光谱学与光谱分析, 2016, 36 (2): 316, 网络出版: 2016-12-09   

偏最小二乘法和THz-TDS在正品大黄鉴别中的应用

Identification of Official Rhubarb Samples by Using PLS and Terahertz Time-Domain Spectroscopy
作者单位
1 首都师范大学化学系, 北京 100048
2 首都师范大学物理系, 太赫兹光电子学教育部重点实验室, 北京 100048
摘要
太赫兹技术的发展近年来受到广泛的关注并被应用于热点。 中草药大黄的品质鉴定对于中药制剂的质量控制具有重要的意义。 利用大黄的太赫兹时域光谱结合偏最小二乘法(PLS)模型对基于41个正品和非正品大黄的中草药鉴别模型进行了研究。 首先采集大黄样品的太赫兹时域光谱(THz-TDS)信号, 然后将化学计量学方法用于这些大黄样品太赫兹光谱的信号处理与建模, 再建立基于太赫兹光谱的大黄品质鉴定的偏最小二乘模型方法。 应用S-G一阶导数、 去趋势、 标准正态变换、 自标度化、 均值中心化等方法对原始时域谱预处理再与未经预处理的结果相比, 偏最小二乘(PLS)模型的预测正确率从80%明显提高到90%。 在模型建立和模型检验中, 采用留一法(LOO)选取训练集和检验集样本。 利用留一法交叉验证确定了PLS模型的最佳主因子数。 结果表明, 当采用均值中心化方法时, PLS模型的RMSECV和RMSEP的值均达到了最小, 分别为0.076 6和0.169 0。 研究结果表明, THz-TDS技术结合化学计量学方法能够快速、 准确的对大黄的真伪进行鉴别, 直接使用太赫兹时域光谱而不使用计算后的吸收谱有两个优点: (1)在分频测定和光谱信号处理时无需考虑样品的厚度; (2)使光谱信号处理过程得到简化。 该技术也可以对其他中草药进行鉴别和质量控制。 该法快速、 简单、 无污染、 无需样品预处理, 是一种有发展前景的中草药无损检测方法。
Abstract
The development of terahertz technology is attracting broad intention in recent years. The quality identification is important for the quality control of Chinese medicine production. In the present work, terahertz time-domain spectroscopy (THz-TDS) combined with partial least squares (PLS) were used for the identification model building and studied based on 41 official and unofficial rhubarb samples. First, the THz-TDS spectra of rhubarb samples were collected and were preprocessed by using chemometrics methods rather than transformed to absorption spectra. The identification models were then established based on the processed terahertz time domain spectra. The spectral preprocessing methods include Savitzky-Golay (S-G) first derivative, detrending, standard normal transformation (SNV), autoscaling, and mean centering. The identification accuracy of 90% was accomplished by using proper pretreatment methods, which was higher than the classified accuracy of 80% without any preprocessing for the time domain spectra. The component number of the PLS model was evaluated by leave-one-out cross-validation (LOOCV). The minimum values of the root-mean squared error of cross-validation (RMSECV) and root-mean squared error of prediction (RMSEP) were 0.076 6 and 0.169 0 by using mean centering method, respectively. The results of this work showed that the combination of terahertz time domain spectroscopy technology with chemometrics methods, as well as PLS can be applied for the recognition of genuine and counterfeit Chinese herbal medicines, as well as official and unofficial rhubarbs. The advantage of using terahertz time domain spectra directly with no transformation into absorption spectra is: (1) the thickness of samples could not be considered in the model establishment, and (2) the spectral processing was simplified. The proposed method based on the combination of THz-TDS and chemometrics proved to be rapid, simple, non-pollution and solvent free, which is suitable to be developed as a promising tool for quality control of many other Chinese herbal medicines.

汪景荣, 张卓勇, 张振伟, 相玉红. 偏最小二乘法和THz-TDS在正品大黄鉴别中的应用[J]. 光谱学与光谱分析, 2016, 36(2): 316. WANG Jing-rong, ZHANG Zhuo-yong, ZHANG Zhen-wei, XIANG Yu-hong. Identification of Official Rhubarb Samples by Using PLS and Terahertz Time-Domain Spectroscopy[J]. Spectroscopy and Spectral Analysis, 2016, 36(2): 316.

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