[關鍵詞]
[摘要]
目的 建立龍生蛭膠囊的HPLC指紋圖譜,結合化學模式識別方法進行質量評價。方法 采用HPLC法建立龍生蛭膠囊的指紋圖譜,進行相似度評價,確定共有峰;對測定結果進行層次聚類分析和主成分分析,并結合正交偏最小二乘–判別分析對樣品進行模式識別,以VIP值大于1為標準篩選影響龍生蛭膠囊質量的差異性成分。結果 19批龍生蛭膠囊樣品的HPLC指紋圖譜共標定了20個共有峰,相似度均大于0.95,指認了9個共有峰,分別為槲皮素、沒食子酸、原兒茶酸、紫丁香苷、綠原酸、芍藥苷、刺五加苷E、異嗪皮啶、毛蕊異黃酮葡萄糖苷。19批樣品可分為2類;前4個主成分的累積方差貢獻率為85.504%;以VIP值大于1為標準,篩選出8個主要峰,13、8、2(沒食子酸)、3(原兒茶酸)、1(槲皮素)、14(芍藥苷)、10、11號峰。結論 建立了龍生蛭膠囊更全面、系統(tǒng)的質量評價和分析方法,為龍生蛭膠囊的質量標準提高提供理論依據。
[Key word]
[Abstract]
Objective To develop an HPLC fingerprint of Longshengzhi Capsules and evaluate its quality consistency by combining with the chemical pattern recognition method for the purpose of its quality control. Methods HPLC fingerprints of Longshengzhi Capsules was establish. The similarity was evaluated to establish the common peaks. The hierarchical clustering analysis (HCA), principal component analysis (PCA), and orthogonal partial least squares-discriminant analysis (OPLS-DA) method were carried out, and the differential components of Longshengzhi Capsules quality were screened by the VIP value greater than 1. Results There were 20 common peaks in HPLC fingerprints of Longshengzhi Capsules and the similarities of 19 batches of Longshengzhi Capsules were above 0.95. Nine common peaks have been identified, namely quercetin, gallic acid, protocatechuic acid, syringin, chlorogenic acid, paeoniflorin, eleutheroside E, isofraxidin, and calycosin-7-O-glucoside. 19 Batches of samples were divided into two categories and the cumulative variance contribution rate of the first four principal components was 85.504%. There were eight common peaks with VIP>1, which were 13, 8, 2(gallic acid), 3(protocatechuic acid), 1(quercetin), 14(paeoniflorin), 10, and 11 peak. Conclusion A more comprehensive and systematic quality evaluation and analysis method for Longshengzhi Capsules has been established to provide theoretical basis for improving the quality standard of Longshengzhi Capsules.
[中圖分類號]
R286.02
[基金項目]
陜西省教育廳重點科研協(xié)同創(chuàng)新中心項目(21JY001);陜西省科技廳一般項目(2023-YBSF-365);陜西省科技廳自然科學研究一般項目(2022JQ-919);咸陽市重大科技專項計劃項目(2018K01-47)