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Integrating SAOS, LAOS, and food tribology: Emerging frameworks for structure-function relationships and sensory prediction in food systems.

Nov 2026 · Food Research International · Vol 243 Pt 1, pp. 120331 · 0 citations · 68 references
Medicine

Abstract

Food structure and its effect on deformation behaviour and sensory perception is still a challenge in food science. Small-Amplitude Oscillatory Shear (SAOS) is a common method for the determination of the linear viscoelastic properties and stability of food materials, but it is not applicable to large deformations, such as those occurring during food processing and consumption. Large-Amplitude Oscillatory Shear (LAOS) extends this limitation by giving insights into the nonlinear phenomena like yielding, strain hardening, strain softening and structural recovery. In addition to these rheological methods, food tribology investigates friction and lubrication mechanisms at the contact surfaces of the mouth, including complementary methods that are related to the sensory attributes of creaminess, smoothness, roughness and astringency. This review suggests a common framework to incorporate the fields of SAOS, LAOS, and food tribology, to understand the relationship between structure-function-sensory in a wide variety of food systems. The latest analytical techniques like Fourier-transform rheology, Chebyshev polynomial analysis, Lissajous-Bowditch plots, biomimetic tribological techniques and machine-learning-based predictive tools are explained in detail. This approach is illustrated with examples of dairy products, plant-based protein foods, dysphagia-friendly formulations, reduced fat foods and 3D-printed foods. The review highlights that the use of nonlinear measurements of the rheological parameters is essential to augment the prediction of sensory properties of these materials in order to overcome limitations of the application of conventional linear rheology. Furthermore, the capabilities of AI and data modelling techniques for texture forecasting and food design are examined. In general, the proposed framework is useful for the predictive food engineering and the development of high quality, sustainable and consumer friendly food products.

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