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DOI: https://doi.org/10.4491/eer.2018.011
Optimization of high-performance liquid chromatography–tandem mass spectrometry for chlortetracycline using response surface analysis
Hyokwan Bae1, Hee-Suk Jung2, and Jin-Young Jung3
1Department of Civil and Environmental Engineering, Pusan National University, Busan 46241, Republic of Korea
2Plant Engineering Division, Institute for Advanced Engineering, Yongin 17180, Republic of Korea
3Department of Environmental Engineering, Yeungnam University, Gyeongsan 38541, Republic of Korea
Corresponding Author: Jin-Young Jung ,Tel: +82-53-810-2541 , Fax: +82-53-810-4624, Email: jinjung@ynu.ac.kr
Received: January 3, 2018;  Accepted: March 6, 2018.
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Chlortetracycline (CTC) is one of the most important compounds in antibiotic production, and its distribution has been widely investigated due to health and ecological concerns. This study presents systematic approach to optimize the high-performance liquid chromatography–tandem mass spectrometry for analyzing CTC in a multiple reaction monitoring mode (479  462 m/z). One-factor-at-a-time (OFAT) test with response surface analysis (RSA) was used as optimization strategies. In OFAT tests, the fragmentor voltage, collision energy, and ratio of acetonitrile in the mobile phase were selected as major factors for RSA. The experimental conditions were determined using a composite in cube design (CCD) to maximize the peak area. As a result, the partial cubic model precisely predicted the peak area response with high statistical significance. In the model, the (solvent composition) and (collision energy2) terms were statistically significant at the 0.1 α-level, while the two-way interactions of the independent variables were negligible. By analyzing the model equation, the optimum conditions were derived as 114.9 V, 15.7 eV, and 70.9% for the fragmentor voltage, collision energy, and solvent composition, respectively. The RSA, coupled with the CCD, offered a comprehensive understanding of the peak area that responds to changes in experimental conditions.
Keywords: Chlortetracycline | HPLC-MS/MS | Optimization | Response surface analysis
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