This study focused on predicting high-moisture texturization of plant-based proteins (soy protein concentrate (SPC), soy protein isolate (SPI), pea protein isolate (PPI)) at different water contents (57.5%, 60%, 65%, 70%, and 72.5% (w/w db)) to optimize and guarantee the production of high-moisture meat analogs (HMMA). Therefore, high-moisture extrusion (HME) experiments were performed, and the texture of the obtained high-moisture extruded samples (HMES) was sensory evaluated and categorized into poorly-textured, textured, or well-textured. In parallel, data on heat capacity (cp) and phase transition behavior of the plant-based proteins were determined using differential scanning calorimetry (DSC). Based on the DSC data, a model for predicting cp of hydrated, but not extruded, plant-based proteins was developed. Furthermore, based on the aforementioned model for predicting cp and DSC data on phase transition behavior of the plant-based proteins in combination with conducted HME trials and the mentioned model for predicting cp, a texturization indicator was developed, which could be used to calculate the minimum threshold temperature required to texturize plant-based proteins during HME. The outcome of this study could help to minimize the resources of expensive extrusion trials in the industry to produce HMMA with defined textures.
Keywords: HMMA; high-moisture extrusion; plant-based proteins; texturability; texturization indicator; thermophysical properties.