Quantitative determination of the carbonyl value in frying oils based on LF-NMR combined with chemometrics

Abstract

Low-field nuclear magnetic resonance (LF-NMR) combined with chemometrics was used for the rapidly and nondestructively quantitative determination of carbonyl value (CV) of frying oils during frying process. The quality indices of frying oils during frying process were analyzed as well as the changes of its LF-NMR signal, followed by exploring the correlation between the quality indices of frying oils and the relaxation-characteristic indices and investigating the influences of modeling data and preprocessing methods on the modeling performance. Based on the echo decay curves data of LF-NMR and the relaxation-characteristic indices data, the prediction model of CV was established by partial least square (PLS), principal component regression (PCR), multiple linear regression (MLR), and support vector machine regression (SVR). Results showed that there was a significant correlation between CV and relaxation-characteristic indices (p<0.01) with both modeling data and preprocessing methods affecting the model performance. The prediction performance of non-linear SVR model was significantly superior to that of linear modeling methods (PLS, PCR, and MLR). The best prediction model of CV was built using the SVR method based on echo decay curves data. The root mean square error of prediction and coefficient of determination were 2.599 mmol/kg and 0.9873, respectively.