Predictive Response Surface Model for Heat‐Induced Rheological Changes and Aggregation of Whey Protein Concentrate

Whey proteins are now far more than a by-product of cheese processing. In the last 2 decades, food manufacturers have developed them as ingredients, with the dairy industry remaining as a major user. For many applications, whey proteins are modified (denatured) to alter their structure and functional properties. The objective of this research was to study the influence of 85 to 100 °C, with protein concentration of 8% to 12%, and treatment times of 5 to 30 min, while measuring rheological properties (storage modulus, loss modulus, and complex viscosity) and aggregation (intermolecular beta-sheet formation) in dispersions of whey protein concentrate (WPC). A Box–Behnken Response Surface Methodology modeled the heat denaturation of liquid sweet WPC at 3 variables and 3 levels. The model revealed a very significant fit for viscoelastic properties, and a lesser fit for protein aggregation, at temperatures not previously studied. An exponential increase of rheological parameters was governed by protein concentration and temperature, while a modest linear relationship of aggregation was governed by temperature. Models such as these can serve as valuable guides to the ingredient and dairy industries to develop target products, as whey is a major ingredient in many functional foods. Practical Application Statistical modeling is a well-established discipline that permits the study of complex situations while minimizing the sampling effort, thus saving resources. The models generated can then be used to predict outputs, which in the case of the present article could serve the dairy industry focus their whey protein processing by forecasting desired results.