The goal of this project is to develop AI predictive models for starch digestibility from common starchy foods (potatoes and rice) and to assess the effect of clean label processing techniques on this digestibility. Based on this overarching goal, the specific objectives are to develop: (a) AI-based predictive models using imaging and DSC (Differential Scanning Calorimetry) of the digestibility of individual foods subjected to various clean-label processing techniques (b) AI-based predictive models for starch digestibility in binary systems of starchy foods and lipids (c) AI-based predictive models of starch digestibility integrating processing and product data.