Separation of a binary mixture of pesticides in fruits using a flow-through optosensor

Applying novel economic simple green sample preparation procedures on natural and industrial specimens for chromatographic determination of insecticidal residues

Spraying a tertiary blend of the insecticides (hexythiazox, imidacloprid, and thiamethoxam), on tomato fruits, is a routine in agriculture-attentive countries. A simple green sample preparation technique was developed and applied to the field samples. Specific HP-TLC and RP-HPLC methodologies are established to estimate the residual insecticides and applied to the prepared field specimens. In the planner chromatographic methodology, methanol:chloroform:glacial acetic acid:triethyl amine (8.5:1.5:0.2:0.1, v/v) is recommended as a mobile system. The other one is columnar chromatography; acetonitrile: water (20:80, v/v), pH 2.8, is recommended as a mobile system. The validation parameters were examined following the ICH rules. The means percentages and standard deviations of the accuracy of the HP-TLC method for the determined compounds were 99.66 ± 0.974, 99.41 ± 0.950, and 99.89 ± 0.983, correspondingly. The values were 99.24 ± 0.921, 99.69 ± 0.681, and 99.20 ± 0.692, correspondingly, when they were determined by the RP-HPLC method. The relative standard deviation percentages of the methods' repeatability and intermediate precision ranged from 0.389 to 0.920. Both methods were highly specific having resolution factors of ≥ 1.78 and selectivity factors of ≥ 1.71. They were applied to the field samples perfectly.

Novel sequential separation and determination of a quaternary mixture of fungicides by using an automatic fluorimetric optosensor

A versatile flow-through multi-optosensor is proposed for the separation and spectrofluorimetric determination of mixtures of four widely used pesticides: carbendazim, thiabendazole, carbaryl and o-phenylphenol at µg g^-1 levels in fruits. The flow system is based on the online pre-concentration and separation of the pesticides on a solid sensing microzone, followed by the sequential measurement of their native fluorescence. The separation of the pesticides takes place on a solid support located in the same flow cell, on which analytes are temporarily immobilized and separated from the matrix due to their different retention/desorption kinetics when they interact with the C₁₈ silica gel microbeads. Suitable analytical parameters were obtained for the selected analytes, with method detection and quantification limits ranging between 0.1-0.5 and 0.2-1.6 µg g^-1, respectively. These values comply with the maximum residue limits (MRLs) established by the Codex Alimentarius for these commodities; in addition, carbendazim, thiabendazole and ortho-phenylphenol comply with the MRLs of The European Union. The developed method was applied to the analysis of citrus fruits by performing recovery studies. Recoveries between 85% and 115% were obtained in all cases, and the results were confirmed by a liquid chromatography-mass spectrometry reference method.

A colorimetric sensor array based on sulfuric acid assisted KMnO4 fading for the detection and identification of pesticides

Pesticides play a critical role in improving crop yield in modern agriculture, but their residues significantly harm the environment and human health. Herein, a novel and simple colorimetric sensor array built on sulfuric acid assisted KMnO₄ fading strategy has been developed for pesticides detection and discrimination. This sensor array is facilely fabricated by KMnO₄ and sulfuric acid through simply adjusting their concentrations and ratios. Hierarchical clustering analysis (HCA) demonstrates that the as-fabricated colorimetric sensor array has a high dimensionality, and shows excellent capability to recognize common kinds of pesticides from potential interferants. Semi-quantitative detection was achieved through combining HCA and corresponding fitting curves. Moreover, the proposed sensor array was successfully applied to detect pesticide residues (e.g. carbaryl) in real samples. The strategy described herein will not only "maximally" simplify the design and fabrication approach, but expand the application fields of colorimetric sensor array methodology towards weak-reactive analytes.

Magnetic Cu-MOFs embedded within graphene oxide nanocomposites for enhanced preconcentration of benzenoid-containing insecticides

Hybrid magnetic nanocomposites based on Cu-MOFs, graphene oxide (GO), and Fe₃O₄ nanoparticles (NPs) were prepared via chemical bonding approach, which GO were used as platforms to load nanostructured Cu-MOFs and Fe₃O₄ NPs. The composite features both magnetic separation characteristics and high MOFs porosity, making it an excellent adsorbent for magnetic solid-phase extraction (MSPE). The as-synthesized nanocomposites are characterized by XRD, TGA, SEM, TEM, nitrogen adsorption-desorption analysis and FT-IR spectroscopy. The composites are used in MSPE of six aromatic insecticides from various real samples prior to their quantification by HPLC. Amount of adsorbent, extraction times, extraction temperature, desorption times and oscillation rate are optimized. Under the optimal conditions, the method has a relative standard deviations (RSDs) of 1.9-2.7%, and good linearity (correlation coefficients higher than 0.9931). The low LOD and LOQ for six insecticides are found to be 0.30-1.58μgL^-1 and 1.0-5.2μgL^-1, respectively. The RSDs of within batch extraction are 1.6-9.5% and 3.9-12% for batch to batch extraction. The experimental results suggest that the nanocomposites have potential application for removal of hazardous pollutants from effluents.

Recent advances in flow injection analysis

A dynamic development of methodologies of analytical flow injection measurements during four decades since their invention has reinforced the solid position of flow analysis in the arsenal of techniques and instrumentation of contemporary chemical analysis.

Strong base pre-treatment for colorimetric sensor array detection and identification of N-methyl carbamate pesticides

A strategy of strong base pre-treatment was developed and employed to the colorimetric sensor array detection and differentiation of N-methyl carbamate pesticides.

Colorimetric sensor array for detection and identification of organophosphorus and carbamate pesticides

Due to relatively low persistence and high effectiveness for insect and pest eradication, organophosphates (OPs) and carbamates are the two major classes of pesticides that broadly used in agriculture. Hence, the sensitive and selective detection of OPs and carbamates is highly significant. In this current study, a colorimetric sensor array comprising five inexpensive and commercially available thiocholine and H2O2 sensitive indicators for the simultaneous detection and identification of OPs and carbamates is developed. The sensing mechanism of this array is based on the irreversible inhibition capability of OPs and carbamates to the activity of acetylcholinesterase (AChE), preventing production of thiocholine and H2O2 from S-acetylthiocholine and acetylcholine and thus resulting in decreased or no color reactions to thiocholine and H2O2 sensitive indicators. Through recognition patterns and standard statistical methods (i.e., hierarchical clustering analysis and principal component analysis), the as-developed array demonstrates not only discrimination of OPs and carbamates from other kinds of pesticides but, more interestingly, identification of them exactly from each other. Moreover, this array is experimentally confirmed to have high selectivity and sensitivity, good anti-interference capability, and potential applications in real samples for OPs and carbamates.