A rapid and convenient screening method for detection of restricted monensin, decoquinate, and lasalocid in animal feed by applying SERS and chemometrics

• Published in: Food and chemical toxicology 2020-10, Vol.144, p.111633-111633, Article 111633
• Main Authors: Lee, Kyung-Min, Yarbrough, Danielle, Kozman, Mena M., Herrman, Timothy J., Park, Jinhyuk, Wang, Rui, Kurouski, Dmitry
• Format: Article
• Language: English
• Subjects: Antimicrobials; Chemometrics; Food safety; Gold nanoparticles; Surface-enhanced Raman spectroscopy (SERS)
• ISSN: 0278-6915; 1873-6351
• DOI: 10.1016/j.fct.2020.111633

The surface-enhanced activities of size- and shape-controlled gold nanoparticles (AuNPs) with superior chemical stability were investigated to explore a possible development of a simple and non-destructive spectroscopic method to help the regulatory agency's analytical services for rapid detection and characterization of selected antimicrobials in animal feeds. Feed samples spiked at different concentration ranges of antimicrobials were evaluated using AuNPs as a surface-enhanced Raman spectroscopy (SERS) agent. The collected SERS spectra were mathematically preprocessed for further analysis. The classification models obtained 100% predictive accuracy with zero or little misclassification. The first two canonical variables (p = 0.001) could explain >95% of the variability in preprocessed spectral data. Most chemometric models for predicting MON, DEC, and LAS concentrations showed a high predictive accuracy (r2 > 0.90), lower predictive error ( 0.05). The findings and implications from the study indicate that SERS would be a powerful and efficient technique possessing a great potential serving as an excellent monitoring and screening tool for antimicrobial contaminated samples in the on-site analysis. [Display omitted] •SERS technique was investigated for rapid detection of antimicrobials in feed.•SERS spectral difference was correlated with a level of antimicrobials in samples.•Chemometric models showed an excellent classification accuracy and low error rate.•Quantification models for antimicrobials revealed a high predictability and accuracy.•SERS has a great potential to serve as an efficient screening tool for antimicrobials.