Prediction of recombined dairy emulsion properties through formulation and process: An integrated approach

Abstract

High-Pressure Homogenization (HPH) was applied to dairy emulsions reconstituted from micellar caseins, whey proteins, and anhydrous milk fat. A three-factor optimal experimental design was implemented, varying protein ratio (from 80:20 to 20:80), total protein content (0.5–3.5 %), and pressure (10–90 MPa) to investigate interaction effects. Multiple regression models were used to assess the influence of formulation and process variables, and ANOVA tests were conducted to evaluate model significance. Response profiling indicated that interactions between micellar caseins and whey proteins affected emulsion properties, particularly particle size (D[3,2] ranging from 0.5 to 2.2 μm) and rheology. Micellar caseins contributed to viscosity (3–359 mPa·s at 50 s⁻¹) through interfacial interactions and viscoelastic networks at high concentration. Homogenization pressure played a key role in droplet size distribution (D[3,2] and Span) and interfacial protein composition. Ternary plots revealed nonlinear effects in viscosity and droplet size, highlighting the complexity of multi-component interactions. Homogenization pressure, in combination with formulation parameters modulated the interfacial area, and protein coverage (varying from 0.6 to 15 mg.m⁻²) and influence the resulting whey protein-to-casein ratio at the fat globule interface. These findings underscore the necessity of multi-factorial optimization in dairy emulsion design. Predictive modelling now enables a reverse-engineering approach, allowing precise adjustment of formulation and process conditions to achieve targeted emulsion properties, such as droplet size, viscosity, and physical stability. This study uniquely combines a mixture–process design with a mechanistic view of protein functionality at the oil–water interface, providing predictive insights beyond single-factor approaches.