|
|
|
|
|
|
Rapid Detecting Study of Sodium Saccharin Additive in Spirit with SERS |
CHEN Si1, GUO Ping2, WAN Jian-chun2, LUO Peng-jie3, WU Rui-mei4, WANG Wen-jun1* |
1. Institute of Food and Biological Engineering, Jiangxi Agricultural University, Nanchang 330045, China
2. Entry-Exit Inspection and Quarantine, Jiangxi Province, Nanchang 330002, China
3. China National Center for Food Safety Risk Assessment, Beijing 100022, China
4. Optics-Electrics Application of Biomaterials Lab, Jiangxi Agricultural University, Nanchang 330045, China |
|
|
Abstract In this paper, surface enhanced Raman spectroscopy (SERS) was employed to realize quick detection of illegally additive (sodium saccharin sweeteners) in spirit. Gold colloid was used to enhance Raman signal of molecule. Several parameters such as the volume ratio of gold colloid, detection sample and sodium chloride solution, time of mixing, pH value of working buffer were optimized. The results illustrated that the strength of Raman signal was maximum when the volume ratio of gold colloid, detection sample and sodium chloride solution, time of mixing, pH value of working buffer were 1∶1∶0.5, 5 min and 4, respectively. Contrasting the test values of sodium saccharin sweeteners and the simulation values with Density Functional Theory, and three characteristic peaks of sodium saccharin sweeteners such as 1 148, 1 164 and 1 296 cm-1 were found. These characteristic peaks could be as a basis for qualitatively and quantitatively analyzing sodium saccharin sweeteners in spirit. The standard curve of saccharin sodium concentration in spirit was established based on the strength of 1 164 cm-1. The results indicated that the curve possessed a good linear relationship within the range of 1 and 20 mg·L-1, and the determination coefficient was 0.993 3. Average recovery of saccharin sodium in spirit was 98.57%~102.5%, and the relative standard deviation (RSD) was 2.44%~8.6%. The minimum detectable concentration of sodium saccharin sweeteners in spirit reached to 1 mg·L-1 and the detection time of a sample was within 10 min. The study indicated that SERS method could rapidly and accurately identify saccharin sodium sweeteners in spirit. This study can offer a method as a support for the development of real-time and rapid detection device in liquor.
|
Received: 2016-05-05
Accepted: 2016-10-12
|
|
Corresponding Authors:
WANG Wen-jun
E-mail: wwjun9999@sina.com
|
|
[1] YAO Xiu-juan,WANG Zhi-qiang(姚秀娟,王志强). Environmental and Occupational Medicine(环境与职业医学),2015,32(7):686.
[2] YU Min,WU Teng,ZHAO Gui-rong,et al(于 敏,吴 腾,赵桂荣,等). China Dairy Industry(中国乳品工业),2014,42(6):52.
[3] Lorenzoa R A, Penaa M T, Fernándezb P, et al. Food Control, 2015, 47: 43.
[4] LIU Chao,LUO Hong-xia,HUANG Guang-xue,et al(刘 超,罗红霞,黄广学,等). China Food Additives(中国食品添加剂),2015,4:199.
[5] XIONG Jun-fei,WU Rui-mei,GUO Ping,et al(熊俊飞,吴瑞梅,郭 平,等). Modern Food Science and Technology(现代食品科技),2016, 1(4): 283.
[6] Aline L F, Diego P, Hélio F D S, et al. Spectrochimica Acta. Part A: Molecular and Biomolecular Spectroscopy, 2015, 136(B): 979.
[7] Jokerst J V, Cole A J, Bohndiek S E, et al. Applied Spectroscopy, 2014, 68(4): 483.
[8] Jokerst J V, Cole A J, Bohndiek S E, et al. Proceedings of SPIE-the International Society for Optics and Photonics, 2014, 8943(1): 2858.
[9] Vlastimil P, Martin J. Analytical Chemistry, 2015, 87(5): 2840.
[10] XU Xue-qin,LIU Qiong-hua,YANG Fang,et al(许雪琴,刘琼华,杨 方,等). Spectroscopy and Spectral Analysis(光谱学与光谱分析),2015,35(11):3092.
[11] Fu D Y, Yuan D, Zhang X F, et al. Advanced Materials Research,2014, 960-961: 32.
[12] LIN Lei,WU Rui-mei,WANG Xiao-bin,et al(蔺 磊,吴瑞梅,王晓彬,等). Modern Food Science and Technology(现代食品科技), 2015, 31(5): 291.
[13] ZHU Zi-ying,GU Ren-ao,LU Tian-hong(朱自莹,顾仁敖,陆天虹). The Application of Raman Spectra in Chemistry(拉曼光谱在化学中的应用). Shenyang:Northeast University Press(沈阳:东北大学出版社),1998.
[14] ZHU Zi-ying(朱自莹). The Characteristic Raman Frequency of Organic Compound(有机化合物的特征拉曼频率). Beijing:Chinese Chemical Society(北京:中国化学会),1980.
[15] LUO Wei-qi,CHENG Han-wen,HUAN Shuan-yan,et al(罗伟琪,成汉文,宦双燕,等). Analytical Chemistry(分析化学),2011,39(7):1003. |
[1] |
XING Hai-bo1, ZHENG Bo-wen1, LI Xin-yue1, HUANG Bo-tao2, XIANG Xiao2, HU Xiao-jun1*. Colorimetric and SERS Dual-Channel Sensing Detection of Pyrene in
Water[J]. SPECTROSCOPY AND SPECTRAL ANALYSIS, 2024, 44(01): 95-102. |
[2] |
WANG Zhi-qiang1, CHENG Yan-xin1, ZHANG Rui-ting1, MA Lin1, GAO Peng1, LIN Ke1, 2*. Rapid Detection and Analysis of Chinese Liquor Quality by Raman
Spectroscopy Combined With Fluorescence Background[J]. SPECTROSCOPY AND SPECTRAL ANALYSIS, 2023, 43(12): 3770-3774. |
[3] |
LU Wen-jing, FANG Ya-ping, LIN Tai-feng, WANG Hui-qin, ZHENG Da-wei, ZHANG Ping*. Rapid Identification of the Raman Phenotypes of Breast Cancer Cell
Derived Exosomes and the Relationship With Maternal Cells[J]. SPECTROSCOPY AND SPECTRAL ANALYSIS, 2023, 43(12): 3840-3846. |
[4] |
WANG Qi-biao1, HE Yu-kai1, LUO Yu-shi1, WANG Shu-jun1, XIE Bo2, DENG Chao2*, LIU Yong3, TUO Xian-guo3. Study on Analysis Method of Distiller's Grains Acidity Based on
Convolutional Neural Network and Near Infrared Spectroscopy[J]. SPECTROSCOPY AND SPECTRAL ANALYSIS, 2023, 43(12): 3726-3731. |
[5] |
GUO He-yuanxi1, LI Li-jun1*, FENG Jun1, 2*, LIN Xin1, LI Rui1. A SERS-Aptsensor for Detection of Chloramphenicol Based on DNA Hybridization Indicator and Silver Nanorod Array Chip[J]. SPECTROSCOPY AND SPECTRAL ANALYSIS, 2023, 43(11): 3445-3451. |
[6] |
LI Wen-wen1, 2, LONG Chang-jiang1, 2, 4*, LI Shan-jun1, 2, 3, 4, CHEN Hong1, 2, 4. Detection of Mixed Pesticide Residues of Prochloraz and Imazalil in
Citrus Epidermis by Surface Enhanced Raman Spectroscopy[J]. SPECTROSCOPY AND SPECTRAL ANALYSIS, 2023, 43(10): 3052-3058. |
[7] |
GUO Ge1, 3, 4, ZHANG Meng-ling3, 4, GONG Zhi-jie3, 4, ZHANG Shi-zhuang3, 4, WANG Xiao-yu2, 5, 6*, ZHOU Zhong-hua1*, YANG Yu2, 5, 6, XIE Guang-hui3, 4. Construction of Biomass Ash Content Model Based on Near-Infrared
Spectroscopy and Complex Sample Set Partitioning[J]. SPECTROSCOPY AND SPECTRAL ANALYSIS, 2023, 43(10): 3143-3149. |
[8] |
ZHAO Ling-yi1, 2, YANG Xi3, WEI Yi4, YANG Rui-qin1, 2*, ZHAO Qian4, ZHANG Hong-wen4, CAI Wei-ping4. SERS Detection and Efficient Identification of Heroin and Its Metabolites Based on Au/SiO2 Composite Nanosphere Array[J]. SPECTROSCOPY AND SPECTRAL ANALYSIS, 2023, 43(10): 3150-3157. |
[9] |
SU Xin-yue1, MA Yan-li2, ZHAI Chen3, LI Yan-lei4, MA Qian-yun1, SUN Jian-feng1, WANG Wen-xiu1*. Research Progress of Surface Enhanced Raman Spectroscopy in Quality and Safety Detection of Liquid Food[J]. SPECTROSCOPY AND SPECTRAL ANALYSIS, 2023, 43(09): 2657-2666. |
[10] |
CHENG Fang-beibei1, 2, GAN Ting-ting1, 3*, ZHAO Nan-jing1, 4*, YIN Gao-fang1, WANG Ying1, 3, FAN Meng-xi4. Rapid Detection of Heavy Metal Lead in Water Based on Enrichment by Chlorella Pyrenoidosa Combined With X-Ray Fluorescence Spectroscopy[J]. SPECTROSCOPY AND SPECTRAL ANALYSIS, 2023, 43(08): 2500-2506. |
[11] |
LI Bin, SU Cheng-tao, YIN Hai, LIU Yan-de*. Hyperspectral Imaging Technology Combined With Machine Learning for Detection of Moldy Rice[J]. SPECTROSCOPY AND SPECTRAL ANALYSIS, 2023, 43(08): 2391-2396. |
[12] |
ZHAO Yu-wen1, ZHANG Ze-shuai1, ZHU Xiao-ying1, WANG Hai-xia1, 2*, LI Zheng1, 2, LU Hong-wei3, XI Meng3. Application Strategies of Surface-Enhanced Raman Spectroscopy in Simultaneous Detection of Multiple Pathogens[J]. SPECTROSCOPY AND SPECTRAL ANALYSIS, 2023, 43(07): 2012-2018. |
[13] |
ZHANG Jing, GUO Zhen, WANG Si-hua, YUE Ming-hui, ZHANG Shan-shan, PENG Hui-hui, YIN Xiang, DU Juan*, MA Cheng-ye*. Comparison of Methods for Water Content in Rice by Portable Near-Infrared and Visible Light Spectrometers[J]. SPECTROSCOPY AND SPECTRAL ANALYSIS, 2023, 43(07): 2059-2066. |
[14] |
CHENG Chang-hong1, XUE Chang-guo1*, XIA De-bin2, TENG Yan-hua1, XIE A-tian1. Preparation of Organic Semiconductor-Silver Nanoparticles Composite Substrate and Its Application in Surface Enhanced Raman Spectroscopy[J]. SPECTROSCOPY AND SPECTRAL ANALYSIS, 2023, 43(07): 2158-2165. |
[15] |
LI Chun-ying1, WANG Hong-yi1, LI Yong-chun1, LI Jing1, CHEN Gao-le2, FAN Yu-xia2*. Application Progress of Surface-Enhanced Raman Spectroscopy for
Detection Veterinary Drug Residues in Animal-Derived Food[J]. SPECTROSCOPY AND SPECTRAL ANALYSIS, 2023, 43(06): 1667-1675. |
|
|
|
|