Identification of curcumin content in raw and vinegar-processed rhizomes of Curcuma kwangsiensis based on electronic nose combined with back propagation neural network
(2.School of Pharmacy, Nanjing University of Chinese Medicine, Nanjing, Jiangsu province, China 210023)
【Abstract】This study established a rapid and accurate method for the identification of raw and vinegar-processed rhizomes of Curcuma kwangsiensis to predict the curcumin content for scientific evaluation. A complete set of bionics recognition mode was adopted. The digital odor signal of raw and vinegar-processed rhizomes of C. kwangsiensis was obtained by the electronic nose (E-nose) and analyzed by back propagation (BP) neural network algorithm, with the accuracy, the sensitivity, and specificity in the discriminant model, correlation coefficient as well as the mean square error in the regression model as the evaluation indexes. The experimental results showed that the three indexes of the E-nose signal discrimination model established by the neural network algorithm were 100% in training set, correction set and prediction set, which were obviously superior to the traditional decision tree model, naive bayes model, support vector machine, K-nearest neighbor, and boost model, and could accurately differentiate the raw and vinegar-processed products. Correlation coefficient and mean square error of the regression model in prediction set were 0.974 8 and 0.117 5 respectively, which could well predict curcumin content in C. kwangsiensis, and demonstrate the superiority of the simulation biometrics model in the analysis of Chinese medicine. By BP neural network algorithm, E-nose odor fingerprint could quickly, conveniently and accurately realize the discrimination and regression, which suggested that more bionics information acquisition and identification patterns could be combined in the field of Chinese medicine to provide ideas and methods for the rapid evaluation and standardization of the quality of Chinese medicine.
【Keywords】 Curcuma kwangsiensis; vinegar-processed rhizomes of Curcuma kwangsiensis; electronic nose; BP neural network; curcumin; content prediction;
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