Srivastava Anjana, Tandon Shishir, Singh Gajanpal, Pathak Shruti
Department of Chemistry, Govind Ballabh Pant University of Agriculture and Technology, Pantnagar, Udham Singh Nagar, Uttarakhand, India.
PLoS One. 2025 Sep 11;20(9):e0330736. doi: 10.1371/journal.pone.0330736. eCollection 2025.
Reliability and accuracy of an analytical method is ensured by method validation technique. The present study was aimed to optimize and validate a rapid, reliable and accurate method for quantitatively determining pesticide residues of a diverse group in okra matrix. All method performance characteristics pertaining to method validation was tested. Three different pesticides viz. Thiamethoxam, Ethion, and lambda Cyhalothrin of diverse chemical classes which are applied on okra cultivation and have high MRLs as per FSSAI, were selected. Okra available in local market is often laced with these pesticides. The higher concentrations of pesticide residues in okra can be severely toxic to consumers. Thus validation of method that is simple and cost effective and can give accurate results is desirable for monitoring of these pesticides in okra. Hence a method was validated for analysis of Thiamethoxam, Ethion, and lambda Cyhalothrinby HPLC/GC. Pesticide residues fromokra samples were extracted using modifiedQuEChERs method, followed by injection into GC/HPLC. The validated method demonstrated suitable specificity, linearity, recovery etc.The calibration curves were linear for all the threepesticides with a regression coefficient, r2 > 0.99. Matrix effect observed for all three pesticides in okra, fell within the range of ±20%. All pesticides were quantified successfully at a concentration of 0.30 mg/kg with an average recovery of more than 70% and a relative standard deviation (RSD) of less than 20%. The procedure was simple, rapid, cost effective and depicted high accuracy. The greenness of the method evaluated on Agro Eco Scale was satisfactory. Theestimation of uncertainties based on the validation data, werefound to be below the default limit of 50%. The quality control (QC) charts based on the basis of intra-laboratory performance were prepared at LOQ of pesticides to ensure the validity and accuracy of laboratory test results.
分析方法的可靠性和准确性通过方法验证技术来确保。本研究旨在优化和验证一种快速、可靠且准确的方法，用于定量测定秋葵基质中多种农药残留。测试了与方法验证相关的所有方法性能特征。选择了三种不同的农药，即噻虫嗪、乙硫磷和高效氯氟氰菊酯，它们属于不同的化学类别，用于秋葵种植，并且根据印度食品安全与标准管理局（FSSAI）规定具有较高的最大残留限量。当地市场上的秋葵通常含有这些农药。秋葵中较高浓度的农药残留可能对消费者具有严重毒性。因此，对于监测秋葵中的这些农药而言，验证一种简单、经济高效且能给出准确结果的方法是很有必要的。因此，通过高效液相色谱/气相色谱法（HPLC/GC）对噻虫嗪、乙硫磷和高效氯氟氰菊酯的分析方法进行了验证。秋葵样品中的农药残留采用改良的QuEChERS方法进行提取，随后注入气相色谱/高效液相色谱仪。验证后的方法显示出合适的特异性、线性、回收率等。所有三种农药的校准曲线均呈线性，回归系数r2＞0.99。在秋葵中观察到的所有三种农药的基质效应均在±20%的范围内。所有农药在浓度为0.30 mg/kg时均成功定量，平均回收率超过70%，相对标准偏差（RSD）小于20%。该方法简单、快速、经济高效且具有很高的准确性。基于农业生态尺度评估的该方法的绿色度令人满意。基于验证数据对不确定度的估计发现低于50%的默认限值。在农药的定量限（LOQ）处制备了基于实验室内性能的质量控制（QC）图，以确保实验室测试结果的有效性和准确性。
