Profiling the flavor and peptide characteristics in fish-derived oligopeptides based on a quantitative peptide profile and bionic sensory technology.

Molecular weight (MW), tripeptide proportion (TP), and amino acid composition are critical parameters that influence the functional properties and flavor of peptides used in collagen beverages. This study evaluates three detection methods for analyzing MW and TP parameters in two oligopeptide products (Mw < 1 kDa): collagen peptides (CP) and collagen tripeptides (CTP). Additionally, the stability of a chromatographic protocol was validated. For CTP characterization, we innovatively constructed multi-index quantitative models of hydroxyproline (Hyp), Gly-Pro-Hyp (GPH), and TP, and proposed a standardized improvement scheme for TP calculated with Mp < 500 Da (Mp, peak molecular weight). Peptide profiles were identified by UHPLC-Q-Orbitrap-MS2, and the amino acid distribution was visually depicted by Seqlogo. The frequency statistics of amino acids in N- and C-terminal, combined with free amino acids and flavor profiles, were used for multimodal correlation analysis. The results indicate that compared with CP, CTP with lower MW and higher GPH exhibited stronger odors of sulfides, aldehydes, and ketones, and enhanced umami and saltiness, despite having similar peptide distribution and high-frequency hydrophobic amino acids at both terminals (Pro, Gly, Leu, Val, Ser, and Phe). These advances in methods not only provide technical standards for industrial production but also provide a theoretical framework for quality optimization and flavor of peptide-based foods.