Wang Xinhong, Wang Xiaoguang, Guo Yuhai
College of Agronomy, China Agricultural University, Yuanming Yuan West Road, Haidian District, Beijing 100193, China.
Molecules. 2017 May 19;22(5):843. doi: 10.3390/molecules22050843.
Quantitative determination of multiple effective components in a given plant usually requires a very large amount of authentic natural products. In this study, we proposed a rapid and non-destructive method for the simultaneous determination of echinacoside, verbascoside, mannitol, sucrose, glucose and fructose in Cistanche tubulosa by near infrared spectroscopy (NIRS). Near infrared diffuse reflectance spectroscopy (DRS) and high performance liquid chromatography (HPLC) were conducted on 116 batches of C. tubulosa samples. The DRS data were processed using standard normal variety (SNV) and multiplicative scatter correction (MSC) methods. Partial least squares regression (PLSR) was utilized to build calibration models for components-of-interest in C. tubulosa. All models were then assessed by calculating the root mean square error of calibration (RMSEC), correlation coefficient of calibration (r). The r values of all six calibration models were determined to be greater than 0.94, suggesting each model is reliable. Therefore, the quantitative NIR models reported in this study can be qualified to accurately quantify the contents of six medicinal components in C. tubulosa.
对给定植物中多种有效成分进行定量测定通常需要大量的正宗天然产物。在本研究中，我们提出了一种快速且无损的方法，通过近红外光谱（NIRS）同时测定管花肉苁蓉中的松果菊苷、毛蕊花糖苷、甘露醇、蔗糖、葡萄糖和果糖。对116批次的管花肉苁蓉样品进行了近红外漫反射光谱（DRS）和高效液相色谱（HPLC）分析。DRS数据采用标准正态变量变换（SNV）和多元散射校正（MSC）方法进行处理。利用偏最小二乘回归（PLSR）建立管花肉苁蓉中目标成分的校准模型。然后通过计算校准均方根误差（RMSEC）、校准相关系数（r）对所有模型进行评估。所有六个校准模型的r值均大于0.94，表明每个模型都是可靠的。因此，本研究报道的近红外定量模型能够准确地定量管花肉苁蓉中六种药用成分的含量。
