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| Rapid Detection and Analysis of Chinese Liquor Quality by Raman
Spectroscopy Combined With Fluorescence Background |
| WANG Zhi-qiang1, CHENG Yan-xin1, ZHANG Rui-ting1, MA Lin1, GAO Peng1, LIN Ke1, 2* |
1. School of Physics, Xidian University, Xi'an 710071, China
2. Interdisciplinary Research Center of Smart Sensor, Xidian University, Xi'an 710071, China
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Abstract With its unique technical advantages, such as non-destructive detection, high sensitivity, simplicity and speed, Raman spectroscopy has shown good application potential in food safety and other fields. Liquor is a very popular drink, and everyone has highly valued its quality and safety. There are always some inferior blended liquors in the market that seriously affect everyone's health, and there is no clear detection method in the current national inspection standards to identify them. If these inferior blended liquors are quickly identified, it will effectively protect everyone's safety. We measured the Raman spectra of 56 bulk liquors and 7 bottled branded liquors using Raman spectroscopy. The fluorescence background of all spectra was analyzed with the C—C—O stretching vibration peak of ethanol at 886 cm-1 in the spectrum as the internal standard. The results show that the fluorescence background of bottled brand liquor is smaller than that of bulk liquor, which can clearly distinguish the two types of liquor samples. For the measurement and analysis of Raman spectra, it is generally believed that the fluorescence background will affect the experimental results, so various methods have been developed to reduce or subtract the fluorescence background. Our work shows that retaining the fluorescence background may be more beneficial to the quality detection of liquor. This detection method is very simple and quick to operate and analyze if this method is combined with a portable Raman spectrometer, an effective and rapid detection method can be provided for the quality and safety of liquor.
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Received: 2022-05-18
Accepted: 2022-10-31
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Corresponding Authors:
LIN Ke
E-mail: klin@xidian.edu.cn
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