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ARS Home » Pacific West Area » Albany, California » Western Regional Research Center » Healthy Processed Foods Research » Research » Research Project #446482

Research Project: Process Engineering and Techno-Economic Validation of Commercially Competitive Ingredients from Food Waste and Processing Byproducts

Location: Healthy Processed Foods Research

Project Number: 2030-30600-005-007-S
Project Type: Non-Assistance Cooperative Agreement

Start Date: Apr 15, 2026
End Date: Jul 14, 2028

Objective:
(1) Develop novel processes to convert food processing byproducts and wastes into value-added animal feed and human food ingredients (2) Quantify functional performance of the ingredients in food and feed formulations (3) Conduct integrated techno-economic analysis to assess commercial feasibility

Approach:
Task 1: Development and Optimization of Scalable Upcycling Processes. We will convert diverse agricultural byproducts into high-value food and feed ingredients (e.g., functional proteins, dietary fibers, and bioactive compounds) using adaptable, economically viable technologies like advanced bioprocessing and targeted extraction. Processing parameters will be systematically optimized to maximize yield, ensure safety, and enhance nutritional quality, establishing a flexible framework tailored for commercial scalability. Task 2: Structural, Nutritional, and Functional Characterization of Ingredients. Upcycled ingredients will undergo rigorous evaluation to quantify their proximate composition, in vitro digestibility, and structural properties. Crucially, we will assess their techno-functional performance within model food matrices and feed formulations to establish mechanistic links between processing methods, ingredient structure, and end-use commercial viability. Task 3: Integrated Techno-Economic Analysis (TEA) for Commercial Translation. To ensure commercial feasibility, we will develop comprehensive process models (simulating mass and heat balances) to quantify the material and energy requirements of production at an industrial scale. These metrics will drive robust economic models and sensitivity analyses to determine overall profitability, identify key cost drivers, and directly guide the experimental process optimizations in Task 1.