An updated review of functional properties, debittering methods, and applications of soybean functional peptides

Abstract

Soybean functional peptides (SFPs) are obtained via the hydrolysis of soybean protein into polypeptides, oligopeptides, and a small amount of amino acids. They have nutritional value and a variety of functional properties, including regulating blood lipids, lowering blood pressure, anti-diabetes, anti-oxidant, preventing COVID-19, etc. SFPs have potential application prospects in food processing, functional food development, clinical medicine, infant milk powder, special medical formulations, among others. However, bitter peptides containing relatively more hydrophobic amino acids can be formed during the production of SFPs, seriously restricting the application of SFPs. High-quality confirmatory human trials are needed to determine effective doses, potential risks, and mechanisms of action, especially as dietary supplements and special medical formulations. Therefore, the physiological activities and potential risks of soybean polypeptides are summarized, and the existing debitterness technologies and their applicability are reviewed. The technical challenges and research areas to be addressed in optimizing debittering process parameters and improving the applicability of SFPs are discussed, including integrating various technologies to obtain higher quality functional peptides, which will facilitate further exploration of physiological mechanism, metabolic pathway, tolerance, bioavailability, and potential hazards of SFPs. This review can help promote the value of SFPs and the development of the soybean industry.

Keywords:

• Soybean functional peptides
• functional properties
• debitterness technologies
• bioavailability
• applications

Disclosure statement

No potential conflict of interest was reported by the authors.

Additional information

Funding

This work was financially supported by the National Natural Science Foundation of China (Grant No: 32101981), Sichuan Science and Technology Program (2019YFN0174, 2020YFN0149, 2020JDRC0111, and 2021JDRC0030).