Discrimination and color component correlation analysis of Citrus Medica before and after processing based on machine vision system
Objective To discriminate the different processed products of Citrus Medica and the correlation between color and component content based on machine vision system,and provide reference for quality evaluation and processing control of Citrus Medica.Methods High-performance liquid chromatography method was used to determine the contents of hesperidin,6,7-dimethoxycoumarin,Hyoscytin in Citrus Medica and its processed products.Machine vision system was used to obtain the image of the decoction pieces and extract the color features of the decoction pieces in RGB,L*a*b* and HSV color spaces.Machine learning methods,such as linear discriminant analysis(LDA),partial least squares-discriminant analysis(PLS-DA)and support vector machine(SVM),were used to establish qualitative identification model for the different processed products of Citrus Medica,and analyzed the correlation between the color eigenvalues and the contents of measured 3 components by Pearson correlation analysis.Results LDA,PLS-DA and SVM had higher prediction accuracy and lower prediction error rate.There was a certain correlation between the content of Citrus Medica and its processed product and the color characteristic values.Conclusion Based on the machine vision system,the discrimination effect for different processed products of Citrus Medica is good,and this method is simple,efficient,and accurate,which can provide reference for the quality control and clinical application of Citrus Medica and its processed products.