To investigate the effect of process parameters during high-moisture extrusion on system parameter (specific mechanical energy, SME) and product physical properties, blend of soy protein isolate, wheat gluten, and corn starch (50:40:10 w/w) was extruded using co-rotating twin screw extruder equipped with cooling die at 55 and 65% feed moisture, 150 and 170 °C barrel temperature, 150 and 200 rpm screw speed. The hardness and chewiness of products increased as all the extrusion process parameters became low. Among the tested range of process parameters in this study, a combination of high moisture (65%), high barrel temperature (170 °C), and low screw speed (150 rpm) generated the low SME input (less energy consumption) with high texturization degree of meat analogs. Layer and fibrous structure formation of the samples were influenced by variations in process parameters, primarily feed moisture and barrel temperature.
The aim of this study was to evaluate the optimization extrusion variables on quality of textured vegetable protein by using response surface methodology. In this study, 50% soy protein isolate, 40% wheat gluten, and 10% corn starch were blended and 15% of the mixture was substituted with green tea. The moisture content (45, 50, and 55%), barrel temperature (130, 140, and 150°C), and screw speed (100, 150, and 200 rpm) were varied. A Box-Behnken design was used in this experiment. Second order polynomial regression equations were developed to relate the response to extrusion variables as well as to obtain a response surface plot. The independent variables had significant effects on the quality of the products and moisture content was the most significant. The lower moisture content led to the higher integrity index, lower nitrogen solubility index, lower water absorption capacity, higher texture, and higher cutting strength. The optimum conditions were identified as moisture content 47.78%, barrel temperature 150.00°C, and screw speed 196.05 rpm. Incorporation of green tea into protein materials could effectively improve the nutritional value of the product. Understanding these optimized extrusion variables on the product quality was useful for producing textured vegetable protein in the future.
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.