Prof. Hongxia Zhao Profile

Prof. Hongxia Zhao

at Ningbo Univ. of Technology

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Proceedings Article | 19 December 2022 Poster + Paper

Identification of adulterated extra virgin olive oil based on three-dimensional fluorescence characteristic peaks

Zhiqun Ding, Peihong Cheng, Hongxia Zhao, Zhuoyuan Wang, Ligang Wu

Proceedings Volume 12320, 1232028 (2022) https://doi.org/10.1117/12.2656340

KEYWORDS: Fluorescence, Quantitative analysis, Fluorescence spectroscopy, Vegetable oil, Fluorescence intensity, Spectroscopy, Doping, Statistical analysis, Data acquisition

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Extra virgin olive oil has very high nutritional value and its price is 5 to 6 times the price of ordinary cooking oil. The national standard detection of physical and chemical indicators of extra virgin olive oil requires very expensive chemical analysis instruments and related professionals, which is limited the market supervision of olive oil. Studying the threedimensional fluorescence spectra of extra virgin olive oil and other kinds edible vegetable oils revealed that the 3D fluorescence peak of extra virgin olive oil showed significant specificity with others. Three-dimensional fluorescence matrix data with full-wavelength scanning is large amounts of data, and the excitation fluorescence peak data was selected for olive oil quality algorithm study. Many oil samples were analyzed which include different brands of extra virgin olive oils, refined olive oil, and different proportions adulterated olive oil, and doped with peanut oil from 0.5% to 50%. When the fluorescence excitation wavelength was from 350~360nm, fluorescence data of three bands ranging were extracted for quality factor N, from 675~685nm, from 400~450nm, 500~525nm. N is has positive correlation with olive oil quality, resolution is 0.5%. The weighted normalized quality factor nonlinear curve fitting correlation coefficient for the quality factor based on the 3D fluorescence feature peaks reached 0 to 0.985, with a deviation of 2.63%, and the measured dynamic range was 49.6 dB. The quality factor identification method based on 3D fluorescence peak is no preprocessing and has high sensitivity. The algorithm only requires few fluorescence spectral data, which provides theoretical support for the low-cost and fast quantitative analysis of olive oil quality.

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