| Literature DB >> 27601204 |
Khaled El Hawari1,2, Samia Mokh1, Samah Doumyati3, Mohamad Al Iskandarani1,3, Eric Verdon2.
Abstract
A new, simple and fast method was developed for the determination of multi-class antibiotic residues in honey (sulfonamides, tetracyclines, macrolides, lincosamides and aminoglycosides). Separation and determination were carried out by LC-MS/MS. During sample preparation, various parameters affecting extraction efficiency were examined, including the type of solvent, pH, efficiencies of cleavage of N-glycosidic linkages by hydrochloric acid, ultrasonic extraction and its duration compared with shaking, along with dispersive SPE clean-up. Experiments with fortified samples demonstrated that 10 min of ultrasonic treatment with acidified methanol (HCl 2 M) followed by dispersive SPE clean-up with 50 mg PSA gave an effective sample preparation method for several classes of antibiotics in honey. Anhydroerythromycin A, erythromycin A enol ether and desmycosin were used as markers for the presence of erythromycin A and tylosin A in honey samples. The method was validated according to European Commission Decision (EC) No. 2002/657. The recoveries of analytes ranged from 85% to 111%. Repeatability and intra-laboratory reproducibility were < 20.6% and 26.8%, respectively. Decision limit (CCα) and detection capability (CCβ) ranged from 6 to 9 µg kg-1 and from 7 to 13 µg kg-1, respectively, except for streptomycin and neomycin, which showed slightly higher CCα at 25 µg kg-1 and CCβ at 34 µg kg-1. Finally, the method was applied to the honey test material 02270 through a FAPAS proficiency test (PT) for the determination of tetracyclines. PT results were obtained within a z-score range of ±2, proving that the validated method is suitable for routine analysis to ensure the quality of honey.Entities:
Keywords: LC-MS/MS; Multi-class analysis; honey; validation; veterinary drugs
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Year: 2016 PMID: 27601204 DOI: 10.1080/19440049.2016.1232491
Source DB: PubMed Journal: Food Addit Contam Part A Chem Anal Control Expo Risk Assess ISSN: 1944-0057