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Evaluation of the SERS‐based strategy in fast and on‐site food safety inspection: Qualitative and quantitative analysis of trace unexpected herbicide in complicated herbicide matrix
Author(s) -
Pan Cheng,
Chen Hongju,
Lin Qin,
Luo Siheng,
Gu Jialei,
Ye Shaoqing,
Zeng Yongming,
Ren Bin,
Tian Zhongqun,
Xue Wendong,
Liu Guokun
Publication year - 2020
Publication title -
journal of raman spectroscopy
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.748
H-Index - 110
eISSN - 1097-4555
pISSN - 0377-0486
DOI - 10.1002/jrs.6026
Subject(s) - raman spectroscopy , matrix (chemical analysis) , nanotechnology , qualitative analysis , trace (psycholinguistics) , complex matrix , food safety , surface enhanced raman spectroscopy , chemistry , reliability (semiconductor) , computer science , biological system , chromatography , materials science , biochemical engineering , raman scattering , engineering , physics , optics , qualitative research , social science , linguistics , philosophy , food science , power (physics) , quantum mechanics , sociology , biology
Recently, surface‐enhanced Raman spectroscopy (SERS)‐based detection strategies have been widely developed for various practical applications, due to the near‐single‐molecule sensitivity and fingerprint identification capability. However, the qualitative and quantitative reliability of SERS have always been questioned when comparing with the classical GC/LC–MS techniques. Here, we systematically compared the properties of SERS and LC–MS in the detection of an unexpected herbicide in commercial herbicide. The result showed that, in the case of the ultra‐trace target detection in a complicated matrix, SERS‐based strategy exhibited high sensitivity and a much higher detection efficiency than the LC–MS‐based one, which demonstrated a more accurate quantifiability being facilitated with a well‐controlled sample pretreatment. Therefore, we showed that SERS could be further implemented in fast and on‐site detection tools for food safety application and environment monitoring.