摘要
[目的/意义]为满足目前市场上对农产品农药残留的快速灵敏检测需求,报道一种基于柠檬汁还原制备银纳米粒子(AgNPs)的方法。[方法]首先将新鲜柠檬汁经滤纸过滤,稀释成2%的柠檬汁水溶液,再配制一定浓度的AgNO3溶液、50 mM的NaOH溶液,放置室温保存。然后在室温下,将10 mL的ddH2O、2mL的NaOH、2mL的2%柠檬汁和5 mL的AgNO3溶液混合,待溶液颜色变为澄清的黄色时,溶液离心即可获得AgNPs。[结果和讨论]该方法制备的AgNPs,其颗粒形貌大小基本均一,约为20 nm,具有很好的表面增强拉曼散射(Surface Enhancement of Raman Scattering,SERS)增强效应,即良好的SERS信号稳定性,较强的SERS增强性能。该胶体中AgNPs分散较均匀,并且具有较长时间储存的稳定性,因此可用于微量农残检测。柠檬汁中主要还原成分抗坏血酸、葡萄糖和果糖,其含量分别为395.76μg/mL、5.95 mg/mL和5.90 mg/mL。将柠檬汁还原法制备的AgNPs用于果蔬表面农残检测,对于百草枯、多菌灵的检出限分别最低至3.90 ng/kg及0.22μg/kg。[结论]这项工作为果蔬农残快检提供了一种绿色、便捷的SERS材料制备方法,为实现农产品农药残留的快速、灵敏检测提供一种新的途径。
[Objective]The use of pesticides is one of the root causes of food safety problems.Pesticide exposure and pesticide residues can not only lead to environmental pollution issues but also seriously affect human health.In order to meet the rapid and sensitive detection needs of pesticide residues in agricultural products,a method based on lemon juice reduction to prepare silver nanoparticles(AgNPs)is reported in this research.[Methods]First,fresh lemon juice was filtered through filter paper and diluted to a 2%lemon juice aqueous solution.Then,a certain concentration of AgNO3 solution,50 mm NaOH solution were prepared and stored at room temperature.Then,10 mL ddH2O,2 mL NaOH,2 mL 2%lemon juice,and 5 mL AgNO3 solution were mixed.When the solution turned to a clear yellow color,the solution was centrifuged to obtain AgNPs.The morphology and structure of AgNPs were observed by transmission electron microscopy(TEM).In order to verify the successful synthesis of the nanoparticles and the distribution characteristics of the nanoparticles,ultravio‐let spectroscopy was used for measurement and analysis,and 4-ATP was used as a SERS probe to preliminarily verify the SERS en‐hancement performance of AgNPs.Furthermore,the content of the main reducing components in lemon juice,namely ascorbic acid,glucose,and fructose was analyzed.The content of ascorbic acid in lemon juice was determined by high-performance liquid chroma‐tography,and the content of glucose and fructose in lemon juice was determined by UV-visible spectrophotometry.To verify the stabil‐ity and uniformity of the SERS signal of the nanoparticles,4-ATP was used as an surface enhancement of raman scattering(SERS)probe for detection analysis.The stability of the SERS performance of the colloidal substrate within 41 days and the SERS perfor‐mance at temperatures ranging from 0-80°C were analyzed.Using 4-ATP as the SERS probe,the experimental conditions were opti‐mized for the preparation of AgNPs by the lemon juice method,including pH and AgNO3 concentration.To validate the practical us‐ability of the nanoparticles,the solutions of paraquat and carbendazim and the detection limits of pesticide residues on different fruits and vegetables were detected by SERS.[Results and discussions]The method for preparing AgNPs has the advantages of simple operation,green and easy synthesis.The parti‐cle morphology and size of the prepared AgNPs were basically uniform,with a size of about 20 nm.The ultraviolet-visible spectrum of AgNPs solution showed that the absorption peak was about 400 nm and the peak shape was narrow,indicating that the colloidal so‐lution had good homogeneity.The detection limit of 4-ATP as the SERS probe was 10-14 M,indicating that the nanoparticle had a good SERS.In addition,the content of ascorbic acid,the main reducing ingredient,in lemon juice measured by high-performance liquid chromatography(HPLC)was 395.76μg/mL.The contents of glucose and fructose,which were the main reducing components in lem‐on juice,were 5.95 and 5.90 mg/mL,respectively.Furthermore,the characterization and analysis results of the AgNPs prepared by the mixed reducing solution prepared according to the concentration data of each component showed that the AgNPs obtained were al‐so uniform in morphology and size,with a diameter of about 20 nm,but the SERS enhancement performance was not as good as that of the AgNPs reduced by lemon juice.The SERS signal uniformity of the AgNPs reduced by lemon juice analyzed results showed that the peak intensity of the SERS spectral of 4-ATP at different sites at the same concentration was not significantly changed for 15 times,and its standard deviation RSD=5.03%,which was much lower than the intersubstrate RSD value(<16%)of the qualified new SERS active substrate for quantitative analysis.The temporal stability and temperature stability of AgNPs analyzed results showed that the nanoparticles still had SERS enhanced performance after 41 days of storage,and had SERS enhanced performance stability over a wide temperature range(0~80℃).In addition,the optimization results of experimental conditions showed that the optimal pH for the preparation of AgNPs was around 7.5,and the optimal range of AgNO3 concentration used was 1.76×10^(-4)~3.33×10^(-4) mol/L.Finally,using AgNPs prepared by lemon juice reduction method for pesticide residue SERS detection on the surface of fruits and vege‐tables,the detection limits for paraquat and carbendazim in solution were as low as 10-14 and 10-10 M,respectively,and the concentra‐tion of pesticides showed a good linear relationship with Raman spectral intensity.The lowest detection limits for paraquat and carben‐dazim residues on different fruits and vegetables were as low as 3.90 ng/kg and 0.22µg/kg,respectively.[Conclusions]This work provides a green and convenient method for preparing SERS materials for rapid detection of pesticide resi‐dues on fruits and vegetables.This method has practical value for universal operation.The prepared AgNPs can be used for trace pesti‐cide residue detection,providing a pathway for rapid and sensitive detection of pesticide residues in agricultural products.
作者
董闪闪
张凤秋
夏琦
李佳林
刘超
柳少伟
陈翔宇
王儒敬
黄青
DONG Shanshan;ZHANG Fengqiu;XIA Qi;LI Jiain;LIU Chao;LIU Shaowei;CHEN Xiangyu;WANG Rujing;HUANG Qing(School of Physics and Laboratory of Zhongyuan Light,Zhengzhou University,Zhengzhou 450001,China;Agricultural Sen‐sors and Intelligent Perception Technology Innovation Center of Anhui Province,Zhongke Hefei Institutes of Collaborative Research and Innovation for Intelligent Agriculture,Anhui Hefei 231131,China;Intelligent Agriculture Engineering Laboratory of Anhui Province,Institute of Intelligent Machines,Hefei Institutes of Physical Science,Chinese Academy of Sciences,Anhui Hefei 230031,China;School of Materials and Chemistry,Anhui Agricultural University,Hefei 230036,China;Institute of Physical Science and Information Technology,Anhui University,Hefei 230601,China)
出处
《智慧农业(中英文)》
CSCD
2024年第1期101-110,共10页
Smart Agriculture
基金
中国科学院合肥研究院长融合基金项目(E02AAG85135)。