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ARS Home » Southeast Area » New Orleans, Louisiana » Southern Regional Research Center » Food Processing and Sensory Quality Research » Research » Research Project #450123

Research Project: Texturization of Proteins by Extrusion for Enhanced Protein Security

Location: Food Processing and Sensory Quality Research

Project Number: 6054-30600-009-002-S
Project Type: Non-Assistance Cooperative Agreement

Start Date: Sep 1, 2026
End Date: Aug 31, 2030

Objective:
1. Evaluate extrusion texturization under high-moisture conditions by systematically modifying the cooling die zone temperatures. 2. Develop a quantitative correlation between the cooling die temperature profile and the degree of texturization in extruded HMMA.

Approach:
This project will systematically evaluate how hot-melt protein temperature during cooling influences HMMA structure and texture. Using a Brabender TSE 20/40 twin-screw extruder with a three-stage cooling die, we will vary cooling-die temperatures to achieve melt temperatures from 50–90°C. Internal melt temperatures will be monitored at four thermocouple points, with pea protein isolate as the primary system and soy as a secondary system. Each treatment will be analyzed for texture, anisotropy index (AI), macro-fiber structure, moisture/water activity/color, protein secondary structure (FTIR), molecular weight changes (SDS-PAGE), and polymeric protein fractions (SEC). We will then develop an empirical correlation linking melt-temperature profiles to degree of texturization (AI), supported by RSM modeling and validated through confirmation runs. Findings will be interpreted alongside prior SAXS results indicating that fiber formation is optimized within the 50–90°C cooling window.Expected Deliverables Complete dataset for all cooling-temperature treatments across both protein systems. Validated RSM model correlating cooling-die profiles with texturization outcomes. At least one peer-reviewed publication and a national conference presentation. Data shared with ARS collaborators per USDA open-data requirements.