Quantitative analysis of typical fluoroquinolone antibiotics in livestock feed using terahertz spectrum

Abstract

The antibiotic residues are increasing concerns in agricultural and food products, an effective, rapid, and accurate detection method of antibiotics is still in exploration stage for applications. In this study, we employed terahertz (THz) spectroscopy as a tool to find its feasibility to detect quinolone antibiotics in livestock feed (LSF) quantitatively. A total of 220 samples with pefloxacin (PEF) and fleroxacin (FLE) in LSF were prepared separately and the THz spectrum of each sample was measured using a TERA K15 THz-TDS system. Then, the absorption characteristics of PEF and FLE in THz band were analyzed. For the binary and ternary mixtures, successive projections algorithm (SPA), competitive adaptive reweighted sampling (CARS) algorithm, and the combination algorithm (CARS-SPA) were selected as dimensionality reduction process methods, and back propagation neural network (BPNN) was selected to establish a model for the quantitative analysis. The results showed, PEF has two typical absorption peaks at 0.775 and 0.988 THz, and FLE has two typical absorption peaks at 0.919 and 1.088 THz, which implies the features can be used for qualitative identification. For the quantitative analysis, The CARS-BPNN model achieved the best predictive ability based on the prediction set, and the correlation coefficients can reach 0.98 for both the binary and ternary mixtures. The results also showed that predictive models of the ternary mixtures have better performance than that of the binary mixtures. The research provides theoretical and technical reference for practical detection of antibiotic residues in livestock and poultry industry.