Abstract

Public health and food safety are gaining attention globally. Consumer health can be protected from chemical residues in meat by early detection or screening for antibiotic residues before selling the meat commercially. However, conventional practices are normally applied after slaughtering, which leads to massive business losses. This study aimed to use portable surface-enhanced Raman spectroscopy (SERS) equipped with multivariate curve resolution-alternation least squares (MCR-ALS) to determine the concentrations of enrofloxacin, oxytetracycline, and neomycin concentrations. This approach can overcome the problems of business loss, costs, and time-consumption, and limit of detection (LOD). Aqueous solutions of three standard antibiotics (enrofloxacin, oxytetracycline, and neomycin) with different concentrations were prepared, and the LOD for each antibiotic solution was determined using SERS. Extracted pig urine was spiked with enrofloxacin at concentrations of 10, 20, 50, 100, and 10,000 ppm. These solutions were investigated using SERS and MCR-ALS analysis. Urine samples from pigs at 1 and 7 days after enrofloxacin administration were collected and investigated using SERS and MCR-ALS to differentiate the urinary enrofloxacin concentrations. The LOD of enrofloxacin, oxytetracycline, and neomycin in aqueous solutions were 0.5, 2.0, and 100 ppm, respectively. Analysis of enrofloxacin spiking in pig urine samples demonstrated the different concentrations of enrofloxacin at 10, 20, 50, 100, and 10,000 ppm. The LOD of spiking enrofloxacin was 10 ppm, which was 10 times lower than the regulated value. This technique was validated for the first time using urine collected on days 1 and 7 after enrofloxacin administration. The results revealed a higher concentration of enrofloxacin on day 7 than on day 1 due to consecutive administrations. The observed concentration of enrofloxacin was closely correlated with its circulation time and metabolism in pigs. A combination of SERS sensing platform and MCR-ALS is a promising technique for on-farming screening. This platform can increase the efficiency of antibiotic detection in pig urine at lower costs and time. Expansion and fine adjustments of the Raman dataset may be required for individual farms to achieve higher sensitivity.

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