Issue 10, 2018, Issue in Progress

An azo-coupling reaction-based surface enhanced resonance Raman scattering approach for ultrasensitive detection of salbutamol

Abstract

To date, great achievements with GC-MS, HPLC-MS, and fluorescence biosensing techniques have been made to detect illegal additives of salbutamol (SAL) in swine meat. However, these methods are not suitable for rapid on-site screening due to either costly instruments or rather complicated and/or time consuming sample pretreatments. Herein, a simple, rapid and ultrasensitive approach based on an azo-coupling reaction and surface-enhanced resonance Raman scattering (SERRS) is presented. By combining with a magnetic SERS substrate, an indirect detection for SAL, with a LOD of 1.0 × 10−11 M (2.39 pg mL−1), was realized. Moreover, a colorimetric method for naked eye detection was successfully carried out for rapid screening of SAL in concentrations higher than 2.09 × 10−5 M (5 μg mL−1). In addition, the proposed method was successfully applied for the rapid determination of SAL in real swine meat. The entire process, including pretreatment, coupling reaction and SERRS detection, was performed within 7 min. Moreover, the SERRS fingerprint band being specific to corresponding functional group guarantees the selectivity for the target molecule. Therefore, the proposed strategy in the present study offers a new way to identify trace amounts of analytes, such as SAL as well as other illegal additives in health-related products and food.

Graphical abstract: An azo-coupling reaction-based surface enhanced resonance Raman scattering approach for ultrasensitive detection of salbutamol

Supplementary files

Article information

Article type
Paper
Submitted
01 Dec 2017
Accepted
11 Jan 2018
First published
01 Feb 2018
This article is Open Access
Creative Commons BY-NC license

RSC Adv., 2018,8, 5536-5541

An azo-coupling reaction-based surface enhanced resonance Raman scattering approach for ultrasensitive detection of salbutamol

S. Yu, Z. Liu, J. Zhang, H. Li, N. Xu, X. Yuan and Y. Wu, RSC Adv., 2018, 8, 5536 DOI: 10.1039/C7RA12927K

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