| Obejective: Odor and color have always been an important basis for the macroscopic identification of Alpinia officinarum Hance(galangal),but the odor and color are only language descriptions,which is not conducive to the accurate grasp for practitioners.Therefore,this study introduces electronic sensory technology to digitally study the odor and color of different quality galangal,and then related the odor,color and chemical composition to interpret the scientific connotation of galangal macroscopic identification.Simultaneously,the near-infrared spectroscopy technique was introduced to establish prediction model for the chemical compositions of galangal,and to realize the rapid analysis of the components content of galangal.Method:(1)Determination of the quality grade of galangal and chemical compositions analysis: 10 Chinese medicine experts were invited to perform sensory evaluation on the traits of galangal samples,with a total score more than or equal to 70 points divided into first-class products,and less than 70 points divided into second-class products.The chemical compositions analysis method was as follows: the volatile oil content was determined by steam distillation,and the volatile oil of 30 batches of samples was analyzed by GC-MS;the content of diphenylheptane A,kaempferol and galangin was determined by HPLC;The content of the70% ethanol extract was determined by alcohol hot dip method.(2)Digital research on the odor and color of galangal: The odor of galangal was determined by electronic nose(E-nose),the odor data of different quality galangal were analysed by Matlab software,and thediscriminant model was established by linear discriminant analysis(LDA);The color of galangal was determined by colorimeter,the differences of L*,a*,b* and ?Eab of different quality galangal were analyzed and compared,and the discriminant model was established by typical discriminant analysis.(3)Correlation analysis of odor,color and chemical compositions of galangal: Pearson correlation analysis was used to study the correlation between the volatile oil content of galangal and the peak response of each sensor,and the prediction model of volatile oil content was established by multiple linear regression method;The partial least squares(PLS)was used to analyze the correlation between the volatile components of galangal and the peak response of each sensor;Pearson correlation analysis was used to study the correlation between the color values(L*,a*,b* and?Eab)of galangal and the content of chemical components.(4)Establishment of quantitative model for the components of galangal: The spectral data of galangal was collected by near-infrared spectroscopy,and the chemometric method was used to screen the spectral pretreatment method and the band.Quantitative analysis model of galangal diphenylheptane A,galangin,kaempferol and alcohol extract was established by PLS.Result:(1)Determination of the quality grade of galangal and chemical compositions analysis: According to the result of the sensory score of galangal trait,55 first-class products and 45 second-class products were finally determined.The results of chemical compositions analysis indicated that the content of volatile oil,diphenylheptane A,galangin,kaempferol and alcohol extracts of the first-class product were generally higher than second-class products.The PCA analysis of the five components can roughly distinguish the two grades of galangal,in which diphenylheptane A and alcohol extract are the key components.GC-MS analysis of volatile oil identified 43 components,but the number and the spscies of volatile components of two class products were the same,and there was no significant difference in the content of all components(P>0.05).(2)Digital research on the odor and color of galangal: Odor: The odor response value of the first-class product was higher than the second-class;There are also differences in the odor response mean,peak and variance characteristic fingerprints of different quality galangal;By screening 5~7eigenvalues from the electronic nose data,the recognition rate of the established LDA discriminant model was over 90%.Color: There were significant differences in the L*,b*,and ?Eab values of two grades of galangal(P<0),that is,the first-class products color is lighter and closer to brownish red,but the second-class products is opposite;The three-dimensional maps of L*,a*,and b* can more intuitively display the color difference of different quality galangal;The correlation coefficient between ?Eab and color sensory score was-0.71,indicating that the colorimeter's expression of galangal color was consistent with human visual sensory expression;According to the L*,b*,and ?Eab values,the average recognition rate of the discriminant model of different quality galangal was 86%.(3)Correlation analysis of odor,color and chemical compositions of galangal: Odor: the content of volatile oil was significantly positively correlated with the response values of sensors S4,S7,S8,S9 and S10;The prediction model of volatile oil content is established,the correlation coefficient R between reference and predicted values was 0.6213,and the root mean square error of predication(RMSEP)was 0.1191,which indicates that the volatile oil content can be roughly predicted by the odor response value;It can be seen from the correlation load map obtained from the PLS analysis that the response values of the electronic nose sensors are mainly related to the terpene and alcohol components.Color: the content of diphenylheptane A,galangin,kaempferol and alcohol extract was significantly positively correlated with L*,and negatively correlated with?Eab,indicating that the color of galangal is closer to brownish red,the content of the these compositions is relatively higher,which reveals the reason why the galangal is “good quality in color brown red”.(4)Establishment of quantitative model for the components of galangal: the near-infrared spectroscopy quantitative model of diphenylheptane A,galangin,kaempferol and alcohol extracts was established.The verification results indicate that: the average value of the absolute deviation between reference and predicted values of four components was 0.04%,0.02%,0.01%,and 0.46%,respectively;the correlation coefficient between reference and predicted values was 0.9672,0.9549,0.9160,and 0.9800,respectively;the relative analysis error(RPD)was 3.32,3.15,2.15,4.49,respectively.It is indicated that the quantitative model prediction ability of diphenylheptane A,galangin and alcohol extract are very robust,but the prediction accuracy of kaempferol model needs to be improved.Conclusion: There are differences in appearance traits and components content of galangal with different quality grades,and the subdivision of galangal quality grade should be emphasized.The introduction of electronic sensory technology(E-nose,colorimeter)can make the difference of odor and color of different quality galangal be digitalized and objectively expressed.It also provides a basis for further research on the correlation between odor,color and internal components of galangal,which is conducive to the interpretation of the scientific connotation of the macroscopic identification of galangal.Simultaneously,the near-infrared spectroscopy technique was introduced to establish prediction model for the content of multiple components of galangal.Therefore,through the combination of electronic sensory and near-infrared spectroscopy,the modernization of macroscopic identification of galangal and the rapid prediction of the components content can be achieved.It is conforms with the era requirements to establish an accurate,objective,rapid,simple and Internationalized method for Chinese medicine quality control and evaluation. |
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