[Exploration of rapidly determining quality of traditional Chinese medicines by (NIR) spectroscopy based on internet...

Because of the numerous varieties of herbal species and active ingredients in the traditional Chinese medicine(TCM),the traditional methods employed could hardly satisfy the current determination requirements of TCM.The present work proposed an idea to realize rapid determination of the quality of TCM based on near infrared(NIR)spectroscopy and internet sharing mode. Low cost and portable multi-source composite spectrometer was invented by our group for in-site fast measurement of spectra of TCM samples. The database could be set up by sharing spectra and quality detection data of TCM samples among TCM enterprises based on the internet platform.A novel method called as keeping same relationship between X and Y space based on K nearest neighbors(KNN-KSR for short)was applied to predict the contents of effective compounds of the samples. In addition,a comparative study between KNN-KSR and partial least squares(PLS)was conducted. Two datasets were applied to validate above idea:one was about 58 Ginkgo Folium samples samples measured with four near-infrared spectroscopy instruments and two multi-source composite spectrometers,another one was about 80 corn samples available online measured with three NIR instruments. The results show that the KNN-KSR method could obtain more reliable outcomes without correcting spectrum.However transforming the PLS models to other instruments could hardly acquire better predictive results until spectral calibration is performed. Meanwhile,the similar analysis results of total flavonoids and total lactones of Ginkgo Folium samples are achieved on the multi-source composite spectrometers and near-infrared spectroscopy instruments,and the prediction results of KNN-KSR are better than PLS. The idea proposed in present study is in urgent need of more samples spectra, and then to be verified by more case studies.