表面增强拉曼光谱快速检测香蕉中的苯醚甲环唑和毒死蜱残留

目的 基于双重基底的表面增强拉曼光谱(surface-enhanced Raman spectroscopy, SERS)对香蕉中苯醚甲环唑与毒死蜱进行定性和定量检测。方法 采用银溶胶作为柔性衬底,增强芯片作为固体基底,实现双信号放大策略。选用香蕉这种常见的热带水果作为基质,向香蕉基质中加入不同浓度苯醚甲环唑和毒死蜱标准溶液,利用QuEChERS法对香蕉中农药残留进行提取,通过SERS技术对两种农药进行定量分析。结果 在0.10～5.00μg/mL范围内,苯醚甲环唑和毒死蜱的特征峰强度和浓度之间均满足线性关系,相关系数分别为0.9794、0.9773,方法检出限分别为0.16 mg/kg、0.032 mg/kg。结论 本研究建立了一种基于双重基底的SERS,为香蕉中苯醚甲环唑和毒死蜱农药残留快速检测提供了依据,也为热带水果中农药残留的快速检测提供了方法支持。     

脐橙果皮中三唑磷农药残留的表面增强拉曼光谱快速检测研究

采用表面增强拉曼光谱技术结合化学计量方法快速分析脐橙果皮中的三唑磷农药残留。利用乙腈快速提取脐橙果皮的提取液,采用石墨化碳、C18和PSA去除果皮提取液中色素等物质的干扰。以脐橙果皮提取液为基质,配制不同浓度的三唑磷农药溶液,进行拉曼信号采集,得到的拉曼特征峰与三唑磷标准溶液的特征峰基本一致。建立脐橙果皮中三唑磷农药残留的偏最小二乘法预测模型,结果表明,以脐橙果皮提取液为基质的三唑磷溶液最低检测浓度为0.8 mg/L;模型对预测集样本的预测均方根误差为1.60 mg/L,相关系数为0.9669。再利用该方法检测脐橙中实际所含三唑磷农药残留,其模型对样本的预测值与真实值的相对误差绝对值在0.08%~5.98%之间,预测回收率为94.36%~104.36%,模型预测能力和重现性良好。     

QuEchERS/GC-MS快速检测番茄中苯醚甲环唑残留

建立了番茄中苯醚甲环唑残留的快速检测方法。样品采用改进的Qu Ech ERS方法进行提取和净化,提取液使用GC-MS检测。结果表明,苯醚甲环唑在0.01μg/m L~0.20μg/m L范围内具有良好的线性关系,相关系数为0.999,样品中苯醚甲环唑添加水平为0.05 mg/kg、0.10 mg/kg、0.5 mg/kg时,平均回收率为87.6%、90.4%、98.0%,相对标准偏差在3.8%~8.1%之间。本方法操作简便、快速、高效,适用于番茄中苯醚甲环唑的快速筛查与检测。     

苯醚甲环唑农药残留检测技术的研究进展

苯醚甲环唑是一种具有高效、广谱、低毒和内吸传导性强的三唑类杀菌剂,对作物具有保护和治疗作用,广泛应用于水果和蔬菜等农作物上。简述苯醚甲环唑的毒性和最大残留限量,综述苯醚甲环唑农药残留的固相萃取、液相萃取、分散固相萃取等样品前处理技术,重点总结气相色谱法、液相色谱法、质谱法、拉曼光谱、免疫分析法等检测技术在苯醚甲环唑农药残留分析中的应用及特点,并对其发展方向进行展望,为今后苯醚甲环唑农药残留的分析研究提供参考。     

果蔬中苯醚甲环唑免疫分析方法的研究

针对目前由于三唑类杀菌剂苯醚甲环唑的广泛应用所带来的农药残留问题,建立了苯醚甲环唑的直接酶联免疫检测方法,其灵敏度IC_(50)为(67.96±2.73)μg/L,检测限IC_(15)为(8.86±0.34)μg/L,与11种三唑类杀菌剂的交叉反应率均小于0.01%。苯醚甲环唑在10种果蔬类样品中的平均回收率为89.01%~103.43%,变异系数小于14.33%,检出限为0.443 mg/kg。     

基于SERS技术的脐橙果肉中三唑磷农药残留快速检测研究

采用表面增强拉曼光谱(SERS)技术结合快速溶剂前处理方法建立脐橙果肉中三唑磷农药的快速检测方法。以脐橙果肉为空白对照,利用快速溶剂前处理方法对脐橙果肉进行提取,对不同浓度的以脐橙果肉提取液为基质的三唑磷溶液进行SERS检测。结果表明,以脐橙果肉提取液为基质的三唑磷溶液最低检测浓度为0.5mg/L;选择乙腈为内标物,以三唑磷1409cm-1特征峰与乙腈2257cm-1特征峰强度比值作为相对强度,其相对强度与三唑磷溶液浓度在0.5~20mg/L范围内具有良好的线性关系,相关系数(R2)为0.9919;预测误差在0.12mg/L以下,预测回收率为98.1%~102.5%,说明模型具有较好的预测效果,本文所建立的方法是准确可靠的。     

测定葡萄中苯醚甲环唑、己唑醇和咪鲜胺代谢物残留量方法研究

目的建立用于葡萄中苯醚甲环唑、己唑醇和咪鲜胺残留检测的分析方法。方法葡萄样品先经乙腈和水提取,盐析后取上清液进行水解并测定。通过优化前处理及色谱条件,建立色谱分析方法,结合目标物标准曲线进行定量分析。结果经过3个水平的加标回收实验,所建立方法的平均回收率在79%~102%,相对标准偏差0.5%~6.9%(n=5)。苯醚甲环唑和己唑醇的最低检出浓度为0.01 mg/kg,2,4,6-三氯苯酚的最低检出浓度为0.2 mg/kg。结论所建立的分析方法操作简便,分离净化效果良好,显著提高前处理效率,灵敏度、准确度和精密度均达到农药残留检测要求。     

苹果泥加工及储藏过程中6种农药残留变化

目的 明确苹果泥加工及储藏过程中多菌灵、噻虫嗪、吡虫啉、啶虫脒、咪鲜胺和苯醚甲环唑残留变化规律。方法 通过实验室模拟加工和加速储藏实验, 采用液相色谱-质谱法检测其中多菌灵、噻虫嗪、吡虫啉、啶虫脒、咪鲜胺和苯醚甲环唑的残留变化。结果 建立的检测方法中, 6种农药回收率范围为80.48%~114.58%, 相对标准偏差为2.08%~6.43%, 检出限为0.10~1.25 μg/kg, 定量限为0.50~5.00 μg/kg。苹果泥加工过程中清洗步骤农药残留浓度降低12.93%~38.87%, 预煮步骤农药残留浓度降低24.61%~58.16%, 而巴氏杀菌步骤农药残留浓度略有增加(P>0.05)。加速储藏过程中6种农药残留浓度均降低, 其中咪鲜胺在加速储藏14 d后未检出。苹果泥加工全程及储藏过程中6种农药的加工因子均小于1。结论 研究结果可为苹果泥中农药最大残留限量制定及消费者安全膳食引导提供参考, 获得的加工因子可用于食品安全风险评估, 提升风险评估结果的准确性。     

高效液相色谱串联质谱法测定蔬菜中苯醚甲环唑的残留量

建立高效液相色谱-串联质谱检测蔬菜中苯醚甲环唑残留的分析方法。样品采用乙腈提取,经石墨碳黑-氨基串联固相萃取(GCB/NH2 SPE)柱净化,液相色谱分离多反应监测模式下测定,外标法定量。结果显示：苯醚甲环唑质量浓度在1～500ng/mL范围内线性关系良好。苯醚甲环唑在不同基质中平均回收率为79.3%～108.0%,相对标准偏差为2.7%～8.5%,检出限为0.001mg/kg。该方法灵敏度高,准确度、精密度好,满足样品测定的定性、定量要求。     

苯醚甲环唑和吡唑醚菌酯在西瓜中的残留分析及膳食风险评价

目的评价苯醚甲环唑和吡唑醚菌酯在西瓜中的长期慢性和短期急性膳食摄入风险。方法于2018年进行1年10地规范残留试验,建立检测西瓜中苯醚甲环唑和吡唑醚菌酯残留的分析方法。样品经乙腈提取,加NaCl盐析,经无水MgSO4除水和PSA净化,用超高效液相色谱串联质谱法(ultra performance liquid chromatography tandem mass spectrometry, UPLC-MS/MS)分析,采用多反应离子监测模式(MRM)检测,正离子(ESI+)化,基质匹配外标法定量。结果目标物在一定质量浓度范围内具有良好的线性关系(r≥0.9991)。西瓜在0.01、0.05、0.5 mg/kg添加水平下,苯醚甲环唑平均回收率为92%~103%,相对标准偏差为0.9%~8.9%之间;吡唑醚菌酯的平均回收率为92%~95%, RSDs为1.7%~10.3%,定量限为0.01 mg/kg。膳食评估的结果:一般人群苯醚甲环唑的国家估算每日摄入量(the national estimated daily intake, NEID)为8.57μg/kg·bw/d,占日允许摄入量的85.7%;一般人群吡唑醚菌酯的NEID为18.72μg/kg·bw/d,占日允许摄入量的62.4%。短期急性膳食风险评苯醚甲环唑短期膳食摄入量(the national estimated short-term daily intake, NESTI)为2.98~4.26μg/kg·bw/d,占急性参考剂量(the acute reference dose, ARfD)的0.99%~1.42%,吡唑醚菌酯NESTI为6.23~8.90μg/kg·bw/d,占ARfD的12.46%~17.8%。我国规定的水果中苯醚甲环唑和吡唑醚菌酯最高MRL分别为2 mg/kg和4 mg/kg,该值对我国各类人群在水果中苯醚甲环唑暴露保护水平为1.44~11.24倍;吡唑醚菌酯暴露保护水平为2.16~16.86倍。结论苯醚甲环唑和吡唑醚菌酯长期慢性和短期急性膳食摄入风险较低,现有水果MRL对各类人群的暴露量在可接受的范围之内。     

叶菜中多类农药残留的SERS快速无损检测

有机磷、有机硫和烟碱类农药常应用于叶菜的种植和生产中,常规的检测方法前处理复杂、检测时间长、成本高等特点,难以满足快速检测的需求,为了实现农药残留的在线检测,本文提出一个基于SERS技术进行定量和定性分析叶菜中农药残留的检测方法,选取农药的特征拉曼峰作为校正峰,制定农药残留的浓度与校正峰强度的线性校准方程,将最低检测限对应SERS光谱的校正峰的强度代入线性校准方程,计算出定量检测限。研究表明,小白菜中亚胺硫磷农药的检测限能达到0.5mg/kg以下,相关系数R~2为0.95273,标准偏差为2.89%～13.63%,回收率为96.00%～121.33%;大白菜中福美双农药残留的检测限能达到0.5mg/kg以下,相关系数R~2为0.8905,标准偏差为3.90%～8.39%,回收率为88.80%～112.44%;空心菜中啶虫脒农药残留的检测限能达到1mg/kg以下,相关系数R~2为0.93858,标准偏差为2.12%～9.29%,回收率为87.67%～107.17%。这些结果说明,基于SERS技术进行定量和定性分析叶菜中农药残留的检测方法是一种有效的方法,可以实现叶菜农药残留的快速无损检测。     

基于表面增强拉曼光谱技术的苹果汁中溴氰菊酯农药残留的快速定量分析

针对苹果汁中农药残留量超标问题,采用共焦显微拉曼仪,研究了针对苹果汁中溴氰菊酯农残量的快速检测方法。分别以乙醇溶液(对照)、苹果汁溶液为背景溶液,分别采用拉曼光谱技术、表面增强拉曼光谱技术(SurfaceEnhanced Raman Scattering,SERS)采集含农药(溴氰菊酯)的两种样本的拉曼光谱与SERS光谱,并结合一阶导加Norris求导法进行光谱预处理,进而使用偏最小二乘方法建立两种样本溶液中溴氰菊酯残留量的拉曼光谱定量分析模型与SERS光谱定量分析模型,并对两种模型进行对比分析。结果表明,乙醇中溴氰菊酯溶液样本的拉曼光谱定量分析模型的校正集相关系数可达到0.9634,而SERS模型校正集相关系数可达到0.9995,最大误差不超过0.1 mg/kg。苹果汁中溴氰菊酯样本的拉曼光谱模型校正集相关系数为0.9355,最大误差不超过0.02 mg/kg;而SERS模型校正集相关系数为0.9870,最大误差不超过0.1 mg/kg。结果表明,拉曼光谱技术对快速检测苹果汁中的农药残留量具有可行性。     

基于表面增强拉曼光谱快速检测苹果汁中亚胺硫磷

利用种子生长法合成出不同大小(35～91nm,金核19nm;66～127nm,金核43nm)的金核银壳纳米粒子(Au-Ag NPs),对其形貌和光学特性进行表征,并将其作为表面增强拉曼散射(SERS)基底,探究不同粒径和金银比例对亚胺硫磷检测的影响。试验结果显示:42nm Au-Ag NPs(金核19nm)和78nm Au-Ag NPs(金核43nm)对亚胺硫磷标准溶液具有最佳的SERS增强效果,最低检出浓度可低至0.05mg/L。但Au-Ag NPs基底应用于苹果汁中亚胺硫磷的SERS快速检测效果存在较大差异,以42,78nm Au-Ag NPs作为增强基底时,苹果汁中的亚胺硫磷最低检出浓度分别为5.0,0.5 mg/L。研究表明通过筛选出合适的粒径及金银比例的Au-Ag NPs有望实现对果汁中亚胺硫磷的现场快速检测。     

基于D152树脂吸附蛋白质结合SERS测定鱼肉中的鸟嘌呤含量

基于大孔树脂除杂与表面增强拉曼光谱的灵敏实时性,建立一种鱼肉中鸟嘌呤含量的快速检测方法。以D152树脂为填料,柱内直径1 cm,柱高20 cm,蛋白吸附率在83%～92%之间,鸟嘌呤滤除率大于95%。经单因素试验筛选和正交试验优化得出,上样流速为3 mL/min,洗脱液pH值为4.0以及洗脱流速为0.5 mL/min。基于银包金纳米颗粒（silver-coated gold nanoparticles,Au@Ag NPs）为表面增强基底,鸟嘌呤质量浓度在0.001～100 mg/L范围,鸟嘌呤质量浓度与拉曼强度呈线性关系,R2为0.969 9,检出限为0.1 mg/L。整个检测过程只需10 min,且无需复杂的样品处理。结果表明,D152树脂作为填料的层析柱能有效去除鱼肉中蛋白质等杂质的干扰,以Au@Ag NPs为基底的表面增强拉曼光谱技术的方法能够灵敏、快速的检测鱼肉中痕量嘌呤,检出限低于现有的高效液相色谱法,为开发设计水产品中嘌呤的快速检测方法提供研究基础。     

Standing Gold Nanorod Arrays as Reproducible SERS Substrates for Measurement of Pesticides in Apple Juice and Vegetables

There is an increasing interest in recent years in using novel nanomaterials as cost‐effective, sensitive, and reproducible substrate for surface‐enhanced Raman spectroscopy (SERS) applications. In this study, a novel SERS substrate was developed by assembling gold nanorods into standing arrays on a gold‐coated silicon slide. The standing nanorod arrays were closely packed on the gold film, generating strong electromagnetic field and uniformly distributed SERS “hot‐spots” on the array surface. The as‐prepared SERS substrates were used to detect a widely used pesticide (that is, carbaryl) in acetonitrile–water solution, apple juice, and cabbage. Results demonstrate that the actual concentrations of carbaryl in apple juice and cabbage were linearly correlated with the concentrations predicted by the multiple linear regression models (R > 0.97). The detection limits of carbaryl in apple juice and cabbage were both 2.5 ppm, meeting the maximum residue limits set by US Environmental Protection Agency (EPA). SERS can detect as low as 0.1 ppm of carbaryl in acetonitrile–water solution. In addition, satisfactory recoveries were obtained for carbaryl in both apple juice and cabbage. These results indicate that SERS coupled with the standing gold nanorod array substrates is a sensitive and reproducible method and can accurately detect pesticides in foods.     

Rapid Detection of Acetamiprid in Foods using Surface‐Enhanced Raman Spectroscopy (SERS)

Acetamiprid is a neonicotinoid pesticide that is commonly used in modern farming. Acetamiprid residue in food commodities can be a potential harm to human and has been implicated in the honey bee hive die off crisis. In this study, we developed rapid, simple, and sensitive methods to detect acetamiprid in apple juice and on apple surfaces using surface‐enhanced Raman spectroscopy (SERS). No pretreatment of apple juice sample was performed. A simple surface swab method was used to recover acetamiprid from the apple surface. Samples were incubated with silver dendrites for several minutes and SERS spectra were taken directly from the silver surface. Detection of a set of 5 apple juice samples can be done within 10 min. The swab‐SERS method took 15 min for a set of 5 samples. Resulting spectral data were analyzed using principal component analysis. The highest acetamiprid peak at 634 cm^?1 was used to detect and quantify the amount of acetamiprid spiked in 1:1 water–methanol solvent, apple juice, and on apple surface. The SERS method was able to successfully detect acetamiprid at 0.5 μg/mL (0.5 ppm) in solvent, 3 μg/mL (3 ppm) in apple juice, and 0.125 μg/cm² on apple surfaces. The SERS methods provide simple, rapid, and sensitive ways to detect acetamiprid in beverages and on the surfaces of thick skinned fruits and vegetables.     

Rapid extraction and detection of trace Chlorpyrifos-methyl in orange juice by surface-enhanced Raman spectroscopy

It is estimated that 20–50% of crops are saved from infestation through the use of pesticides. However, US inspectors find that more than 4% of fruits and vegetables imported exceed concentration levels considered safe for human consumption. This represents millions of tons of food brought to market annually that cannot be inspected using current hour-long laboratory methods. In an effort to provide inspectors with a simple, fast, field-usable analyzer and method, we have been developing a sampling device that includes surface-enhanced Raman spectroscopy (SERS) to detect, identify, and quantify pesticides below part-per-million (μg/mL) concentrations in approximately 10 min using a portable Raman analyzer. The entire method, including solvent extraction, solid-phase extraction, and SERS-detection, was used to detect 50 parts-per-billion (ppb) Chlorpyrifos-methyl (CPM) artificially added to orange juice in 12 min. The same method and analyzer can be readily adapted to other pesticides and foods.     

海拔对四种叶类蔬菜中吡虫啉和啶虫脒的残留及消解动态的影响

为探讨高、低海拔对吡虫啉和啶虫脒在四种叶类设施蔬菜中的残留和消解规律的影响。本文在西藏拉萨市和四川彭州市开展相关消解动态试验和最终残留试验,采用超高效液相色谱-串联质谱（UPLC-MS/MS）开展大白菜、快白菜、生菜、西芹中吡虫啉和啶虫脒残留的测定。结果表明,吡虫啉和啶虫脒在0.005~0.500 mg/L范围内线性良好。在0.01、0.10和0.50 mg/kg添加水平下,两种杀虫剂在四种叶类蔬菜中的平均回收率为81.22%～116.95%,相对标准偏差（RSD）为1.2%～7.1%,检出限（LOD,S/N≥3）为0.11~1.21 μg/kg,定量限（LOQ,S/N≥10）为0.38~0.69 μg/kg。田间试验结果表明,吡虫啉和啶虫脒在4种叶类蔬菜中的消解动态均符合一级反应动力学方程,施药7 d后至收获期,其最终残留量均未超出食品安全国家标准中规定的最大残留限量值。吡虫啉和啶虫脒在拉萨市4种叶类蔬菜中的半衰期均短于彭州市4种叶类蔬菜中的半衰期,但两种农药半衰期的长短在不同海拔地区的4种叶类蔬菜中无显著差异,即在拉萨市和彭州市中吡虫啉和啶虫脒的半衰期由短到长均为生菜<快白菜<大白菜<西芹,两种农药的残留及消解动态与蔬菜品种及不同海拔的种植环境有密切关联。     

基于食品安全指数法和危害物风险系数法评估海南芹菜的农药残留风险

目的 调查海南省市售芹菜的农药残留情况,评估其农药残留风险。方法 从市场上采集115份芹菜样品,采用超高效液相色谱-四极杆串联飞行时间质谱法和气相色谱-三重四极杆串联质谱法对359种农药残留进行筛查,并采用食品安全指数法和危害物风险系数法对检出的农药残留进行风险评估。结果 在所有筛查的样品中有83份检出农药残留,检出率为72.2%,超标率为3.5%。检出农药39种,其中以杀菌剂和杀虫剂为主,检出率最高的杀虫剂为灭蝇胺,杀菌剂为苯醚甲环唑。所有检出的农药残留的安全指数值均小于1,安全影响较小;除毒死蜱、甲拌磷、敌敌畏这3种农药呈高中风险外,其他农药残留风险系数均小于1.5,为低度风险。结论 海南地区市售芹菜中普遍存在农药残留污染,但总体风险较低,不会对一般人群健康造成不可接受的风险,本研究可为海南地区芹菜的食品安全监管提供科学依据。     

Establishment of rapid detection method of methamidophos in vegetables by surface enhanced Raman spectroscopy

Methamidophos (MAP) is a highly efficient and broad-spectrum organophosphate pesticide. In this study, a rapid method for detecting MAP in vegetables using surface enhanced Raman scattering (SERS) spectroscopy has been established. Density functional theory calculations were performed with Gaussian 03 at RB3LYP level and with the 6-311G (d) basis set. SERS, normal and theoretical Raman spectroscopy were compared to investigate the mechanism of Raman scattering enhancement. The SERS signal of MAP was improved in alkaline conditions with optimum scattering efficiency at pH of 13.46. Furthermore, MAP detection in vegetables by SERS method had a good linear relationship between 0.01 and 1,000?μg/mL. The concentration of MAP in vegetables was detected and chosen for recovery test with three levels: 4, 8, and 15?μg/mL. The results of three level tests were 86.7–96.6?% and their relative standard deviations were between 1.2 and 2.5?%, which shows the good repeatability of this method.