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| Quantitative Determination of Alcohol Concentration in Liquor Based on Polarized Raman Spectroscopy |
| KANG Ying1, ZHUO Kun1, LIAO Yu-kun1, MU Bing1, QIN Ping2, LI Qian1, LUAN Xiao-ning1* |
1. College of Physics and Opto-Electronic Engineering, Ocean University of China, Qingdao 266100, China
2. College of Electronic Engineering, Ocean University of China, Qingdao 266100, China
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Abstract Due to its unique advantages of rapid, high efficiency, non-contact detection and no need for sample pretreatment, Raman spectroscopy is an ideal method for high-throughput, non-destructive on-line detection of large quantities of samples and a suitable method for rapid detection of ethanol concentration of liquor products. However, different from pure water, besides Raman characteristic peaks of ethanol and water, there is apparent fluorescence interference within the spectra of most liquor under laser excitation, which negatively influences the quantitative determination of ethanol concentration. Therefore, during the determination of ethanol concentration based on the Raman characteristic peak intensity ratio method, the data points for fluorescence background fitting need to be manually selected before data processing, which possess strong subjectivity and low data processing efficiency and is difficult to fully meet the technical requirements of the high-throughput samples on-line screening. In order to solve the above problems, based on the self-built laser-induced polarized Raman spectroscopy detection system, a series of experiments were carried out on the polarization characteristics of the Raman peaks and fluorescence background of four kinds of liquor samples under excitation of linearly polarized laser with different polarization orientation. Based on the polarization difference of them, a quantitative determination method of alcohol concentration in liquor products based on polarized Raman spectroscopy is proposed. The experimental results show that, with the aid of differential polarization Raman spectroscopy, the correlation coefficient of the polynomial fitting of three times is over 0.99, which can achieve accurate inversion of ethanol concentration in the range of 3%~97%vol. The accuracy of ethanol concentration in four kinds of liquor samples is significantly higher than the inversion results of traditional methods, which significantly improves the accuracy and efficiency of alcohol concentration determination of liquor products.
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Received: 2022-01-04
Accepted: 2022-10-18
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Corresponding Authors:
LUAN Xiao-ning
E-mail: luanxiaoning@ouc.edu.cn
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[1] The People's Republic of China General Administration of Quality Supervision, Inspection and Quarantine, China National Standardization Administration(国家质量监督检验检疫局，国家标准化管理委员会). GB/T 10781.2—2006. Mild Aromatic Chinese Spirits(GB/T 10781.2—2006. 清香型白酒). Beijing: China Standard Press(北京：中国标准出版社), 2006.
[2] WANG Tian-jiang, JIAN Hua-li, WEI Gao-li, et al(王天将, 蹇华丽, 卫高利, 等). The Food Industry(食品工业), 2016, 37(2): 149.
[3] TAN Yu-liang, JIAN Hua-li, YANG You-hui, et al(谭余良, 蹇华丽, 杨幼慧, 等). Liquor-Making Science & Technology(酿酒科技), 2009，(10): 25.
[4] Amrit Qaudel, Dhara Raijada, Jukka Rantanen. Adv. Drug. Deliv. Rev., 2015, 89(15): 3.
[5] Vickers T J, Rosen C A, Mann C K. Applied Spectroscopy, 1996, 50(8): 1074.
[6] Shaw A D, Kaderbhai N, Jones A. Applied Spectroscopy, 1999, 53(11): 1419.
[7] WU Bin, LUO Xiao-sen, LU Jian(吴 斌, 骆晓森, 陆 建). Optics and Precision Engineering(光学精密工程), 2011, (2): 392.
[8] Egashira K, NiShi N. The Journal of Physical Chemistry B, 1998, 102(21): 4054.
[9] Fountain A W, Vicker T J, Mann C K. Applied Spectroscopy, 1998, 52(3): 462.
[10] ZHANG Hong-bo, SU De-zhi, HE Yan-lan(张洪波, 宿德志, 何焰蓝). Analysis and Testing Technology and Instruments(分析测试技术与仪器), 2007, 13(3): 190.
[11] LIU Wen-han, YANG Wei, WU Xiao-qiong(刘文涵, 杨 未, 吴小琼). Chinese Journal of Analytical Chemistry(分析化学), 2007, 35(3): 416.
[12] GENG Xiang, CHEN Bin, YIN Dao-yong(耿 响, 陈 斌, 殷道永). Spectronic Instrument & Analysis(光谱仪器与分析), 2009, Z1: 134.
[13] GAO Guo-ming, LI Xue, TAN Zong-ding, et al(高国明, 李 雪, 覃宗定). Acta Optica Sinica(光学学报), 2013, 33(2): 258.
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