• Spectroscopy and Spectral Analysis
  • Vol. 40, Issue 10, 3113 (2020)
Wei-wei ZHANG*, Yan-hui SUN, Hai-yang GU, Ri-qin LÜ, and Wen-zheng WANG
Author Affiliations
  • School of Biological Science and Food Engineering, Chuzhou University, Chuzhou 239000, China
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    DOI: 10.3964/j.issn.1000-0593(2020)10-3113-05 Cite this Article
    Wei-wei ZHANG, Yan-hui SUN, Hai-yang GU, Ri-qin LÜ, Wen-zheng WANG. Application of Synchronous Fluorescence Spectroscopy and Chemometric Models for Rapid Evaluating Peanut Oil Oxidative Stability[J]. Spectroscopy and Spectral Analysis, 2020, 40(10): 3113 Copy Citation Text show less

    Abstract

    At present, the tradition way to detect the oxidative stability could not provide information about a variety of chemical species and simultaneously in real time, and so on. Synchronous fluorescence spectroscopy is considered to be an ideal method, because it is sensitive and reproducible, and should be amenable to longer periods. Combined methods of synchronous fluorescence spectrometer with chemometrics were to monitor the oxidation of peanut oil, which were stored under OXITEST oil oxidation stabilizer to carry out accelerated oxidation test. There was the oxidation induction curve in the accelerated oxidation test, and meanwhile, the 3D synchronous fluorescence spectral data and physical and chemical indexes were collected. The results showed that the Induction Period (IP) of cold pressed peanut oil was worse than that of hot-pressed peanut oil. The hot-pressed peanut oil was roasted at high temperature, which made antioxidant substances to improve the oxidation stability. It was clearly showed induction period, oxidation period and the static period from the oxidation curve. The fluorescence peak of Ex shifted from 300~400 to 400~450 nm. With the increment of oxidation time, the fluorescence peak changed significantly, and the red shift appeared in the fluorescence wavelength. Data multidimensional was reduced by the parallel factor analysis (PARAFAC) method. It was used to select an optimized Δλ of 70 nm on 6 components with the adequate loading score. Then the artificial neural network (ANN) was used to build a regression model for both synchronous fluorescence and the acid value and peroxide value respectively to evaluate the degree of the oil oxidation. The peanut oil exhibited a high regression coefficient (R=0.99) between fluorescence intensity and acid value in the training and the testing. The overall results suggested that synchronous fluorescence spectroscopy combined with chemometrics was useful for rapidly monitoring oil oxidation process in time, and could provide a theoretical basis for the formation of oxidation products and evolution of fluorescence spectra.
    Wei-wei ZHANG, Yan-hui SUN, Hai-yang GU, Ri-qin LÜ, Wen-zheng WANG. Application of Synchronous Fluorescence Spectroscopy and Chemometric Models for Rapid Evaluating Peanut Oil Oxidative Stability[J]. Spectroscopy and Spectral Analysis, 2020, 40(10): 3113
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