目的 筛选夏枯草的质量标志物，并建立其含量测定的方法。方法 利用 UPLC Q Exactive Plus Orbitrap 高分辨液质联用仪进行全成分分析，采用高效液相色谱（HPLC）法建立夏枯草的指纹图谱，对 20 批次夏枯草药材进行化学计量学分析，筛选夏枯草的质量标志物并测定含量。综合分析相关的文献数据，研究不同产地夏枯草的迷迭香酸含量变化，进而评价药材质量。结果 从夏枯草中共鉴定出 72 个化合物，其中有机酸类化合物 36 个，占总数的 50%；20 批次夏枯草的指纹图谱中共标记了 8 个共有峰，指认出咖啡酸、芦丁、金丝桃苷和迷迭香酸 4 个成分，各批次之间的相似度大于 0.900。化学计量学分析结果表明，迷迭香酸可能是夏枯草的潜在质量标志物。测定 20 批次夏枯草中迷迭香酸含量，发现有 5 个批次不合格。综合文献分析了158 批次夏枯草，发现迷迭香酸含量的整体合格率为 59.77%。结论 迷迭香酸是夏枯草的潜在质量标志物，其含量能有效地评价不同产地夏枯草药材的质量。

Objective To screen quality markers of Prunellae Spica and develop a method for determining their content. Methods The total component analysis were conducted by using a UPLC Q Exactive Plus Orbitrap high resolution liquid mass spectrometer. The fingerprints of Prunellae Spica were produced using HPLC. Twenty batches of Prunellae Spica were subjected to chemometric analysis to determine their contents and screen quality marker. In addition，a thorough examination of data from the literature was done to study the content changes in rosmarinic acid of Prunellae Spica from various origins and to evaluate the quality of Prunellae Spica. Results A total of 72 compounds from Prunellae Spica were found，36 of them were organic acids，accounting for 50% of the total compounds. Eight common peaks were observed by fingerprint analysis of 20 batches of Prunellae Spica. Four key constituents including caffeic acid，rutin，hyperoside，and rosmarinic acid were identified. The similarity between the batches was higher than 0.900. The results of chemometric analysis indicated that rosmarinic acid may be a potential quality marker of Prunellae Spica. Rosmarinic acid content in twenty batches of Prunellae Spica showed that five batches were unqualified. After comprehensive literature analysis on 158 batches of Prunellae Spica was conducted，it was found that the overall qualification rate of rosmarinic acid content was 59.77%. Conclusion Rosmarinic acid is identified as a potential quality marker for Prunellae Spica，and its content can be used to assess the quality of Prunellae Spica from various origins.

R284.1

广东省重点领域研发计划项目 （2020B1111110007）；广州市校 （院） 联合资助项目基础与应用基础研究项目 （2023A03J0756）；广东省基础与应用基础研究企业联合基金资助项目 （2023A1515220218）；广州市科技局基础与应用基础研究项目 （2023A04J0479）