Microextraction by packed sorbent: Introducing a novel hybrid silica-based chitosan-graphene oxide biosorbent for the evaluation of pesticides and antibiotics in food matrices

Abstract

This study introduces a novel silica-graphene oxide@chitosan (SiGO@CS) material as a packed biosorbent for microextraction by packed sorbent (MEPS), followed by liquid chromatography-tandem mass spectrometry (LC-MS/MS) analysis of pesticides (atrazine and thiamethoxam) and antibiotics (ceftiofur and sulfonamide) in food samples. The graphene-based aerogel was modified with varying percentages of silica-graphene oxide/chitosan (w/w) and characterized to confirm successful chitosan incorporation. Optimization of the MEPS protocol, using 2^4–1 and 2³ experimental designs, identified draw/eject and washing cycles as the most influential parameters for extraction efficiency. The SiGO@CS biosorbent with 80 % CS/SiGO (w/w) exhibited superior extraction efficiency compared to other ratios and commercial sorbents. The method demonstrated excellent linearity for all analytes (R² > 0.9900), with low limits of detection (LOD) and quantification (LOQ) ranging from 0.020 to 0.045 µg l^-1 and 0.045 to 1.0 µg l^-1 for pesticides, respectively, and 5 to 15 µg l^-1 and 15 to 20 µg l^-1 for antibiotics, respectively. Trueness values were within 82 % to 109 %. The method's green credentials were confirmed using AGREEprep and the Green Analytical Procedure Index (GAPI) approach, highlighting sorbent reusability (over 15 times) and rapid analytical throughput (5 min per sample) with low use of pre-treated sample extract volume (500 µL). The application to local corn, tomato, and milk samples confirmed the detection and quantification of thiamethoxam and atrazine at concentrations above the recommended ingestion per day for one sample of tomato and corn out of the three samples analyzed. Furthermore, using the novel SiGO@CS biosorbent in the MEPS protocol offers a green, high-performance analytical alternative to traditional sorbent phases, with the potential for evaluating trace levels of pesticides and antibiotics in food matrices.