Highly Sensitive and Selective Detection of Enrofloxacin Residues in Chicken Based on Solution-Gated Graphene Field-Effect Transistors

Abstract

Enrofloxacin (ENR) has been widely used in poultry farming because of its low cost and high efficiency, yet ENR residues due to improper use may cause severe damage to human body. Herein for effective control of ENR residues, we report an ultra-sensitive ENR sensor based on a solution-gated graphene field-effect transistor (SGGT) through modification of the gate with Au nanoparticles and multi-walled carbon nanotube, dispersed by poly diallyl-dimethyl ammonium chloride (PDDA). The detection limit of the optimized SGGT-based sensor was as low as 10 nM for ENR, and the linear range was 300 nM ~ 30 μM. The as-prepared sensor was applied to ENR-spiked chicken samples, and the detection recoveries were 94.47% ~ 105.95%. Considering the low-cost and easy manufacturing features of the SGGT-based sensor, we expect that it offers a highly sensitive sensing platform for on-site and real-time detection of ENR residues in many other food samples.

Keywords: Enrofloxacin, Chicken, Solution gated graphene field-effect transistor, Multi-wall carbon nanotube, Gold nanoparticles