Abstract:

This study aims to establish characteristic fingerprints of Polygonati Rhizoma and develop a method for quantifying fructose and sucrose, combined with multivariate dynamic analysis to investigate the chemical component variations and explore their dynamic patterns during different wine-processing durations, thereby providing a scientific basis for quality control and processing mechanism elucidation. Comprehensive evaluation indicators, such as morphological characteristics, alcohol-soluble extractives,the content of polysaccharides, fructose, and sucrose, characteristic peak numbers, and peak areas, were applied to optimize wine-processing duration and establish a characteristic fingerprint for wine-processed Polygonati Rhizoma. Results revealed that raw and wine-processed Polygonati Rhizoma exhibited respectively ten and nine characteristic peaks in HPLC chromatograms, respectively. Six peaks were retained during processing, three new peaks emerged and four peaks disappeared. Key components were identified as uridine (peak 1), adenine (peak 4), 5-hydroxymethylfurfural (5-HMF, peak 5), guanosine (peak 6), thymidine (peak 7), tryptophan (peak 8), adenosine (peak 9), and polygonatine A (peak 10). Notably, the peak area of 5-HMF (peak 5) significantly increased post-processing, and a newly formed peak 7 was identified as 5-(hydroxymethyl)-1H-pyrrole-2-carbaldehyde. Alcohol-soluble extractives and fructose content showed an upward trend, sucrose content peaked at 8 h before declining, and polysaccharides gradually decreased. In conclusion, the characteristic fingerprint combined with multi-component quantitative analysis establishes a systematic revelation of dynamic transformation patterns of chemical constituents Polygonati Rhizoma during wine processing. This approach provides data-driven insights for optimizing wine-processing parameters and proposes a novel quality assessment strategy applicable to both raw and processed Polygonati Rhizoma.

Key words: Polygonati Rhizoma, processing time, characteristic fingerprint, multi-component, content determination