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| Raman Spectroscopy Analysis of Forchlorfenuron Based on Two-Dimensional Correlation Technique |
| LU Dan1, ZHAO Wu-qi1*, GAO Gui-tian1,2, MENG Yong-hong1, ZENG Xiang-yuan1, WU Ni1, LEI Yu-shan2 |
1. School of Food Engineering and Nutritional Science, Shaanxi Normal University, Xi’an 710119, China
2. Engineering Research Center of Actinidia in Shaanxi Province, Xi’an 710404, China |
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Abstract As a kind of Benzourea, Forchlorfenuronis widely used to regulate the growth of fruits and vegetables. However, excessive use of Forchlorfenuron extremely hinders the growth of agricultural products. The residual Forchlorfenuron taken by humans also leads to damage of health. Various technologies were limited to fulfil both high accuracy and low cost in detecting Forchlorfenuron, so simple and time-saving technologies need to be developed. In this paper, highly sensitive and efficient Raman spectroscopy based on two-dimensional correlation technique were applied to detect the concentration change of Forchlorfenuron in ethyl acetate solution. The development of this technology provided theoretical basis of relevant analysis method for detecting Forchlorfenuron, which has a great influence on food safety. Raman spectrogram of Forchlorfenuron powders and its formula were used to analyze the Raman peaks. Different concentration of 2.5, 5.0, 7.5, 10.0, 12.5, 15.0, 17.5, 20.0 g·L-1 Forchlorfenuron in ethyl acetate solution were also tested to analyze the relationship of Raman peaks with the concentration change by using the synchronous and asynchronous spectroscopy of Forchlorfenuron. The result of synchronous showed that a synergetic effect of the peaks occurred at 842, 992, 1 044, 1 442, 1 604 cm-1 and the intensity of peaks increased with the rise of Forchlorfenuron concentration. Meanwhile, The results of asynchronous spectroscopy showed that the sensitivity of peaks had the following relationship: 1 044 cm-1>992 cm-1>842 cm-1, 1 735 cm-1>1 604 cm-1>1 442 cm-1, 842 cm-1>1 735 cm-1. Raman characteristic absorption peaks of Forchlorfenuron in ethyl acetatesolution were determined to be 842, 992, 1 044, 1 442, 1 604 and 1 735 cm-1, respectively, among which the peaks at 1 044 cm-1 (stretching vibration of benzene), 992 cm-1 (breathing vibration of pyridine), 842 (C—N—O asymmetrical stretching vibration) and 1 735 cm-1 (C=O stretching vibration)were more sensitive to the concentration of Forchlorfenuron and the sensitive order were stretching vibration of benzene, breathing vibration of pyridine, C—N—O asymmetrical stretching vibration, C=O stretching vibration, C=C stretching vibration of various coupling peaks and C—H deformation vibration. Such a combination of Raman spectroscopy based on two-dimensional correlation technique could exactly analyze the concentration change of Forchlorfenuron in ethyl acetatesolution, which will provide a new idea and method for the detection of Forchlorfenuroncontent in fruits and vegetables.
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Received: 2018-03-30
Accepted: 2018-07-28
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Corresponding Authors:
ZHAO Wu-qi
E-mail: zwq65@163.com
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[1] QI Ming-fang(齐明芳). Jiangsu Agricultural Sciences(江苏农业科学), 2011, 39(6): 486.
[2] SUN Da-li, ZHENG Zun-tao, YE Huo-chun, et al(孙大利, 郑尊涛, 叶火春, 等). Agrochemicals(农药), 2011, 50(10): 751.
[3] NIE Lei, LIU Hong-xian(聂 磊, 刘鸿先). Ecologic Science(生态科学), 2001, (3): 44.
[4] WANG Tian-xiao(王天晓). Changchun University of Science and Technology(长春理工大学), 2014.
[5] Noda I, Ozaki Y. Hoboken: 1st ed. Johns Wiley & Sons, 2004.
[6] Noda I. Vib. Spectrosc. 2004, 36(2): 143.
[7] Yang Renjie, Liu Rong, Xu Kexin, et al. Anal. Methods, 2013, 5: 5949.
[8] ZHAO Li-jun, GAO Lei, YI Ling-xue, et al(赵丽君, 高 磊, 衣玲学，等). Spectroscopy and Spectral Analysis(光谱学与光谱分析), 2017, 37(1): 109.
[9] Yang Renjie, Liu Rong, Dong Guimei, et al. Spectrochimica Acta Part A: Molecular and Biomolecular Spectroscopy, 2016, 157：50. |
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