Rheology and Tribology for Predicting Food Perception

December 11, 2017


Food scientists deliberately formulate foods and ingredients to be appealing to consumer tastes. Delectability can be analyzed through categorizing specific qualities of a food product tested by sensory panels that rate the item by various aspects, including crunchiness, smoothness, stickiness, and many other characteristics. With quantification of these rather qualitative food attributes, researchers have applied rheology and its sister-science, tribology, to correlate the sensory data to the physical properties of food samples. This process involves examining the samples by both human perception and characterization equipment to see if in the future the instruments can be used to predict basic food qualities with less involvement from sensory panels.


Rheology and Sensory Correlations


Rheology measures the bulk physical properties of a soft material in response to shear forces, which has been applied for many aspects of food formulation and processing. Just like any other fluid or soft material, food structure influences the flow properties and storage, but also comes into play for nutritional value. (1) Although there remains much more investigation to be done before exact correlations can be deduced for general types of food, various researchers have pinpointed shear rates that represent specific qualities for a particular food. Texture and mouthfeel have been characteristics sought after by rheology studies, with some results correlating fluid thickness to 50 1/s on a flow curve. (1, Figure 1) The initial bite into a solid food item has been correlated to rheology studies through yield stress and storage modulus (G’) as a measure of firmness, (1) but thereafter the influence of chewing and saliva take over. Furthermore, shear thinning materials may display similar rheology data but yet have drastically different sensory attributes, especially emulsions. (2)


Oscillatory tests also have their use, as amplitude sweeps measure the low-strain elastic modulus (G’) as a measure of gel-like qualities (Figure 2). Mayonnaise was shown to lack sensory correlations with flow curve data, but linked well with elastic modulus for perceived hardness and perceived adhesion. (3) Particle size in mashed potatoes was shown to alter perceived smoothness and after-feel, which also lowered the storage modulus with increased particle sizes due to increases in interfacial adhesion. (4) 


Tribology and Sensory Correlations


Tribology data provides further information on perceived mouth-feel by measuring the friction between the sample and its corresponding environment, which is typically the tongue and palate in the mouth.  To emulate the tongue and palate, a glass rotating surface with a PDMS stationary lower surface has been found useful. (1) Studies have also used stainless steel on PDMS, (2) neoprene and Teflon. (5)


Stribeck curves display the friction response at increasing sliding speed of the upper surface. Three basic friction regimes elucidate the response of the sample and the two surfaces with the increased speed such that the first response of the friction is a reflection of asperity contact between the surfaces (boundary friction) followed by the friction being influenced by the sample becoming wedged between the surfaces (mixed friction). The highest rotation speeds display the impact of the sample completely separating the two surfaces, referred to as the hydrodynamic friction.


Different regions of the Stribeck curve may correspond to various motions undergone during eating. Some foods experience behaviors similar to all three regions of the curve, while beverages are believed to be sipped and swallowed with close simulation to the boundary friction and mixed friction (medium speeds) of the Stribeck curve. (6) The behavior of thick fluids and pastes in the mouth is likely represented by the hydrodynamic friction due to their higher viscosities. (6)


The appropriate testing speed for a specific sensory quality can be established through statistical analyses of the tribology data and the sensory panel results. In the study of mashed potatoes, speeds of 50 and 100 mm/s were closely correlated to the quality of “smoothness” (4) - other food materials were shown to have smoothness correlate to high speeds of the hydrodynamic friction regime as well. (6) However, other authors caution against correlating smoothness solely to tribology data, as perception of smoothness is believed to also include taste. (1)


Sensory studies with rheometers and tribometers are becoming more common due to ever-changing ingredients and shifting consumer demands for both healthy and dietary-specific requirements. The emerging correlations likely have played a role in making your favorite snack delicious and will contribute to the healthy and convenient foods of the future.  


To download a free copy of our Rheo-Tribology report, click here


To learn more about getting started with rheology and tribology testing for sensory applications, contact us for a free initial consultation. 



  1. Stokes, J., Boehm, M., and Baier, S., “Oral processing, texture and mouthfeel: from rheology to tribology and beyond”, Current Opinion on Colloidal and Interface Science, 2013, 18, 349.

  2. Douaire, M., Stephenson, T., and Norton, I., “Soft tribology of oil-continuous emulsions”, Journal of Food Engineering, 2014, 139, 24.

  3. Maruyama, K., et al., “Relationship between Rheology, Particle Size and Texture of Mayonnaise”, Food Science Technology Resources, 2007, 13, 1, 1.

  4. Park, H. W., and Yoon, W. B., “Effect of drying and grinding characteristics of colored potato (Solanum tuberosum L.) on tribology of mashed colored potato paste”, CyTA – Journal of Food, 2018, 16, 1, 135.  

  5. Chojnicka-Paszun, A., de Jongh, H., and de Kruif, C., “Sensory perception and lubrication properties of milk: Influence of fat content”, International Dairy Journal, 2012, 26, 15.

  6. Chen, J., and Stokes, J., “Rheology and tribology: Two distinctive regimes of food texture sensation”, Trends in Food Science and Technology, 2012, 25, 4.


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