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    基于近红外光谱技术绿色快速预测前胡中白花前胡甲素含量

    Rapid prediction of praeruptorin A in Peucedani Radix based on NIRS

      摘要
    • 摘要:
      目的 基于近红外光谱技术(NIRS)建立前胡中白花前胡甲素的定量模型，实现对前胡质量的绿色快速评价。
      方法 运用高效液相色谱法(HPLC法)测定130份前胡样品的白花前胡甲素含量并采集其漫反射NIRS光谱，采用标准正态变换(SNV)法预处理光谱，并基于最小偏二乘回归法(PLS)建立前胡中白花前胡甲素的定量校正模型。
      结果 此模型校正集的均方根误差和相关系数分别为0.104 7和0.938 0，交叉验证的均方根误差和相关系数分别为0.123 0和0.918 0，预测集的均方根误差和相关系数分别为0.125 1和0.881 5。从此模型的校正集、预测集以及交叉验证结果来看，模型具有很高的预测精度。
      结论 此研究使用NIRS技术所建前胡的定量模型稳定可靠，可实现对市场前胡的质量的绿色快速鉴别，并为维护消费者利益和临床使用安全性，提供了科学依据。

       

      Abstract:
      Objective Near infrared spectroscopy (NIRS) was used to establish the quantitative detection model of the praeruptorin A in Peucedani Radix, so as to realize the rapid evaluation of the quality of Peucedani Radix.
      Methods The sum of praeruptorin A in 130 Peucedani Radix samples were determined by high-performance liquid chromatography (HPLC), and the NIRS diagram was collected.The quantitative correction model of praeruptorin A in Peucedani Radix was established by least partial multiplication (PLS).
      Results The root mean square error and correlation coefficient of the calibration set of this model were 0.104 7 and 0.938 0, respectively, the root mean square error and correlation coefficient of cross validation were 0.123 0 and 0.918 0, respectively.The root mean square error and correlation coefficient of the prediction set were 0.125 1 and 0.881 5, respectively.From the correction set, prediction set and cross validation results of praeruptorin A content models, the model had high prediction accuracy.
      Conclusions The quantitative detection model of Peucedani Radix established by using NIRS is stable and reliable, which can realize the rapid eevaluation of the quality of Peucedani Radix in the market, and provide scientific basis for safeguarding consumers' interests and clinical safety.

       

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