Issue 48, 2023

Rheology and dispensing of real and vegan mayo: the chickpea or egg problem

Abstract

The rheology, stability, texture, and taste of mayonnaise, a dense oil-in-water (O/W) emulsion, are determined by interfacially active egg lipids and proteins. Often mayonnaise is presented as a challenging example of an egg-based food material that is hard to emulate using plant-based or vegan ingredients. In this contribution, we characterize the flow behavior of animal-based and plant-based mayo emulsions, seeking to decipher the signatures that make the real mayonnaise into such an appetizing complex fluid. We find that commercially available vegan mayos can emulate the apparent yield stress and shear thinning of yolk-based mayonnaise by the combined influence of plant-based proteins (like those extracted from chickpeas) and polysaccharide thickeners. However, we show that the dispensing and dipping behavior of egg-based and vegan mayos display striking differences in neck shape, sharpness, and length. The ratio of apparent extensional to shear yield stress value is found to be larger than the theoretically predicted square root of three for all mayo emulsions. The analysis of neck radius evolution of these extension thinning yield stress fluids reveals that even when the power law exponent governing the intermediate pinching dynamics is similar to the exponent obtained from the shear flow curve, the terminal pinching dynamics show strong local effects, possibly influenced by interstitial fluid properties, finite drop size and deformations, and capillarity.

Graphical abstract: Rheology and dispensing of real and vegan mayo: the chickpea or egg problem

Supplementary files

Article information

Article type
Paper
Submitted
01 محرم 1445
Accepted
22 ربيع الثاني 1445
First published
22 ربيع الثاني 1445

Soft Matter, 2023,19, 9413-9427

Rheology and dispensing of real and vegan mayo: the chickpea or egg problem

N. N. Nikolova, C. D. V. Martínez Narváez, L. Hassan, R. A. Nicholson, M. W. Boehm, S. K. Baier and V. Sharma, Soft Matter, 2023, 19, 9413 DOI: 10.1039/D3SM00946G

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