食源性鲜味肽筛选鉴定及生物活性研究进展OA

Umami peptides represent a novel class of umami substances that have been identified in recent years.These peptides not only exhibit favorable flavor characteristics but also demonstrate advantageous processing traits and biological activities,thus emerging as a focal point of research within the food science and food processing industries.Traditional methods for the separation and identification of umami peptides typically involve the extraction and purification of peptide components,which are often characterized by high costs and low efficiency.However,with the rapid advancements in computer technology,machine learning models that possess high predictive capabilities and accuracy have been implemented in the analysis and prediction of umami peptides.This approach effectively addresses the limitations associated with traditional methods used in the screening and preparation of these peptides.In this paper,we review the latest advancements in the preparation technologies,tasting mechanisms,processing characteristics,and biological activities of umami peptides derived from various food sources.Furthermore,we discuss the prospective applications of machine learning and computer simulation technologies in the high-throughput screening of umami peptides,the mechanisms underlying taste formation,and research into functional activities.Our objective is to provide a valuable reference for the development of preparation technologies,the mechanisms taste formation,and the biological activities of umami peptides.