Viscometry-based prediction of structural properties of high-moisture meat analogues using gelation properties of soy and pea isolate protein blends

Abstract

In this study, utilizing the gelation properties of a blend containing soy protein isolate (SPI), pea protein isolate (PPI), and corn starch (CS), we introduced a novel approach to predict the structural attributes of high-moisture meat analogues (HMMA). By leveraging the “Rapid Visco Analyzer 4800″ viscometer, we measured the gelation behavior of SPI and PPI based on temperature profiles, underscoring a method to efficiently forecast fibrous structures and reduce trial errors in complex extrusion processes. As the PPI content increased, we observed a decline in the overall viscosity of the protein mixture, paralleled by a rise in color lightness. Contrary to the sturdy gel network formed by SPI, PPI showcased weaker particle bonds, indicating a structural vulnerability. In line with this, the texture of HMMA diminished as PPI content escalated. The secondary protein structure in both protein gels and HMMA revealed that as PPI content grew, there was a reduction in α-helix and β-sheet structures while random coil structures increased. The molecular strength of the protein gel waned with higher PPI content. Similarly, in HMMA, elevated PPI levels corresponded to fewer protein interactions. The study demonstrates that HMMA's textural properties can be effectively predicted by understanding the gelation characteristics of the SPI-PPI blend, highlighting the need for further research to refine prediction models that incorporate the complexities of molecular interactions in varying processing conditions.