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Design of Rapid Detection System for Urotropine in Food Based on SERS |
LI Wei1, FAN Xian-guang1,2*, WANG Xin1, TANG Ming1, QUE Jing1, HE Jian1, ZUO Yong3 |
1. School of Aerospace Engineering, Xiamen University, Xiamen 361005, China
2. University Key Laboratory of Sensing Technology of Fujian Province, Key Laboratory of Optoelectronic Sensor Technology of Xiamen, Xiamen 361005, China
3. Changcheng Institute of Metrology & Measurement, The 1st Metrology & Measurement Research Center of National Defense Science Industry of China, Beijing 100095, China |
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Abstract Based on surface enhanced Raman spectroscopy (SERS) technology, the detection system for rapid fild determination of urotropine in food is proposed. The detecting system consists of multifunctional pretreating module, Roman optical module and embedded master control module. It completed the pretreatment of sample, the generation, collection and transmission of the Raman spectral data. The multifunctional pretreating module integrate centrifuge, ultrasound and volatile functions all together, reducing the equipments used in the pretreatment experiment. Besides, it is portable and convenient for operation. The Roman optical module we designed embodies the probe of Raman spectrometer and monochromator, and the numerical aperture of the aspherical lens we used in the optical system of the probe was 0.6. Besides, the monochromator was designed based on Asymmetrical crossed Czerny-Turner structure. The hardware part of the embedded master control module is made up of ARM and FPGA, and its peripheral circuits. The software part of the module is made up of real time operation system μC/OS-Ⅲ, graphics library emWin, file system FatFs and various types of equipment components. Thus, accomplished the collection, transmission and calculation of the Raman spectral data from CCD. The liquid colloidal gold nanoparticle (LCP-1) was used in the detection experiments of urotropine, while the characteristic peaks at 1 047 cm-1 was chosen as the identity information of urotropine. The result of detection experiments shows that the system has the ability to identify the urotropine accurately, the detection limit of urotropine standards was 0.01 mg·L-1, with detection limit of urotropine in yuba and rice-noodle was 0.5 mg·L-1. Besides, the testing time was less than 20 minutes,which meets the requirements for rapid field determination of urotropine in food.
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Received: 2016-06-08
Accepted: 2016-11-05
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Corresponding Authors:
FAN Xian-guang
E-mail: fanxg@xmu.edu.cn
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[1] MA Xue-tao, NIU Zhi-rui, FENG Lei, et al(马雪涛, 牛之瑞, 冯 雷,等). Food Science(食品科学), 2014, 35(10): 166.
[2] ZHANG She-li, XU Wen-jing, FAN Yun-chang(张社利, 许文静, 范云场). Chinese Journal of Applied Chemistry(应用化学), 2014, 31(11): 1352.
[3] WU Ying, ZHANG Hui, CUI Fang, et al(吴 颖, 张 慧, 崔 芳,等). Science and Technology of Food Indystry(食品工业科技), 2014, 35(17): 298.
[4] JIA Bao-shen, HASI Wuliji, LIN Xiang et al(贾宝申, 哈斯乌力吉, 林 翔,等). The Journal of Light Scattering(光散射学报), 2015, 27(2): 128.
[5] Foodcontact materials—Polymer—Determination of Formaldehyde and Hexamethylen-Etetramine in Food Simulants—Spectrophotometry (食品接触材料—高分子材料—食品模拟物中甲醛和六亚甲基四胺的测定—分光光度法). National Standards of the People’s Republic of China(中华人民共和国国家标准), GB/T 23296.26—2009.
[6] Determination of Urotropine Residue in Foodstuffs of Animal Origin for Import and Export—LCMS/MS Method(进出口动物源性食品中乌洛托品残留量的检测方法液相色谱—质谱/质谱法). National Standards of the People’s Republic of China(中华人民共和国国家标准), SN/T 2226—2008.
[7] Schluecker, Sebastian. Angewandte Chemie-International Edition, 2014, 53(19): 4756.
[8] Cialla D, Marz A, Bohme R. Analytical and Bioanalytical Chemistry, 2012, 403(1): 27.
[9] NI Wei-quan, HE Jian, LIU Guo-kun, et al(倪伟全, 何 坚, 刘国坤, 等). Spectroscopy and Spectral Analysis(光谱学与光谱分析), 2015, 35(4): 1107.
[10] LIU Xu-xia, JI Yi-qun, HE Hu-cheng, et al(刘旭霞, 季轶群, 贺虎成, 等). Acta Optica Sinica(光学学报), 2013, 33(4): 0422009.
[11] AN Yan, SUN Qiang, LIU Ying, et al(安 岩, 孙 强, 刘 英,等). Chinese Optics(中国光学), 2012, 5(5): 470.
[12] Fan Xianguang, Tang Ming, Wang Xin. Applied Optics, 2015, 54(33): 9966.
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