Applying computer technology to the field of food safety,and how to identify liquor quickly and accurately,is of vital importance and has become a research focus.In this paper,sparse principal component analysis(SPCA)...Applying computer technology to the field of food safety,and how to identify liquor quickly and accurately,is of vital importance and has become a research focus.In this paper,sparse principal component analysis(SPCA)was applied to seek sparse factors of the mid-infrared(MIR)spectra of five famous vintage year Chinese spirits.The results showed while meeting the maximum explained variance,23 sparse principal components(PCs)were selected as features in a support vector machine(SVM)model,which obtained a 97%classification accuracy.By comparison principal component analysis(PCA)selected 10 PCs as features but only achieved an 83%classification accuracy.Although both approaches were better than a direct SVM approach based on the classification results(64%classification accuracy),they also demonstrated the importance of extracting sparse PCs,which captured most important information.The combination of computer technology SPCA and MIR provides a new and convenient method for liquor identification in food safety.展开更多
基金This work was financially supported by the National Nature Science Foundation of China(Grant Number:61962010).
文摘Applying computer technology to the field of food safety,and how to identify liquor quickly and accurately,is of vital importance and has become a research focus.In this paper,sparse principal component analysis(SPCA)was applied to seek sparse factors of the mid-infrared(MIR)spectra of five famous vintage year Chinese spirits.The results showed while meeting the maximum explained variance,23 sparse principal components(PCs)were selected as features in a support vector machine(SVM)model,which obtained a 97%classification accuracy.By comparison principal component analysis(PCA)selected 10 PCs as features but only achieved an 83%classification accuracy.Although both approaches were better than a direct SVM approach based on the classification results(64%classification accuracy),they also demonstrated the importance of extracting sparse PCs,which captured most important information.The combination of computer technology SPCA and MIR provides a new and convenient method for liquor identification in food safety.
