Department of Chemistry, Indian Institute of Technology Ropar, Rupnagar, Punjab 140001, India.
Department of Biomedical Engineering, Indian Institute of Technology Ropar, Rupnagar, Punjab 140001, India.
Anal Chem. 2023 Oct 3;95(39):14533-14540. doi: 10.1021/acs.analchem.3c01331. Epub 2023 Sep 19.
Modern agricultural practice relies heavily on pesticides and herbicides to increase crop productivity, and consequently, their residues have a negative impact on the environment and public health. Thus, keeping these issues in account, herein we developed an azodye-based chromogenic sensor array for the detection and discrimination of pesticides and herbicides in food and soil samples, utilizing machine learning approaches such as hierarchical clustering analysis, principal component analysis, linear discriminant analysis (LDA), and partial least square regression (PLSR). The azodye-based sensor array was developed in combination with various metal ions owing to their different photophysical properties, which led to distinct patterns toward various pesticides and herbicides. The obtained distinct patterns were recognized and processed through automated multivariate analysis, which enables the selective and sensitive identification and discrimination of various target analytes. Further, the qualitative and quantitative determination of target analytes were performed using LDA and PLSR; the results obtained show a linear correlation with varied concentrations of target analytes with values from 0.89 to 0.96, the limit of detection from 5.3 to 11.8 ppm with a linear working range from 1 to 30 μM toward analytes under investigation. Further, the developed sensor array was successfully utilized for the discrimination of a binary mixture of pesticide (chlorpyrifos) and herbicide (glyphosate).
现代农业实践严重依赖农药和除草剂来提高作物产量，因此，它们的残留对环境和公共健康产生了负面影响。因此，考虑到这些问题，我们在此开发了一种基于偶氮染料的比色传感器阵列，用于检测和区分食物和土壤样本中的农药和除草剂，利用机器学习方法，如层次聚类分析、主成分分析、线性判别分析（LDA）和偏最小二乘回归（PLSR）。该偶氮染料基传感器阵列是结合各种金属离子开发的，因为它们具有不同的光物理性质，这导致了对各种农药和除草剂的不同模式。通过自动化的多元分析来识别和处理获得的独特模式，从而能够选择性和灵敏地识别和区分各种目标分析物。此外，使用 LDA 和 PLSR 对目标分析物进行定性和定量测定；得到的结果显示出与目标分析物不同浓度的线性相关性， 值从 0.89 到 0.96，检测限从 5.3 到 11.8 ppm，线性工作范围从 1 到 30 μM 到被调查的分析物。此外，所开发的传感器阵列成功用于区分二元混合物农药（毒死蜱）和除草剂（草甘膦）。
