A comprehensive review of food rheology: analysis of experimental, computational, and machine learning techniques

The main objective of food rheology is to identify food structure and texture by rheological measurements, thereby reducing the requirement for sensory analysis in evaluating food products. However, determining food texture and structure exclusively from rheological measurements can be challenging because of the complicated composition and structure of food, as well as the complexities of factoring in the changes that occur during food mastication. This article provides a comprehensive review of the current experimental, computational and machine learning techniques used in food rheology to probe the structure and texture of food products. The textural attributes and structural information that can be inferred from each measurement technique is discussed and recent studies that carried out the measurements are highlighted. Also presented in this review are the recent progress in the experimental techniques and challenges.

Graphical abstract