不同产地黄芩茎叶UPLC指纹图谱与化学模式识别研究

目的 采用超高效液相色谱法（UPLC）建立不同产地黄芩茎叶指纹图谱，超高效液相色谱串联四极杆飞行时间质谱法（UPLC-QTOF/MS）快速鉴定共有峰，并结合化学模式识别研究，为黄芩地上茎叶资源循环利用与质量控制提供参考。方法 采用UPLC，色谱条件为ACQUITY UPLC BEH C₁₈（100mm×2.1mm，1.7μm）色谱柱，以乙腈-0.1%甲酸水为流动相梯度洗脱，流速0.4mL/min，检测波长254nm，柱温35℃。质谱检测采用负离子模式，电压3.0kV，离子源温度120℃，雾化温度400℃，雾化气800L/h。通过相似度评价结合聚类分析和主成分分析进行分析评价，并通过UPLC-QTOF/MS对黄芩茎叶共有峰进行鉴定。结果 确定了不同产地黄芩茎叶药材的19个共有峰，建立了UPLC指纹图谱。10个产地11批黄芩茎叶样品的指纹图谱相似度均>0.9，各产地黄芩茎叶药材的相似度较高，聚类分析、主成分分析结果与相似度分析结果一致。结论 本方法快速、准确、可靠、重复性好，黄芩茎叶UPLC指纹图谱的构建和化学模式的识别可更好的评价其质量，为黄芩地上部分资源价值的利用与质量的控制提供参考。 

UPLC Fingerprint and Chemical Pattern Recognition Method of Scutellaria Baicalensis Stem-Leaf from Different Regions

OBJECTIVE To study and establish the UPLC fingerprint of Scutellaria baicalensis stem-leaf(SBSL) and rapidly identify the specific peaks by UPLC-QTOF/MS， and combined with the study of chemical pattern recognition to provide scientific basis for resources circulating utilization of the SBSL. METHODS The fingerprint of SBSL was established by UPLC， the samples were conducted by ACQUITY UPLC BEH C₁₈ (100mm×2.1mm， 1.7μm) and eluted with acetonitrile and 0.1% formic acid with the flow rate of 0.4mL/min. The detection wavelength was set at 254nm and column temperature was 35℃. Negative ion mode was chosen for qualitative analysis. The capillary voltage was set at 3.0kV. The nebulization gas was set to 800L/h at 400℃， and the source temperature was 120℃. The similarity evaluation， cluster analysis (CA)， and principal component analysis (PCA) were used to deal with the experimental data， in order to find out the similarities and differences among the 11 batches of SBSL from 10 different regions. RESULTS The specific chromatogram of SBSL was obtained， and 19 common peaks were identified by ESI-QTOF/MS. Similarities of the 11 batches of samples from 10 regions were over 0.9， the results of CA and PCA were consistent with similarity evaluation. CONCLUSION The method established in this paper is rapid， accurate， reliable and reproducible. The establishment of UPLC fingerprint of SBSL and the application of chemical pattern recognition can provide a more comprehensive reference for the quality control of SBSL and the resources circulating utilization value of non-medicinal parts of S. baicalensis.