Food hydrogels: Experimental and theoretical aspects relating to their formulation and application

Background

Hydrogels are semi-solid three-dimensional hydrophilic polymer networks that contain relatively large quantities of water. Biopolymer-based hydrogels have diverse potential applications in the food industry for creating plant-based foods, functional food products, and biodegradable packaging materials. However, there is currently a relatively poor understanding of the underlying molecular and physicochemical mechanisms governing their mechanical properties, which means they are typically formulated using empirical (rather than theory-driven) methods.

Approach and scope

This article reviews mathematical models and experimental methods for characterizing the mechanical properties of hydrogels, covering both their linear (low deformation) and non-linear (high deformation) properties. Initially, the most common analytical techniques used to characterize the mechanical and structural properties of hydrogels are reviewed. Then, mathematical theories that can be used for describing the properties of single and composite hydrogels are presented. Finally, approaches for enhancing the toughness of hydrogels are discussed and potential real-world applications of hydrogels are presented.

Key findings and conclusions

Food hydrogels are typically assembled from proteins and/or polysaccharides, which can adopt various structures (e.g., filamentous, particulate, phase separated, interpenetrating, co-gelling) that have different mechanical properties. Theoretical models can be used to identify the major factors impacting hydrogel properties, such as polymer concentration, molecular weight, and interactions, as well as particle size, concentration, and interactions. These models can therefore facilitate the design of plant-based meat, fish, and egg analogs, as well as healthier functional foods and biodegradable packaging materials. Nevertheless, there are still challenges to identifying appropriate mathematical models and measuring the required model parameters for complex food matrices. Even so, theoretical and computational approaches are rapidly advancing, which should aid to improve product design and production.