目的 本实验提出了一种大黄药材及饮片类别鉴定预测模型的构建方法,预测模型包括真伪预测及种属预测2个模型。方法 样品经甲醇超声提取,超高效液相色谱法(UPLC)分离,DAD检测器多波长检测。经MPP多变量统计分析软件处理、筛选,通过揭示不同大黄成分的差异性和共性的变化,基于偏最小二乘判别分析法(PLS-DA)建立了正品与非正品大黄预测模型及区分3种正品大黄的预测模型。结果 2个模型经验证均具有100%的识别和预测准确性。采用建立的模型对15个未知大黄样本进行了分类预测,预测结果置信度均大于0.57。结论 基于UPLC指纹图谱结合PLS-DA建立的高精度统计学类别预测模型,整体性强,结论可靠,为大黄药材及饮片的真伪鉴别、基源种属鉴别提供了快捷、易行、可靠的依据。
Abstract
OBJECTIVE To establish new category identification models of Rhei Radix et Rhizoma for authenticity and species prediction. METHODS The samples were extracted by ultrasonic with methanol, separated by UPLC and detected by DAD. Data were processed and screened by MPP software to reveal the variation of components of Rhei Radix et Rhizoma. The category prediction models were established to distinguish authentic from unauthentic Rhei Radix et Rhizoma and three species of authentic Rhubarb. RESULTS These models were confirmed to prensent prediction accuracy of 100%. Fifteen samples were predicted and classified with confidence level of greater than 0.57. CONCLUSION The prediction model is simple, reliable and accurate. It is suitable for the identification and quality evaluation of different species of Rhei Radix et Rhizoma crude drugs and decoction pieces.
关键词
超高效液相色谱法 /
大黄 /
类别鉴定 /
预测模型 /
偏最小二乘判别分析
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Key words
UPLC /
Rhei Radix et Rhizoma /
category identification /
prediction model /
PLS-DA
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中图分类号：
R284
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参考文献
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[7] LIU C M, HUA Z D, BAI Y P, et al. Determination of opium alkaloids and discrimination of sample origins by UPLC/Q-TOF and PLS-DA [J]. Chin J Forensic Sci (中国司法鉴定), 2014, 73(2):25-38.
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脚注
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基金
国家十二五“重大新药创制”科技重大专项资助项目(2014ZX09304307-002);国家自然科学基金资助项目(81303214);中国食品药品检定研究院中青年发展研究基金资助项目(2013WA8)
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