胡均鹏,陈荣桥,梁 明,刘艳锋,冼燕萍,侯向昶,王 莉,吴玉銮.基于Au@Ag纳米粒子的表面增强拉曼光谱技术测定苹果和梨中的福美双[J].食品安全质量检测学报,2022,13(2):366-372
基于Au@Ag纳米粒子的表面增强拉曼光谱技术测定苹果和梨中的福美双
Determination of thiram in apples and pears by surface enhanced Raman spectroscopy based on Au@Ag nanoparticles
投稿时间:2021-09-09  修订日期:2022-01-07
DOI:
中文关键词:  Au@Ag纳米粒子  表面增强拉曼光谱  苹果    福美双
英文关键词:Au@Ag nanoparticles  surface enhanced Raman spectroscopy  apples  pears  thiram
基金项目:国家重点研发计划专项(2019YFC1606400)
作者单位
胡均鹏 广州质量监督检测研究院, 广州市食品安全风险动态监测与预警研究中心, 广州市食品安全检测技术重点实验室 
陈荣桥 广州质量监督检测研究院, 广州市食品安全风险动态监测与预警研究中心, 广州市食品安全检测技术重点实验室 
梁 明 广州质量监督检测研究院, 广州市食品安全风险动态监测与预警研究中心, 广州市食品安全检测技术重点实验室 
刘艳锋 广州质量监督检测研究院, 广州市食品安全风险动态监测与预警研究中心, 广州市食品安全检测技术重点实验室 
冼燕萍 广州质量监督检测研究院, 广州市食品安全风险动态监测与预警研究中心, 广州市食品安全检测技术重点实验室 
侯向昶 广州质量监督检测研究院, 广州市食品安全风险动态监测与预警研究中心, 广州市食品安全检测技术重点实验室 
王 莉 广州质量监督检测研究院, 广州市食品安全风险动态监测与预警研究中心, 广州市食品安全检测技术重点实验室 
吴玉銮 广州质量监督检测研究院, 广州市食品安全风险动态监测与预警研究中心, 广州市食品安全检测技术重点实验室 
AuthorInstitution
HU Jun-Peng Guangzhou Quality Supervision and Testing Institute, Guangzhou City Research Center of Risk Dynamic Detection and Early Warning for Food Safety, Guangzhou City Key Laboratory of Detection Technology for Food Safety 
CHEN Rong-Qiao Guangzhou Quality Supervision and Testing Institute, Guangzhou City Research Center of Risk Dynamic Detection and Early Warning for Food Safety, Guangzhou City Key Laboratory of Detection Technology for Food Safety 
LIANG Ming Guangzhou Quality Supervision and Testing Institute, Guangzhou City Research Center of Risk Dynamic Detection and Early Warning for Food Safety, Guangzhou City Key Laboratory of Detection Technology for Food Safety 
LIU Yan-Feng Guangzhou Quality Supervision and Testing Institute, Guangzhou City Research Center of Risk Dynamic Detection and Early Warning for Food Safety, Guangzhou City Key Laboratory of Detection Technology for Food Safety 
XIAN Yan-Ping Guangzhou Quality Supervision and Testing Institute, Guangzhou City Research Center of Risk Dynamic Detection and Early Warning for Food Safety, Guangzhou City Key Laboratory of Detection Technology for Food Safety 
HOU Xiang-Chang Guangzhou Quality Supervision and Testing Institute, Guangzhou City Research Center of Risk Dynamic Detection and Early Warning for Food Safety, Guangzhou City Key Laboratory of Detection Technology for Food Safety 
WANG Li Guangzhou Quality Supervision and Testing Institute, Guangzhou City Research Center of Risk Dynamic Detection and Early Warning for Food Safety, Guangzhou City Key Laboratory of Detection Technology for Food Safety 
WU Yu-Luan Guangzhou Quality Supervision and Testing Institute, Guangzhou City Research Center of Risk Dynamic Detection and Early Warning for Food Safety, Guangzhou City Key Laboratory of Detection Technology for Food Safety 
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中文摘要:
      目的 建立基于Au@Ag纳米粒子(Au@Ag nanoparticles, Au@AgNPs)的表面增强拉曼光谱(surface enhanced Raman spectroscopy, SERS)测定苹果和梨中的福美双的方法。方法 采用快速、简便、廉价、有效、坚固、安全(QuEChERS)样品制备方法提取苹果和梨中的福美双, 提取液直接与Au@AgNPs结合后进行SERS测试。DXRxi-Raman激光拉曼光谱仪条件: 激发波长532 nm±0.5 nm, 光谱覆盖范围300~1700 cm-1, 光谱分辨率为2~5 cm-1, 最后采用超高效液相色谱-串联质谱法(ultra performance liquid chromatography-tandem mass spectrometry, UPLC-MS/MS)进行验证。结果 拉曼位移为1379 cm-1处的特征峰可以作为福美双残留检测的拉曼特征峰, 待测样品和Au@AgNPs加入量分别为20 μL和10 μL, 吸附时间为5 min时, 苹果中福美双的检出限能达到0.1 mg/kg, 相关系数为0.9942, 相对标准偏差为5.21%~6.11%, 回收率为90.0%~98.0%; 梨当中福美双的检出限能达到0.1 mg/kg, 相关系数为0.9924, 相对标准偏差为4.21%~5.11%, 回收率为92.0%~98.4%。与UPLC-MS/MS的对比结果具有较好的一致性。结论 该方法具有操作简单、快速、准确等优点, 可适用于苹果和梨中福美双的检测分析。
英文摘要:
      Objective To establish a method for the rapid detection of thiram in apples and pears by surface enhanced Raman spectroscopy (SERS) method based Au@Ag nanoparticles (Au@AgNPs). Methods The quick easy cheap effective rugged and safe (QuEChERS) sample preparation method was used to extract thiram in apples and pears, and the extract solution was directly combined with Au@AgNPs for SERS test. DXRxi-Raman laser Raman spectrometer test conditions as follows: The excitation wavelength of the experiment was 532 nm±0.5 nm, the spectral coverage was 300?1700 cm-1, and the spectral resolution was 2-5 cm-1, and ultra performance liquid chromatography-tandem mass spectrometry (UPLC-MS/MS) was used for verification finally. Results The characteristic peak at the Raman shift of 1379 cm-1 can be used as the Raman peak for the detection of thiram residues. The amount of the sample to be tested and Au@AgNPs were 20 μL and 10 μL, respectively, and the adsorption time was 5 min. The limit of detection for thiram in apples was 0.1 mg/kg, the r2 and the relative standard deviations were 0.9942, 5.21%?6.11%, respectively, the recoveries were 90.0%-98.0%; the limit of detection for thiram in pears was 0.1 mg/kg, the r2 and the relative standard deviations were 0.9924, 4.21%?5.11%, respectively, the recoveries were 92.0%?98.4%. These results were in good agreement with the UPLC-MS/MS. Conclusion This method is simple, rapid and accurate, and can be applied to the detection and analysis of thiram in apples and pears.
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