Study on the Residence Time and Texture Prediction of Pea Protein Extrusion Based on Image Analysis.

ABSTRACT: This paper initially involves three main processing parameters: screw speed, feeding speed, and initial material moisture content, exploring the RTD of materials inside the extruder barrel under varying parameters and clarifying the impact of parameter variations on RTD. Finally, machine vision technology was utilized to link extruded product images to texture features, and a texture prediction model based on image features was established using a Back Propagation (BP) neural network. Particle Swarm Optimization (PSO) and Genetic Algorithm (GA) were applied to optimize the BP neural network. The results indicate that the feeding speed has a stronger impact than the screw speed on the extrusion process, and an increase in the initial material moisture content tends to shorten the RTD. Speci

SUBMITTER: Wu Q 

PROVIDER: S-EPMC10742850 | biostudies-literature | 2023 Dec

REPOSITORIES: biostudies-literature