摘 要 目的：建立尖尾風(fēng)藥材的高效液相色譜（HPLC）指紋圖譜，并進(jìn)行聚類分析和主成分分析。方法：采用HPLC法。色譜柱為ECOSIL ODS-EXTEND C18，流動(dòng)相為乙腈-0.2%磷酸溶液（梯度洗脫），流速為1.0 mL/min，檢測(cè)波長(zhǎng)為334 nm，柱溫為30 ℃，進(jìn)樣量為20 μL。以毛蕊花糖苷為參照，繪制14批藥材樣品的HPLC圖譜，采用《中藥色譜指紋圖譜相似度評(píng)價(jià)系統(tǒng)》（2012版）進(jìn)行相似度評(píng)價(jià)，確定共有峰，并采用SPSS 22.0軟件進(jìn)行聚類分析和主成分分析。結(jié)果：14批藥材樣品的HPLC圖譜有13個(gè)共有峰，相似度為0.674～0.996，表明14批藥材樣品相似度差異較大，部分批次相似度大于0.9（9批）。14批藥材樣品可聚為4類，S3、S5、S6、S11聚為一類，S1、S2、S4、S9、S10聚為一類，S7、S8、S13、S14聚為一類，S12為一類。經(jīng)主成分分析，主成分1和主成分2是影響藥材樣品質(zhì)量評(píng)價(jià)的主要因子，2個(gè)主成分的累積方差貢獻(xiàn)率為90.32%，以S13的主成分綜合得分最高。結(jié)論：所建指紋圖譜以及聚類分析和主成分分析結(jié)果可為尖尾風(fēng)藥材的質(zhì)量評(píng)價(jià)提供參考。
　　關(guān)鍵詞 尖尾風(fēng)；高效液相色譜法；指紋圖譜；聚類分析；主成分分析
　　中圖分類號(hào) R284.1 文獻(xiàn)標(biāo)志碼 A 文章編號(hào) 1001-0408（2018）16-2215-05
　　ABSTRACT OBJECTIVE： To establish HLPC fingerprint of Callicarpae longsissimae， and to conduct cluster analysis and principal component analysis. METHODS： HPLC method was adopted. The determination was performed on ECOSIL ODS- EXTEND C18 column with mobile phase consisted of acetonitrile-0.2% phosphoric acid solution （gradient elution） at the flow rate of 1.0 mL/min. The detection wavelength was set at 334 nm， and the column temperature was 30 ℃. The sample size was 20 μL. Using acteoside as reference， HPLC fingerprints of 14 batches of C. longsissimae were determined. The similarity of 14 batches of samples was evaluated by TCM Chromatographic Fingerprint Similarity Evaluation System （2012 edition） to confirm common peak. Cluster analysis and principal component analysis were performed by using SPSS 22.0 software. RESULTS： There were 13 common peaks in HPLC chromatograms of 14 batches of sample， the similarity of which was 0.674-0.996， indicating the similarity of 14 batches of sample was great different， but the similarity of some batches was greater than 0.9 （9 batches）. After validation， HPLC fingerprints of 14 batches of sample were in good agreement with control fingerprint. Fourteen batches of samples were clustered into 4 categories； S3，S5，S6 and S11 were clustered into one category； S1，S2，S4，S9 and S10 were clustered into one category；S7，S8，S13 and S14 were clustered into one category；S12 was clustered into one category. By principal component analysis， principal component 1 and principal component 2 were main influential factors of medcicinal material quality；accumulative variance contribution rate of them was 90.32%，and comprehensive score of S13 was the highest. CONCLUSIONS： Established fingerprint， the results of cluster analysis and principal component analysis can provide reference for quality evaluation of C. longsissimae.
　　KEYWORDS Callicarpae longsissimae； HPLC； Fingerprint； Cluster analysis； Principal component analysis

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