College of Biotechnology and Pharmaceutical Engineering, West Anhui University, Lu'an City 237012, China; School of Pharmacy, Anhui University of Traditional Chinese Medicine, Hefei 230012, China.
College of Biotechnology and Pharmaceutical Engineering, West Anhui University, Lu'an City 237012, China; The Provincial 2011 Collaborative Innovation Center of Anhui-Dendrobium Huoshanense Industrialization Exploitation Collaborative Innovation Center, Lu'an City 237012, China; West Anhui Biotechnology Research Center of Natural Medicine and Traditional Chinese Medicine, West Anhui University, Lu'an City 237012, China; College of Pharmacy, Anhui Medical University, Hefei 230032, China.
J Pharm Biomed Anal. 2018 Mar 20;151:331-338. doi: 10.1016/j.jpba.2018.01.027.
A rapid, green, low cost and nondestructive attenuated total reflection near infrared (ATR NIR) method was developed to quantify the total polysaccharide and the main monosaccharides mannose and glucose in Dendrobium huoshanense. Total 100 D. huoshanense samples from different places were analyzed using ATR NIR method. Potential outlying samples were initially removed from the collected NIR data using the PCA-Mahalanobis distance method. Spectral data preprocessing was studied in the construction of a partial least squares (PLS) model and six different signal pretreatment methods, including multiplicative scattering correction (MSC), standard normal transformation (SNV), first and second derivatives, the combination of MSC with the first derivative, and the combination of SNV with the first derivative, were compared. The results showed that the best signal pretreatment method was the spectral data pretreated by SNV combined with the first derivative due to it showed the lowest root-mean-square error of cross-validation (RMSECV), highest R for both the polysaccharide and its main monosaccharides. In order to improve the performance of the model, the pretreated full spectrum was calculated by different wavelength selection method. The results showed that the optional wavelength selection model was the one simultaneously selecting the NIR wavelength ranges 7500-5750 cm, 5250-4700 cm, 4450-4300 cm and 4200-4100 cm because of the lowest RMSECV and the highest R among the ten wavelength selection models. The external validation and the complete external validation confirmed the robustness and reliability of the developed NIR model. The contents of the total polysaccharide and the main monosaccharides are the essential quality assessment criterion for plant medicines while their traditional quantification methods involved sample destruction, tedious sample processing and non-environmentally friendly pretreatment, therefore, our study might provide an efficient technique tool for the rapid, green and nondestructive quantification of the total polysaccharide and the main monosaccharides for D. huoshanense and other rich-in-polysaccharide plant medicines.
建立了一种快速、绿色、低成本、无损的衰减全反射近红外（ATR-NIR）方法，用于定量测定霍山石斛中的总多糖和主要单糖甘露糖和葡萄糖。使用 ATR-NIR 方法分析了来自不同地方的 100 个霍山石斛总样本。使用 PCA-Mahalanobis 距离法从收集的 NIR 数据中初步去除潜在的异常样本。研究了六种不同的信号预处理方法，包括乘法散射校正（MSC）、标准正态变换（SNV）、一阶和二阶导数、MSC 与一阶导数的组合以及 SNV 与一阶导数的组合，用于构建偏最小二乘（PLS）模型中的光谱数据预处理。结果表明，由于 SNV 与一阶导数结合的光谱数据预处理方法具有最低的交叉验证均方根误差（RMSECV）和最高的多糖及其主要单糖的 R 值，因此是最佳的信号预处理方法。为了提高模型的性能，使用不同的波长选择方法计算预处理后的全谱。结果表明，同时选择 NIR 波长范围 7500-5750 cm、5250-4700 cm、4450-4300 cm 和 4200-4100 cm 的可选波长选择模型是性能最佳的模型，因为在十种波长选择模型中，该模型具有最低的 RMSECV 和最高的 R 值。外部验证和完整的外部验证证实了所开发的 NIR 模型的稳健性和可靠性。总多糖和主要单糖的含量是植物药的重要质量评估标准，而其传统的定量方法涉及样品破坏、繁琐的样品处理和非环保的预处理，因此，我们的研究可能为霍山石斛和其他富含多糖的植物药的总多糖和主要单糖的快速、绿色和无损定量提供有效的技术工具。
