On the Entropic Characterization of Mayonnaise Processing.

Mayonnaise is a high-viscosity food emulsion whose consistency evolves during shearing due to structural rearrangement and possible emulsion destabilization. This study presents a laboratory-scale proof-of-concept for adapting an established motor current-derived accumulated entropy generation (AEG) framework as a thermodynamic descriptor for monitoring mayonnaise structure changes. First, eight reference fluids were tested using a rotating-bob viscometer at shear rates of 600, 800, and 1000 s-1 to establish the relationship between viscosity and motor current. The corrected current response showed a strong linear correlation with viscosity. The approach was then extended to commercially available mayonnaise samples. Due to the higher viscosity and structured nature of mayonnaise, testing was performed at 1000 s-1, where stable shearing could be achieved. A modified impeller-based viscometer setup was used to continuously shear the mayonnaise and monitor the motor current in situ, while rheometer measurements were performed independently to validate the corresponding viscosity changes during shearing. The motor current decreased with shearing time, consistent with the reduction in measured viscosity. The calculated AEG increased continuously and distinguished the shear stability of different mayonnaise formulations. The viscosity degradation rates of two different mayonnaises are characterized using the degradation coefficient B introduced in the degradation-entropy generation (DEG) theorem. A higher B value indicates greater structural breakdown. These results suggest that current-derived entropic parameters (B coefficient and AEG) may serve as practical, sensor-accessible descriptors for monitoring mayonnaise consistency evolution when direct torque measurement or in-line rheology is unavailable.