Multiple dimensional rheology approach for oral texture prediction of yogurts

Abstract

Rheological approach has been widely applied to investigate the flow behavior of fluid food for the understanding as well as prediction of oral textural sensation of such products. However, since oral texture sensation is highly dynamic and influenced by multiple contributing factors (i.e. oral temperature, oral processing time, saliva mixing, and varied shear rate), conventional rheological measurements can hardly be precise in predicting oral textural sensation and mouthfeel. Here, we propose a very different rheology approach, which synchronizes four major dimensions/variables in one set of rheological measurements: the oral residence time, the bolus temperature, the saliva ratio, and the oral shear rate. Results indicated that the multiple dimensional rheology approach improved the predictive accuracy of the in-mouth thickness of low-temperature yogurt and provided a new measure for quantifying the mouth-melting of yogurt. It appeared that apparent viscosity at a temperature of 13 °C, a saliva ratio of 20 %, and a shear rate of 1 s-1 gave the most reliable prediction of the in-mouth thickness of yogurt. This novel approach provides a much-improved accuracy of texture prediction which requires a minimal number of rheology tests. We believe that, even though this experimental approach was initially designed for low-temperature yogurt drinks, it is also applicable to the texture and mouthfeel prediction of many other food products.