中药材2017，Vol.40Issue(1)：32-37,6.DOI:10.13863/j.issn1001-4454.2017.01.008
基于近红外光谱和SVM算法对琥珀掺伪的定性鉴别与定量分析
Qualitative and Quantitative Analysis of Amber Adulteration Using Near Infrared Spectroscopy Based on Support Vector Machine
摘要
Abstract
Objective:To establish an identification model on amber and its adulterants of colophony by near infrared spectroscopy (NIR) combined with support vector machine(SVM),and a quantitative model was built up to predict the content of colophony in adulterants.Methods:The near infrared spectra of samples were collected and preprocessed by vector normalization and first derivative respectively.Principal component analysis(PCA) method was used to reduct the dimension,qualitative model of adulterated amber was established by support vector machine classifier(SVC).The optimal preprocessing method was determined by comparing prediction performance.Quantitative model of adulterated amber was established respectively by Partial Least Squares (PLS)and support vector machine regress (SVR).Model parameters (C,g)were optimized and determined by grid search,particle swarm optimization and genetic algorithm.Results:The accuracies of prediction set and calibration set for SVC model were up to 100％ and 97.37％;the coefficient of determination(R2) of PLS and SVR were all above 99.7％,the lowest MSE was 3.03 × 10-4.Conclusion:The established models are relatively stable,accurate and reliable for the rapid identification and the prediction of colophony content in the amber adulteration.关键词
近红外光谱/琥珀/掺伪/鉴别/支持向量机Key words
Near infrared spectroscopy/Amber/Adulteration/Identification/Support vector machine分类
医药卫生引用本文复制引用
明晶,陈龙,陈科力,黄必胜..基于近红外光谱和SVM算法对琥珀掺伪的定性鉴别与定量分析[J].中药材,2017,40(1):32-37,6.基金项目
重大新药创制国家科技重大专项(2014ZX09304307001) （2014ZX09304307001）
武汉市2012年高新技术产业发展行动计划生物技术与新医药专项(201260523193) （201260523193）
