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Cited by 40

The DOI matches its Crossref record; 193 of the 193 references it cites were found in a registry or an index.

Ultrasound-induced changes in the structure and functionality of starch and protein

Zhu, Minqian, Xiong, Weiyan, Devkota, Lavaraj, Dhital, Sushil·2026·Food Hydrocolloids

Abstract

Ultrasound technology is an emerging sustainable processing method that modifies the composition, structure, and functional properties of starch and protein in plant food through its chemical and thermo-mechanical effects. The cavitation effect generated by ultrasound disrupts starch granules and affects molecular reorganisation, thereby enhancing swelling power, solubility, thermal stability, pasting viscosity, gelation and retrogradation. However, excessive ultrasound treatment can damage granules and degrade crystalline regions, diminishing relative structures and properties. Similarly, ultrasound alters protein structures by breaking molecular interactions, partially unfolding peptide chains and modulating aggregation behaviour. While cavitation improves protein solubility, surface hydrophobicity, emulsification, foaming and gelation properties, excessive ultrasound exposure may induce oxidative modifications that reduce protein functionality. Furthermore, ultrasound affects starch–protein interactions by either enhancing or reducing glycation reactions, and influences solubility, thermal stability, foaming capacity, gel formation, and textural properties. The manuscript provides a critical analysis of the current knowledge on the dual effects of ultrasonication on isolated starch and protein or in-situ in food systems, facilitating the development of improved starch-protein ingredients tailored for food industry applications.

Overview

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Registry

Crossref · 10.1016/j.foodhyd.2025.112111

Cites

193 of 193 references verified0 citation errors · 0 not checkable

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Citations

Cites

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Metadata

Authors
Zhu, M., Xiong, W., Devkota, L., & Dhital, S.
Venue
Food Hydrocolloids
Publisher
Elsevier BV
Published
2026-03
Volume
172
Pages
112111
ISSN
0268-005X
Cited by
40
References
193
Language
en
Licence
Funders
Australian Research Council

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Data sources

Bibliographic data: Semantic Scholar, OpenAlex, Crossref.

Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).

Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.