Spectral and chromatographic fingerprint −based qualitative and quantitative evaluation strategy combined with chemometrics for quality control of functional red yeast

Abstract

The red yeast has significant potential for application in the food industry and in the improvement of cardiovascular diseases. The objective of this study is to develop a rapid, accurate, and comprehensive quality control strategy. Functional and common red yeast were identified through Fourier Transform Infrared (FTIR) spectral fingerprinting combined with Orthogonal Partial Least Squares Discriminant Analysis (OPLS-DA). A quantitative prediction model for the indicator component, lovastatin, was constructed by integrating Ultraviolet (UV) spectral fingerprinting with Partial Least Squares (PLS) model. The FTIR and UV spectral quantized fingerprints (QFPs) of functional red yeast were obtained, thereby rendering the spectral information concise. The spectral QFPs were evaluated for qualitative and quantitative similarity by combining them with Systematically Quantified Fingerprint Method (SQFM), and the integration of evaluation results were obtained using the coefficient of variation weighted mean. The combination of High Performance Liquid Chromatography (HPLC) fingerprints and SQFM demonstrated the process stability of the production of functional red yeast into Xuezhikang capsules. This strategy innovatively integrates chemometrics, fingerprinting techniques, and similarity evaluation methods, offering a more efficient and comprehensive approach than traditional identification and quality control methods. It represents a novel paradigm for source-level quality control of functional red yeast.