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The quinolone antibiotics represented by enrofloxacin (ENRO) are harmful to the ecological environment and human health due to illegal excessive use, resulting in increasing food residues and ENRO levels in the environment. To this end, we developed a MIPs–SERS method using surface-enhanced Raman spectroscopy (SERS) and molecularly imprinted polymers (MIPs) to detect ENRO in food matrices. Firstly, a layer of silver nanoparticles (Ag NPs) with the best SERS effect was synthesized on the surface of copper rods as the enhancing material by in situ reductions, and then MIPs targeting ENRO were prepared by the native polymerization reaction, and the MIPs containing template molecules wrapped on the surface of silver nanoparticle films (Ag NPs–MIPs) were obtained. Our results showed that the Ag NPs–MIPs could specifically identify ENRO from the complex environment. The minimum detection limit for ENRO was 0.25 ng/mL, and the characteristic peak intensity of ENRO was linearly correlated to the concentration with a linear range of 0.001~0.1 μg/mL. The experimental results showed that in comparison to other detection methods, the rapid detection of ENRO in food matrices using Ag NPs–MIPs as the substrate is reliable and offers a cost-effective, time-saving, highly selective, and sensitive method for detecting ENRO residues in real food samples.

Molecularly imprinted polymers (MIPs) specifically targeting pentachloronitrobenzene (PCNB) and containing silver nanoparticles have been prepared by free radical polymerization reaction using methyl methacrylate (MMA) as a functional monomer, PCNB as a template molecule, 1,4-butanedioldimethacrylate as a cross linker, lauroyl peroxide (LPO) as an initiator, and the silver nanoparticles with the best surface-enhanced Raman scattering (SERS) effect as SERS enhancement materials. Our results indicated that MIPs specifically recognize PCNB from complex matrices. The intensity of the PCNB characteristic peak was proportional to the concentration, with a linear range of 0.005 to 0.15 μg/mL and a limit of detection of 5.0 ng/mL. The recovery rates and relative standard deviation for the detection of PCNB spiked in the rice samples were from 94.4% to 103.3% and from 4.6% to 7.4%, respectively. The experimental results are consistent with those by the GC-MS method, indicating that the rapid detection of PCNB in food matrices by SERS-MIPs is reliable. In view of the insolubility of PCNB in water, oil-soluble silver nanoparticles were synthesized which can be expanded to detect oil-soluble toxic substances. For the first time, the proposed method provides a point-of-care and cost-effective tool for rapidly detecting PCNB in food matrices with high sensitivity and selectivity by employing SERS-MIPs method.