Research On The Geographical Tracing And Polyphenol Compounds Of Black Wolfberry(Lycium Ruthenicum Murray)Based On HPLC-MS And Hyperspectral Imaging Technology

Black wolfberry(Lycium ruthenicum Murray)is widely distributed in western China and some Central Asian countries.It is a new food material with high content of polyphenols,which have been confirmed as the main source of their antioxidant and other activities by modern pharmacological studies,and the important characterization of the quality evaluation of black wolfberry.As the representative component of black wolfberry,anthocyanin has very little structural differences due to its complex glycosylation,acylation and cis-trans configuration,which is difficult to isolate and identify.In addition,the quality of black wolfberry from different origins has great differences,while there are currently few researches on quality comparison and traceability methods of black wolfberry from different origins.Therefore,this thesis selected the dried black wolfberry from Gansu,Ningxia,Xinjiang,and Qinghai province of China as research objects.Firstly,the content of polyphenols and their chemical antioxidant activity were compared,and the structure of anthocyanins were identified.The quality comparison of black wolfberry from different places were compared according the above indexes.After combined the high-performance liquid chromatography and principal component analysis,this thesis achieved the classification of the origin of black wolfberry.A non-destructive detection model of black wolfberry origin was established by applying hyperspectral imaging(HSI)technology,and a non-destructive quantitative model of polyphenols content was established by combining HSI with chemical quantitative determination,all of which achieved good prediction results.The main research contents and results were as follows:(1)The quality of black wolfberry from different origins were compared.The content of polyphenols and chemical antioxidant activity of black wolfberry from different origins were significantly different.Comprehensive evaluation showed that the quality of black wolfberry from Qinghai was better among the samples we chosen,followed by black wolfberry from Xinjiang,Ningxia,and Gansu.The anthocyanins of black wolfberry from different origins were extracted and identified.Results showed that the composition of anthocyanins of black wolfberry from different origins were basically the same,and they were mainly composed of petunidin derivatives,which accounted for more than 80%of the total content.Petunidin-3-O-rutinoside(trans-p-coumaryl)-5-O-glucoside had the highest content,accounting for about 50%of the total content.A total of 17 anthocyanins were isolated and 15 structures were identified in the study,including a new structure,inferred as petunia-3-O-rhamnoside(p-coumaryl)-5-O-glucose Glycoside.(2)A destructive classification method and a non-destructive classification method were established for geographical tracing of black wolfberry.Anthocyanin fingerprints of black wolfberry were established based on the quantative data of anthocyanin by HPLC.Through principal component analysis(PCA),this thesis achieved the classification of black wolfberry from different origins.Based on the original peak area data of the anthocyanin fingerprint,a clear classification was also achieved through PCA,which eliminated the complexity of calculation and analysis process,and was first proposed and verified in this paper.After hyperspectral images of black wolfberry were collected in the wavelength range of 975 to 1646nm,the PLS-DA and SVM models based on full spectrum and characteristic wavelengths through PCA selection were established.Both models could accurately predict the origin of black wolfberry.The former had an accuracy rate of more than 90%,and the latter had an accuracy rate of more than 80%.It provided a fast and non-destructive detection method for the origin of black fruit wolfberry.(3)Non-destructive quantitative methods for polyphenols in black wolfberry was established.Based on the hyperspectral image of black wolfberry collected in the wavelength range of 975 to 1646nm,PLSR and LS-SVM models based on the full spectrum and characteristic wavelength selected by the successive projections algorithm(SPA)were established with the combination of chemical quantitative data of polyphenols,respectively.The model set decision coefficient R~2c and prediction set decision coefficient R~2p were both higher than 0.9,and the RPD values were higher than 3.0,which showed precise prediction,and the visual distribution images were calculated.Based on the quantitative data of 12 anthocyanin monomers,a full-spectrum PLSR and LS-SVM anthocyanin monomer content prediction model was established,which could achieve the content prediction,but more samples were needed to be studied to improve the accuracy and stability of the model.A prediction model of PLSR and LS-SVM anthocyanin monomer content based on the characteristic wavelength selected by SPA was established.For different anthocyanins,the prediction trend of the regression analysis model based on characteristic wavelength selection was consistent with the prediction result trend of the regression analysis model based on full spectrum.The overall results showed that the hyperspectral imaging technology could be used for the quantitative determination of polyphenols in black wolfberry.