Mirghafouri M Reza, Abbasi-Moayed Samira, Ghasemi Forough, Hormozi-Nezhad M Reza
Department of Chemistry, Sharif University of Technology, Tehran, 11155-9516, Iran.
Anal Methods. 2020 Dec 23;12(48):5877-5884. doi: 10.1039/d0ay02039g.
Great attention has been directed towards developing rapid and straightforward methods for the identification of various pesticides that are usually used simultaneously in citrus fruits. The extensive use of diverse classes of pesticides in citrus fruits and their high toxicity may cause serious diseases in the human body. In the current study, a non-enzymatic sensor array has been developed for the identification and discrimination of five different pesticides belonging to diverse classes, including organophosphate, carbamate, and bipyridylium. For this aim, two gold nanoparticles (AuNPs) with different capping agents, citrate and borohydride, were used as sensing elements. The aggregation-induced spectra alterations of AuNPs were utilized to identify the pesticides in a wide range of concentrations (20-5000 ng mL-1). We have employed data visualization methods (i.e., heat maps, bar plots, and color difference maps), a supervised pattern recognition method (i.e., linear discrimination analysis), and partial least squares regression to qualitatively and quantitatively determine the pesticides. Finally, the practical applicability of the developed sensor array was evaluated for the identification of target pesticides in lime peel. The outcomes revealed that the probe could accurately verify the absence or presence of the pesticides in lime fruit.
人们高度关注开发快速、直接的方法来鉴定通常同时用于柑橘类水果的各种农药。柑橘类水果中广泛使用各类农药及其高毒性可能会导致人体严重疾病。在当前研究中，已开发出一种非酶传感器阵列，用于鉴定和区分属于不同类别（包括有机磷、氨基甲酸酯和联吡啶鎓）的五种不同农药。为此，使用了两种具有不同封端剂（柠檬酸盐和硼氢化物）的金纳米颗粒（AuNPs）作为传感元件。利用AuNPs的聚集诱导光谱变化来鉴定宽浓度范围（20 - 5000 ng mL-1）的农药。我们采用了数据可视化方法（即热图、柱状图和色差图）、监督模式识别方法（即线性判别分析）和偏最小二乘回归来定性和定量测定农药。最后，评估了所开发传感器阵列在鉴定酸橙果皮中目标农药方面的实际适用性。结果表明，该探针可以准确验证酸橙果实中农药的存在与否。
