FT-MIR and Raman spectroscopy coupled to multivariate analysis for the detection of clenbuterol in murine model

Abstract

A fast and simple screening method for the determination of clenbuterol at the ppb level in a murine model was demonstrated by Mid Infrared (MIR) and Raman spectroscopy in conjunction with multivariate analysis. In order to build the calibration models to quantify clenbuterol in rat meat, mixtures of rat meat and clenbuterol were prepared in a range of 5–10 000 ppb. Partial Least Square (PLS) analysis was used to build the calibration model. The results shown that Mid Infrared and Raman spectroscopy were efficient, but Mid Infrared (R² = 0.966 and SEC = 0.27) were superior to Raman (R² = 0.914 and SEC = 1.167). The SIMCA model developed showed 100% classification rate of rat meat samples with or without clenbuterol. The results were confirmed with contaminated meat samples from animals treated with clenbuterol. Chemometric models represent an attractive option for meat quality screening without sample pretreatments which can identify veterinary medicinal products at the ppb level.