|
|
|
|
|
|
Papid Detection of Zilpaterol Residues in Pork by Surface-Enhanced
Raman Spectroscopy |
DONG Xiang-hui, YANG Fang-wei, YU Hang, YAO Wei-rong, XIE Yun-fei* |
School of Food Science and Technology, Jiangnan University,Wuxi 214000, China
|
|
|
Abstract Zilpaterol is a β2-receptor agonist, also known as “Clenbuterol”, often used in livestock breeding by illegal businesses. There is no relevant national standard that stipulates its residue limit. After the veterinary drug enters the animal’s body, it can change the metabolic mode of certain nutrients, promote the growth of the animal’s muscle, and rapidly consume and transform the fat in the animal’s body, thereby increasing the lean meat rate of the animal. The current detection method for the drug is mainly liquid chromatography-tandem mass spectrometry, which has the disadvantages of high cost, cumbersome operation, and long time-consuming. Surface-enhanced Raman spectroscopy has the advantages of high sensitivity and fast detection speed. In recent years, it has beenwidely used to detect toxic and harmful substances in food. In order to realize the rapid detection of zilpaterol in pork, a surface-enhanced Raman spectroscopy method for rapid detection of zilpaterol residue in pork was established. By optimising and comparing a series of experimental results, it is determined that the best volume ratio of sample to gold glue is 1∶2, and the best mixing detection time is 3 min.Through the comparison of multiple extraction solvents, it is finally determined that ethyl acetate is used as the extractant;through the calculation of the theoretical spectrum of B3LYP/6-311 + G(d) basis group aligned patro in density functional theory, the SERS characteristic peak of zipatro is determined and the vibration is assigned. The characteristic peaks at 1 116, 1 447 and 1 573 cm-1 are taken as the characteristic quantitative peaks of zilpaterol, of which 1 116 cm-1 is caused by the in-plane deformation vibration of a benzene ring, and 1 447 cm-1 is the out of plane swing vibration of C—H bond, 1 573 cm-1 is the stretching vibration of C—H bond of the benzene ring. Under the best experimental conditions, a standard curve of the characteristic peak SERS signal and concentration logarithm of zilpaterol standard solution was established, and the R2 value of the linear equation was all above 0.9; actual samples with different spiked concentrations were performed. The detection showed that the average recovery rate was 80.39%~101.24%, and the RSD value was 7.90%~8.94%. This method is convenient, fast, and stable. It can realize the rapid and accurate determination of zilpaterol residues in pork without complicated sample pretreatment. It provides a new method for detecting zilpaterol and the formulation of related standards.
|
Received: 2021-07-26
Accepted: 2021-10-17
|
|
Corresponding Authors:
XIE Yun-fei
E-mail: xieyunfei@jiangnan.edu.cn
|
|
[1] LI Zhi-cheng, ZHENG Xiao-dong, LIU Xue-mei, et al(李志成, 郑晓冬, 刘雪梅,等). Modern Food Science and Technology(现代食品科技),2021, 37(7): 321.
[2] ZHANG Hai-yan(张海燕). Master Dissertation(硕士论文). Jinan University(暨南大学),2016.
[3] Yikilmaz Y, Kuzukiran O, Erdogan E, et al. Biomedical Chromatography,2020,34(10): e4926.
[4] DONG Li-xue, GE Huai-li, ZHENG Bai-qin, et al(董李学,葛怀礼,郑百芹,等). China Animal Husbandry & Veterinary Medicine(中国畜牧兽医),2013, 40(3): 242.
[5] ZHAO Jin-hui, YUAN Hai-chao, HU Qi, et al(赵进辉,袁海超,胡 琪,等). Modern Food Science and Technology(现代食品科技),2017, 33(2): 239.
[6] Cheng J, Wang S, Zhang S, et al. Sensors and Actuators B: Chemical,2019, 279: 7.
[7] Peng Y J, Liu M H, Zhao J H, et al. Journal of Spectroscopy, 2017, 50(10): 579.
[8] Tamitake I,Ken-ichi Y, Hiroharu T, et al. Journal of Photochemistry and Photobiology, A: Chemistry, 2011, 219(2-3): 167.
[9] Cheng J, Fan M D, Wang P L, et al. Food Analytical Methods, 2020, 13(4): 902.
[10] Gao Ting, Ye Nengsheng, Li Jian. Analytical Letters, 2016, 49(8): 1163.
[11] Fowler Stephanie M, Ponnampalam Eric N, Schmidt Heinar, et al. Meat Science, 2015, 110: 70.
|
[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] |
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. |
[3] |
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. |
[4] |
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. |
[5] |
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. |
[6] |
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. |
[7] |
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. |
[8] |
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. |
[9] |
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. |
[10] |
LAI Chun-hong*, ZHANG Zhi-jun, WEN Jing, ZENG Cheng, ZHANG Qi. Research Progress in Long-Range Detection of Surface-Enhanced Raman Scattering Signals[J]. SPECTROSCOPY AND SPECTRAL ANALYSIS, 2023, 43(08): 2325-2332. |
[11] |
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. |
[12] |
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. |
[13] |
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. |
[14] |
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. |
[15] |
LI Jia-jia, XU Da-peng *, WANG Zi-xiong, ZHANG Tong. Research Progress on Enhancement Mechanism of Surface-Enhanced Raman Scattering of Nanomaterials[J]. SPECTROSCOPY AND SPECTRAL ANALYSIS, 2023, 43(05): 1340-1350. |
|
|
|
|