目的 构建白马骨Serissa serissoides多指标定量测定方法，结合化学计量学与加权逼近理想解排序（TOPSIS）模型，对不同产地白马骨药材质量进行综合评价。方法 采用高效液相色谱法（HPLC），建立白马骨中车叶草苷酸、去乙酰车叶草酸、鸡屎藤苷酸、牡荆素、松脂素、丁香树脂酚、豆甾醇、β-谷甾醇、齐墩果酸、熊果酸10种成分的含量测定方法；色谱条件设定为乙腈-0.2%磷酸（含0.03%三乙胺）流动相，检测波长238、270、210 nm，进样量10 μL，柱温30℃，体积流量1.0 mL·min^-1。参照《中国药典》2025年版通则要求，测定样品醇溶性浸出物、总灰分及酸不溶性灰分。运用SPSS 26.0、SIMCA 14.1软件，对20批白马骨药材开展层次聚类分析（HCA）、主成分分析（PCA）、偏最小二乘法-判别分析（PLS-DA），以变量投影重要性（VIP）值＞0.9为阈值，筛选药材质量差异标志物；同时采用TOPSIS模型对20批样品进行质量综合评分与优劣排序。结果 所建立的10种成分在各自质量浓度范围内线性关系良好；各成分质量分数分别为3.327～5.625、0.755～1.296、1.853～3.172、0.187～0.456、0.069～0.151、0.066～0.130、0.335～0.898、0.568～1.661、0.293～0.611、0.893～1.731 mg·g^-1；醇溶性浸出物、总灰分、酸不溶性灰分含量依次为16.0%～32.4%、1.9%～7.2%、0.5%～1.7%。化学计量学分析可将20批白马骨药材分为3大类，PCA共提取2个主成分，累积方差贡献率达91.968%；基于VIP值筛选出车叶草苷酸、齐墩果酸、牡荆素、鸡屎藤苷酸、熊果酸、β-谷甾醇共6种质量差异标志性成分，可用于不同批次白马骨药材的质量评价。TOPSIS分析表明，各产地样品欧氏贴近度（Ci）为0.267 0～0.702 6，其中S9（广东乳源县）、S11（广西隆安县）、S15（贵州绥阳县）、S12（广西上林县）、S8（广东平远县）批次药材综合质量更优。结论 建立的多指标定量检测方法精准、稳定、可靠，可为白马骨药材质量控制及质量标准制订提供实验依据；联合化学计量学与TOPSIS模型的评价体系科学直观，适用于不同产地白马骨药材整体质量的综合评价。

Objective To establish a multi-index quantitative determination system for Serissa serissoides and conduct a comprehensive quality evaluation of different origin samples of this herb by combining chemometrics and the technique for order preference by similarity to ideal solution (TOPSIS) model. Methods A high-performance liquid chromatography (HPLC) method was developed for the determination of 10 active components, including asperulosidic acid, deacetylaspelurosidic acid, paederosidic acid, vitexin, pinoresinol, syringaresinol, stigmasterol, β-sitosterol, oleanolic acid, and ursolic acid in S. serissoides. The chromatographic conditions were set as follows: Mobile phase of acetonitrile-0.2% phosphoric acid (containing 0.03% triethylamine), detection wavelengths of 238 nm, 270 nm, and 210 nm, injection volume of 10 μL, column temperature of 30 ℃ , and flow rate of 1.0 mL·min^-1. The alcohol-soluble extractives, total ash, and acid-insoluble ash of the samples were determined in accordance with the requirements of the 2025 edition of the Chinese Pharmacopoeia. Hierarchical cluster analysis (HCA), principal component analysis (PCA), and partial least squares-discriminant analysis (PLS-DA) were performed using SPSS 26.0 and SIMCA 14.1 software. The variable importance in the projection (VIP) value>0.9 was set as the screening threshold to identify the quality difference markers of the samples. Meanwhile, the TOPSIS model was used to conduct a comprehensive quality score and ranking of the 20 batches of samples. Results The established method showed good linearity for the 10 components within their respective concentration ranges. The mass fractions of the components were 3.327—5.625, 0.755—1.296, 1.853—3.172, 0.187—0.456, 0.069— 0.151, 0.066—0.130, 0.335—0.898, 0.568—1.661, 0.293—0.611, and 0.893—1.731 mg·g^-1, respectively. The contents of alcoholsoluble extractives, total ash, and acid-insoluble ash were 16.0%—32.4%, 1.9%—7.2%, and 0.5%—1.7%, respectively. Chemometrics analysis could classify the 20 batches of S. serissoides into three major categories. PCA extracted two principal components, with a cumulative variance contribution rate of 91.968%. Based on the VIP value, six quality difference marker components, including serissoside acid, oleanolic acid, vitexin, paederosidic acid, ursolic acid, and β-sitosterol, were screened out, which could be used to distinguish the quality of different batches of S. serissoides. TOPSIS analysis indicated that the Euclidean closeness (Ci) of the samples from different origins ranged from 0.267 0 to 0.702 6, with batches S9 (Ruyuan County, Guangdong), S11 (Long’an County, Guangxi), S15 (Suiyang County, Guizhou), S12 (Shanglin County, Guangxi), and S8 (Pingyuan County, Guangdong) having better overall quality. Conclusion The established multi-index quantitative detection method is accurate, stable, and reliable, providing experimental evidence for the quality control and standardization of S. serissoides. The evaluation system combining chemometrics and the TOPSIS model is scientific and intuitive, suitable for the comprehensive quality evaluation of S. serissoides from different origins.

R286.2

安徽省中医药传承创新科研项目（2024CCCX078）