Abstract

Morindae officinalis radix (MOR) is a famous Chinese herbal medicine which has long history of use in medicine and food. MOR and MOR with steaming process (PMOR) are the most commonly used forms in in clinical and health care. In order to establish a fast and mostly nondestructive quality control method for MOR, 183 beaches of MOR samples and 20 beaches of PMOR samples were collected commercially from major producing areas in Guangdong, Fujian and Guangxi Provinces of China. To predict main components of MOR, a calibration model was established based on near-infrared spectroscopy with partial least square regression. The model was optimized by compared the parameters of root mean square error of prediction (RMSEP), root mean square error of cross validation (RMSECV), coefficient of correlation (R2) and ratio of performance to deviation (RPD). Comparative studies were performed to evaluate the performance of models by different spectra preprocessing methods and different data set. The results showed that the model performance was improved with standard normal variate spectra preprocessing methods and when the data set contained both MOR and PMOR samples. A few PMOR samples were added to MOR samples data set the model predictive performance could be improved. The contents of 14 components were predicted in MOR with lower RMSEP and RMSECV, and higher R2 and RPD, including fructose (12.8mg/g, 16.3mg/g, 0.9873, 10.10), glucose (7.28mg/g, 8.73mg/g, 0.9611, 6.21 sucrose (9.24mg/g, 9.10mg/g, 0.8419, 1.75), GF2(9.42mg/g, 11.3mg/g, 0.8526, 2.03), GF3(7.98mg/g, 9.20mg/g, 0.8756, 2.74), GF4(6.81mg/g, 8.93mg/g, 0.8663, 3.06), GF5(8.13mg/g, 8.85mg/g, 0.9001, 3.06), GF6(6.40mg/g, 6.95mg/g, 0.9145, 3.27), GF7(5.53mg/g, 6.15mg/g, 0.9195, 3.57), GF8(5.40mg/g, 6.02mg/g, 0.9179, 3.31), GF9(3.00mg/g,4.35mg/g,0.9446, 5.03),GF10(4.08mg/g, 5.34mg/g, 0.8983, 3.62), GF11(8.97mg/g, 7.70mg/g, 0.8683, 2.01) and iridoid glycosides (4.12mg/g, 5.51mg/g, 0.8712, 2.43). The model established in this paper could predict 14 components of MOR. The results would provide a reference method for the quality control of Chinese medical materials and their process products.

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