Study On On - Line Near Infrared Real - Time Detection Method For Extraction Process Of Chinese Materia Medica

There are many sections in traditional Chinese medicine (TCM) production, and as the main section which the active pharmaceutical ingredients (API) dissoluted most, the extraction process can directly affects the quality and stability of the production. Therefore, the study on extraction process is regarded as an important significance. However, there were some problems in the extraction process, such as the intrinsic quality parameters failed to detect in real-time, the quality control measures were lacked in the production process. Same as pharmaceutical, the quality of production in TCM must be ensured.Therefore, during the extraction process, some TCM decoction pieces were used as carrier, on-line NIR technology was applied to collect the spectra of active pharmaceutical ingredients (API) in real-time. The aim was to achieve real-time detection on the intrinsic quality and improve quality control method of TCM decoction pieces. The main contents are as follows:Firstly, on-line NIR technology was applied to collect the spectra of TCM decoction pieces in pilot-scale extraction process based on the NIR platform which was built by ourselves. NIR models were built to achieve on-line detection and ensure the stability quality. Five TCM decoction pieces (sophora flower, baikal skullcap root, bitter orange, tangerine peel and cassia twig) were selected to research. nine kinds of API in them were used to on-line detect by NIR, and different data preprocessing methods were applied to analyze NIR data. Then the models result was evaluate by the parameters of NIR model which were built by the data of NIR and high performance liquid chromatography (HPLC). The result shown that rutin in sophora flower, the root mean square error of calibration (RMSEC) was 0.0540, the root mean square error of cross-validation (RMSECV) was 0.1110, the root mean square error of prediction (RMSEP) was 0.1421, the corresponding coefficient of determination was approach to 1. For baicalin in baikal skullcap root, the RMSEC was 0.0927, the RMSECV was 0.1344, R2 was approach to 1. The result above shown that on-line NIR could be applied in the single component detection of TCM decoction pieces extraction process. For hesperidin in bitter orange, the RMSEC was 0.0066, the RMSECV was 0.0079, R2 was almost 0.97. For naringin in bitter orange, the RMSEC was 0.0469, the RMSECV was 0.0550, R2 was above 0.98. For neohesperidin in bitter orange, the RMSEC was 0.0406, the RMSECV was 0.0219, R2 was almost 0.99. For hesperidin in tangerine peel, the RMSEC was 0.0169, the RMSECV was 0.0550, R2 was above 0.97. For synthesis of nobiletin in tangerine peel, the RMSEC was 0.00046, the RMSECV was 0.00057, R2 was above 0.97. For cinnamaldehyde in cassia twig, the RMSEC was 0.0793, the RMSECV was 0.0993, R2 was above 0.90. For coumarin in cassia twig, the RMSEC was 0.0042, the RMSECV was 0.0036, R2 was about 0.92. The results shown that on-line NIR could also achieve good result on the multi component detection of TCM decoction pieces extraction process.Secondly, a comprehensive study about nine kinds of API in NIR modeling process was carried out. And three key techniques (pretreatment method selection, band selection and model assessment validation) were validated in detail. The similarities and differences in different pretreatment methods were compared, the model superiority of bands using SiPLS was validated against other bands which were not selected by SiPLS. Residual predictive deviation (RPD) was proposed to evaluate the model performance, and the value of RPD in nine kinds API was all above 3 except hesperidin in tangerine peel and coumarin in cassia twig (about 2.63). The research fully proved that the on-line NIR could be applied in the extraction process of TCM decoction pieces and ensure validity and reliability of API.In conclusion, the result of five TCM decoction pieces NIR models was good, which could be regarded as certain reference significance in the rapid detection (real-time) of TCM decoction pieces production process using on-line NIR.