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| Determination of cream adulterated with non-dairy whip topping using1H NMR combined with principal component analysis and supportvector machines |
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| DOI：10.12166/j.zgyz.1003-7969/2020.01.009 |
| KeyWord:1H nuclear magnetic resonance spectroscopy (1H NMR) principal component analysis (PCA) support vector machines (SVM) cream non-dairy whip topping quantification of adulteration |
| FundProject:国家重点研发计划（2018YFC1602304） |
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| Abstract: |
| The adulteration of non-dairy whip topping in cream was analysed using 1H NMR combined with principal component analysis (PCA) and support vector machines (SVM).1H-NMR was subsection integrated and normalized, and spectral dimension was also reduced through PCA. The cross validation was applied to optimize the parameters of PCA-SVM. The calibration model of determination of cream adulterated with non-dairy whip topping was established using the optimal parameters of PCA-SVM.The performance of PCA-SVM models was compared with partial least squares (PLS)and SVM, and the feasibility of these three methods was examined on the testing set. The results showed that the RMSECV and RMSEP obtained for PCA-SVM were 3.69 and 5.87 respectively, and the determination coefficients of the training set and testing set were 0.987 5 and 0.974 3 respectively. The stability, accuracy and prediction ability of the model were better than PLS and SVM algorithm, and the running speed was faster than SVM algorithm. In conclusion, a combination of 1H NMR with PCA-SVM method could quickly and accurately determined the content of adulterated non-dairy whip topping in cream, which could provide technical support for regulating the quality supervision of bakery products such as cream cake on the market. |
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