基于表面增强拉曼光谱的养殖水中五氯酚残留检测
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(1. 上海市食品药品检验所,上海 201203;2. 赛默飞世尔科技〔中国〕有限公司,上海 201206)

作者简介:

张泸文,女,上海市食品药品检验所主管药师,硕士。

通讯作者:

王柯(1971—),男,上海市食品药品检验所主任药师,硕士。E-mail: wangke@smda.sh.cn

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基金项目:

上海市科委研究计划项目(编号:16391904000,18395810300)


Detection of pentachlorophenol in fishery water using surface-enhanced Raman spectroscopy
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Affiliation:

(1. Shanghai Institute for Food and Drug Control, Shanghai 201203, China;2. Thermo Fisher Scientific 〔China〕 Co., Ltd., Shanghai 201206, China)

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    摘要:

    应用表面增强拉曼光谱(SERS)技术,建立了一种水产品流通过程养殖水中五氯酚残留量的快速测定方法。参照经典方法制备金溶胶后将其浓缩作为增强基底,通过优化促凝剂、调节体系pH值、选择纳米溶剂及其用量、考察吸附等待时间得到最佳SERS增强效果。所建立的方法在0.2~4.0 μg/mL的浓度范围内具有良好的线性相关性,养殖水中五氯酚的检出限为0.5 μg/mL,回收率为78.74%~112.30%,精密度为6.1%~11.3%,满足残留分析的要求。定性方法灵敏度、特异性≥95%、假阴性率和假阳性率≤5%,结果均符合食药监科便函[2017]43号《食品快速检测方法评价技术规范》要求。该方法快速准确、操作简便,适用于现场快速检测养殖水中五氯酚残留量。

    Abstract:

    A method for rapid determination of pentachlorophenol in fishery water was established by surface-enhanced Raman spectroscopy (SERS). The concentrated gold colloid was prepared to use as Raman substrate according to the classic method, and the optimal SERS enhancement effects were obtained by adjusting the pH of the system, optimizing the coagulants, nanoparticles volume and adsorption time. The method had a good linearity between the peak intensity and the pentachlorophenol concentration in the range of 0.2~4.0 μg/mL, and the detection limit was 0.5 μg/mL. The recovery ranged from 78.74% to 112.30%, and the relative standard deviation was between 6.1%~11.3%. The sensitivity and specificity of the SERS method were over 95%, and the rates of false positive and false negative results were less than 5%, which were all conform to the evaluation specification of food rapid analysis method. The method is fast, accurate and easy to operate, and it provides a good foundation for the rapid detection of pentachlorophenol in fishery water.

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引用本文

张泸文,余婉松,夏苏捷,等.基于表面增强拉曼光谱的养殖水中五氯酚残留检测[J].食品与机械,2019,35(12):82-86.
ZHANG Lu wen, YU Wan song, XIA Su jie, et al. Detection of pentachlorophenol in fishery water using surface-enhanced Raman spectroscopy[J]. Food & Machinery,2019,35(12):82-86.

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  • 收稿日期:2019-08-11
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  • 在线发布日期: 2022-10-05
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