Advanced Magnetic Imprinted Polymers Integrated with In Situ Ionization Mass Spectrometry for High-Throughput Pesticide Screening and Detection in Food Matrices

This research introduces magnetic molecularly imprinted polymers (MMIPs) as a novel tool for the efficient extraction and detection of pesticide residues in food products. The MMIPs exhibit a notable adsorption capacity ranging from 15.70 to 23.57 mg g^-1, showcasing their efficacy in preconcentrating multiple pesticides. By leveraging Low-Temperature Plasma Mass Spectrometry (LTP-MS) in conjunction with MMIP-based sample pretreatment, the study achieves rapid screening of 108 pesticides in agricultural products, boasting a detection sensitivity of 86.9%. The MMIPs demonstrate exceptional selectivity, enabling swift separation in an external magnetic field, thereby reducing reliance on chemical reagents and facilitating multiple reuses. Rigorous evaluation of the MMIPs' binding properties, magnetic separation efficiency, and reusability underscores their potential for class-selective enrichment of pesticide residues. The MMIPs were meticulously characterized using a comprehensive array of analytical techniques, including FT-IR spectrometry, SEM, TEM, VSM, and UV-vis spectrophotometry. Remarkably, the MMIPs' performance in pesticide extraction yielded promising results, with successful qualitative detection of 78 out of 87 identified pesticides in cucumber samples, 71 out of 85 identified pesticides in tomato samples, 55 out of 64 identified pesticides in cabbage samples, and 42 out of 48 identified pesticides in leek samples, achieving recovery rates within the range of 60.12% to 119.84% for 50.91% of the identified pesticides. The screening detection limit (SDL) for the 86 pesticides in the MMMIP-LTP-MS method was set according to the corresponding maximum residue limit (MRL) in the National Food Safety Standard of China (GB 2763-2021). The quantification limits of MMMIPs-LC-TQ-MS ranged from 0.000043 to 5.52 µg g^-1, with recoveries between 60.12% and 119.84%. These findings underscore the significant impact of MMIP-based sample preparation in enhancing the precision and efficiency of high-throughput determination of pesticide residues in food products.