A multi-dimensional quality evaluation strategy for Siegesbeckia pubescens Makino integrating chromatographic,...

To identify the optimal quality and geographical origin of Siegesbeckia pubescens Makino (SP), a comprehensive quality evaluation strategy was established using 20 batches of SP samples collected from five distinct producing regions. Initially, the purity of each fingerprint peak was assessed using the dual-wavelength ratio purity test method (DRPM). Subsequently, the contents of four major components in SP were accurately determined using the one-linear multi-analyte method (OLMM), which showed excellent agreement with the conventional quantitative analysis of multi-components by a single marker (QAMS) approach. For fingerprint profiling, a 3D full-wavelength fingerprint (3DFFP) was developed by high-performance liquid chromatography (HPLC), which provided more comprehensive information compared to traditional single-wavelength fingerprints. Beyond conventional UV-absorbing components, the electroactive and thermally responsive characteristics of SP were also integrated into the quality evaluation. To this end, electrochemical (EC) and differential scanning calorimetry (DSC) quantitative fingerprints were constructed respectively using the quantitative fingerprint method (QFM). The binary similarity evaluation method (BSM) was applied as a quality evaluation method for the above fingerprints. Twenty batches were classified into distinct quality grades, and origin-based discrimination was achieved via cluster analysis and principal component analysis (PCA). Finally, partial least squares regression (PLS) was further employed to identify chromatographic peaks with major contributions to thermal effects and uncover potential antioxidant peaks. In summary, the proposed strategy enables the simultaneous quality control of UV-absorbing components, electroactive substances, and thermally responsive components of SP, offering a robust evaluation framework for the holistic quality evaluation of herbal medicines.