Detection of Antibiotic Residues in Blossom Honeys from Different Regions in Turkey by LC-MS/MS Method

Abstract

In the present study, a total of 80 commercial blossom honey samples were obtained from local markets in Ankara, Turkey. These honeys were analyzed for 35 important and risky antibiotics (sulfonamide, tetracycline, macrolide, cephalosporin, aminoglycoside, quinolone, nitrofuran, chloramphenicol, and anthelmintic groups) by the LC-MS/MS multi-antibiotic method. In addition to these analyses, pH measure, moisture, and electrical conductivity were determined in these honey samples. Finally, seven out of 35 antibiotic residues investigated in the honeys were positive. The most frequently detected antibiotics in the analyzed samples were dihydrostreptomycin, streptomycin, erythromycin, sulfadimidine (sulfamethazine), and enrofloxacin as 58.75%, 22.5%, 13.75%, 10%, and 2.5%, respectively. Tetracycline and doxycycline were detected in only one sample. The pH, moisture, and electrical conductivity values of the honey samples were determined as between pH 3.78 and 5.41, 17.48 and 18.03%, and 0.25 and 0.47 mS/cm, respectively. In terms of food safety and human health, it is very important to monitor the residues of these pharmacologically active substances with analytical methods.

Detection of Multiple Antibiotic Residues in Turkish Pine and Blossom Honeys Using LC–MS/MS Method

“…In our study, among the 8 pine honey samples, sulfadimidine antibiotic was found in one sample (I‐pine) at the amount of 16.82 μg/kg. Er Demirhan & Demirhan [23] reported the determination of 35 antibiotic residues in 80 commercial blossom honey samples produced in Turkey using the LC‐MS/MS system. In this study, antibiotic residues were found in 35 samples within the detection limits.…”

“…The sample preparation protocol applied to honey samples for the determination of antibiotic residues was validated according to manufacturer guidelines Jasem [22] and Er Demirhan & Demirhan [23] . This protocol provided simple and quick sample preparation which does not require the use of solid phase extraction (SPE) and immunoaffinity columns.…”

“…The sample preparation protocol applied to honey samples for the determination of antibiotic residues was validated according to manufacturer guidelines Jasem [22] and Er Demirhan & Demirhan. [23] This protocol provided simple and quick sample preparation which does not require the use of solid phase extraction (SPE) and immunoaffinity columns. Sample preparation for honey was done as follows; 5 g honey sample was weighted into a 50 ml centrifuge tube, and 40 μl (10 μg/ml) sulfameter internal standard working solution (Sigma-Aldrich) was added.…”

The preparation of hybrid silicon quantum dots by one-step synthesis for tetracycline detection and antibacterial applications

“…34,35 In addition, the overuse of antibiotics leads to increased bacterial resistance, which in turn poses a threat to human health. Although there are many analytical methods for antibiotic detection, such as high-performance liquid chromatography (HPLC), 36,37 liquid chromatography-tandem mass spectrometry (LC-MS), 38,39 enzyme-linked immunoassay, 40,41 colorimetric analysis 42,43 and electrochemical detection, [44][45][46] these methods are costly and need complex procedures, time-consuming sample pretreatment, professional operation and high instrument maintenance costs. Therefore, the development and establishment of simple, economical, rapid, and sensitive TC essays are crucial.…”

High-Sensitive FAM Labeled Aptasensor Based on Fe3O4/Au/g-C3N4 for the Detection of Sulfamethazine in Food Matrix

“…The European Union, the United States, and China have established maximum residue limits of 100 μg/kg SMZ [ 4 , 5 ]. In previous studies, researchers have used numerous methods for the detection and quantification of SMZ, including liquid chromatography–mass spectrometry (LC–MS), high-performance liquid chromatography (HPLC), and the enzyme-linked immunosorbent assay (ELISA) [ 6 , 7 , 8 ]. Although LC–MS and HPLC are sensitive and highly specific for SMZ, they require complicated operations and are not suitable for detection in large numbers of samples [ 9 ].…”