Abstract
Synchronous fluorescence spectrum coupled with multivariate curve resolution alternating least square (MCR-ALS) and artificial neural network (ANN) has been used for the analysis of edible vegetable oil. Four types of edible vegetable oil extracted from seed were stored at 65 °C for 0, 1, 5, 9, 13 and 17 days under control conditions. Synchronous fluorescence spectra were obtained for each sample in the excitation wavelength range of 200–800 nm with offsets (Δλ) of 10, 20, 30, 40, 50, 60, 70, 80, 90, 100, 110, 120, 130, 140, 150, 160, 170 and 180 nm between emission and excitation wavelengths. The relationship between excitation emission matrix data and peroxide value were analyzed using ANN and MCR-ALS algorithms. The regression results indicated that a rapid method for oil freshness evaluation was developed with correlation coefficient for train set and test set of 1 and 0.96, respectively.
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Acknowledgements
This study was sponsored by National Natural Science Foundation of China (31701685); Anhui Postdoctoral Science Foundation (2017B218); Anhui Postdoctoral Science (Chuzhou university) Foundation (2018bsh001).
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Gu, H., Sun, Y. & Lv, R. A feasibility study for rapid evaluation of oil quality undergoing oven treatment using synchronous fluorescence spectrum. Chem. Pap. 73, 1953–1959 (2019). https://doi.org/10.1007/s11696-019-00748-3
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DOI: https://doi.org/10.1007/s11696-019-00748-3