be accomplished through the followingspecific objectives of the research plan: 1. Evaluate the role of physico-chemical properties of plant protein fractions (concentrates, isolates, soluble proteins) in their stability in aqueous solutions and as ingredients to develop sub-micron scale assemblies based on physical structuring mechanisms to enhance stability in aqueous solutions.2. Characterize the functionality (stability, texture, and digestibility) of protein fractions and novel protein structures in liquid and semi-solid model food systems.3. Develop a machine learning predictive framework to aid in the development and manufacturing of novel plant-based foods with optimal functionality.