Predicting thickness perception of liquid food products from their non-Newtonian rheology

Antoine Deblais (), Elyn den Hollander, Claire Boucon, Annelies E. Blok, Bastiaan Veltkamp, Panayiotis Voudouris, Peter Versluis, Hyun-Jung Kim, Michel Mellema, Markus Stieger, Daniel Bonn and Krassimir P. Velikov ()
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Antoine Deblais: Unilever Innovation Centre Wageningen
Elyn den Hollander: Unilever Innovation Centre Wageningen
Claire Boucon: Unilever Innovation Centre Wageningen
Annelies E. Blok: Wageningen University
Bastiaan Veltkamp: University of Amsterdam
Panayiotis Voudouris: Unilever Innovation Centre Wageningen
Peter Versluis: Unilever Innovation Centre Wageningen
Hyun-Jung Kim: Unilever Innovation Centre Wageningen
Michel Mellema: Unilever Innovation Centre Wageningen
Markus Stieger: Wageningen University
Daniel Bonn: University of Amsterdam
Krassimir P. Velikov: Unilever Innovation Centre Wageningen

Nature Communications, 2021, vol. 12, issue 1, 1-7

Abstract: Abstract The “mouthfeel” of food products is a key factor in our perception of food quality and in our appreciation of food products. Extensive research has been performed on what determines mouthfeel, and how it can be linked to laboratory measurements and eventually predicted. This was mainly done on the basis of simple models that do not accurately take the rheology of the food products into account. Here, we show that the subjectively perceived “thickness” of liquid foods, or the force needed to make the sample flow or deform in the mouth, can be directly related to their non-Newtonian rheology. Measuring the shear-thinning rheology and modeling the squeeze flow between the tongue and the palate in the oral cavity allows to predict how a panel perceives soup “thickness”. This is done for various liquid bouillons with viscosities ranging from that of water to low-viscous soups and for high-viscous xanthan gum solutions. Our findings show that our tongues, just like our eyes and ears, are logarithmic measuring instruments in agreement with the Weber-Fechner law that predicts a logarithmic relation between stimulus amplitude and perceived strength. Our results pave the way for more accurate prediction of mouthfeel characteristics of liquid food products.

Date: 2021
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DOI: 10.1038/s41467-021-26687-w

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