Qualitative Analysis Model Of Tibetan Medicinal Herbs With Tibetan Characteristics Based On Physical Infrared Spectroscopy

As a part of traditional Chinese medicine and ethnic medicine,Tibetan medicine has a history of more than two thousand years.Due to the uniqueness of the growing environment,Tibetan medicine has some irreplaceable therapeutic and medical values,and has been playing its own charm and value in the medical world.Along with the development of the Internet,the popularity of Tibetan medicine has gradually risen and its demand has been increasing.At the critical moment of nationalization and globalization of Tibetan medicine development,the development of Tibetan medicine business is on the verge of bottleneck: Tibetan herbs are mostly wild herbs with limited resources;the varieties are confusing;the research on chemical composition and pharmacological effects of Tibetan medicine is still at a relatively low level,and these dilemmas need to be solved urgently.Physical infrared spectroscopy can not only study the structural content of chemical components,but also be used for anti-counterfeit identification and quality appraisal.Infrared spectroscopy is a new trendy analytical detection method in recent years,which has the advantages of nondestructive,rapid,effective,highly characteristic,low dosage and versatility,and has certain advantages in nondestructive identification,authenticity identification and quality evaluation of medicinal herbs.Chemometrics is an emerging interdisciplinary discipline.It plays a vital role in the field of pharmacology in combination with physical infrared spectroscopy,and is most prominent in spectral analysis and model building.Analysis of near-infrared spectra of medicinal herbs is one of the methods for identification,composition analysis,and quality control of Tibetan medicinal herbs.In this study,based on physical infrared spectroscopy combined with chemometric method,we performed characteristic absorption group analysis,cluster analysis,and established classification and regression models for qualitative analysis of Tibetan medicinal herbs(Rhodiola rosea,Ganoderma lucidum,Cordyceps sinensis and Asparagus)with the aim of promoting the further development of Tibetan medicine,providing a theoretical basis for anti-counterfeit identification of Tibetan medicinal herbs,and providing technical support for the establishment of qualitative analysis models for other medicinal herbs.The results of the study are as follows:(1)The characteristic absorption peaks corresponding to Rhodiola rosea are caused by the multiplicative frequency combined absorption of N-H and O-H groups.(2)Based on the actual conditions of Rhodiola rosea,different parts of different varieties of Ganoderma herbs were subjected to motif analysis,and the classification boundaries of Ganoderma herbs were clarified based on the Ming’s distance clustering analysis method: when the cap distance and stalk distance were equal to 3,all Ganoderma samples could be classified into 4 major categories;after the second-order derivative pretreatment of different varieties of Ganoderma,10 varieties of Ganoderma samples had clear classification boundaries.The differences between species were small and the similarity was high,indicating that the affinity between Ganoderma species was high.This was used to reveal the similarities and differences among different Ganoderma species,and an attempt was made to establish a clustering model to provide some degree of reference for interspecific substitution and evaluation of medicinal efficacy of Ganoderma species.(3)Three qualitative classification models of Cordyceps were established by pre-processing and variable screening of Cordyceps from Tibet and Qinghai,and the accuracy and number of misclassification cases(misclassification rate)were used as indicators to evaluate the models.The model is stable and reliable,with zero false positive cases,and has strong classification and prediction performance.The results show that the qualitative analysis models of different origins of Cordyceps samples have good separation and can provide technical support for the origin discrimination of Tibetan medicine.(4)The qualitative classification model of "Normalization+UVE+RF" for asparagus had an accuracy of 100% in the training set,60% in the prediction set,and an AUC value of 0.8571,which is a general classification effect and can classify asparagus samples well.The "MSC+UVE+PLSR" qualitative regression model for asparagushas better accuracy and poor stability,and the performance of the prediction set has improved compared with the training set.The "normalized+UVE+RF" qualitative analysis model for asparagus can be used to identify the origin of asparagus samples,which is fast,si-mple and accurate,and provides a new method for the qualitative analysis and identification of asparagus.The above results can provide a new way of thinking for the accurate identification and classification of Cordyceps and asparagus samples of different origins,and provide a new direction for the scientific development,classification and qualitative analysis of other Tibetan medicinal materials.