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Determination of eight kinds of glucocorticoids residues in chicken muscle with on-line clean up combined HPLC-MS/MS

Identyfikatory
Warianty tytułu
Języki publikacji
EN
Abstrakty
EN
A sensitive and rapid method using HPLC-MS/MS was developed for the determination of Wight glucocorticoids residues in chicken muscle simultaneously by Turbo Flow. The eight glucocorticoids were prednisone, prednisolone, hydrocortisone, methylprednisolone, dexamethasone, betamethasone, beclomethasone and fludrocortisones. Samples were extracted with ethyl acetate and on-line cleaned up through a Turbo Flow solid-phase extraction column without time-consuming pretreatment before HPLC-MS/MS analysis. Sample pretreatment conditions, Turbo Flow conditions and mass spectra parameters were optimized and obtained eight glucocorticoids calibration curves. These curves showed good linearity over the concentration from 0.2 mg/kg to 50 mg/kg with an average recovery from 71.63% to 117.36%. This method could be applied on real samples and provided simple, rapid, sensitive and highly selective analysis, which made it feasible to be adopted in food inspection organizations or carry out quantitative analysis for other banned substance.
Rocznik
Strony
267--275
Opis fizyczny
Bibliogr. 20 poz., rys., wykr.
Twórcy
autor
  • Institute of Coastal Agriculture, Hebei Academy of Agriculture and Forestry Sciences, Tangshan, 063299, China
autor
  • Hebei Saline Alkali Land Greening Technology Innovation Center, Tangshan, 063299, China
autor
  • Institute of Coastal Agriculture, Hebei Academy of Agriculture and Forestry Sciences, Tangshan, 063299, China
autor
  • Hebei Saline Alkali Land Greening Technology Innovation Center, Tangshan, 063299, China
autor
  • Hebei Saline Alkali Land Greening Technology Innovation Center, Tangshan, 063299, China
autor
  • Institute of Coastal Agriculture, Hebei Academy of Agriculture and Forestry Sciences, Tangshan, 063299, China
autor
  • Shijiazhuang Jinbiao Inspection Service Co., Ltd, Shijiazhuang, 050051, China
Bibliografia
  • 1. Jin-Zhong, X. U.; Zhang, X. Y.; Ding, T.; Bin, W. U.; Shen, C. Y.; Jiang, Y.; Liu, F. Chin. J. Anal. Chem. 2009, 37, 341–6.
  • 2. Zou, X. M.; Zhou, J. W.; Song, S. H.; Chen, G. H. Chin. J. Anal. Chem. 2019, 47, 488–99.
  • 3. Sousa-Lima, J.; Moreira, P. S.; Raposo-Lima, C.; Sousa, N.; Morgado, P. Eur. Neuropsychopharmacol. 2019, 29, 1185–98.
  • 4. Leb, A.; Djba, B. Anal. Chim. Acta 2019, 1063, 75–81.
  • 5. Seo, J.; Kim, H. Y.; Chung, B.; Hong, J. J. Chromatogr. 2005, 1067, 303–9.
  • 6. Paul, M.; Louis, J. B.; Rosen, J. D. J. AOAC Int. 2020, 82, 705–15.
  • 7. Yehia, A. M.; Arafa, R. M.; Abbas, S. S.; Amer, S. M. Chromatographia 2021, 84, 1–11.
  • 8. Fm, A.; As, B.; Fm, A.; Ms, A.; Ap, A. Arab. J. Chem. 2020, 13, 4673–80.
  • 9. Matraszek-Zuchowska, I.; Wozniak, B.; Posyniak, A. Food Anal. Method. 2017, 10, 727–39.
  • 10. Shin, H. S.; Oh, J. A. J. Sep. Sci. 2015, 35, 541–7.
  • 11. Xiong, L.; Gao, Y.-Q.; Li, W.-H.; Yang, X.-L.; Shimo, S. P. Meat Sci. 2015, 105, 96–107.
  • 12. He, S.; Wang, R.; Wei, W.; Liu, H.; Ma, Y. Int. J. Dairy Technol. 2020, 73, 357–65.
  • 13. Qin, Y.; Wang, X. B.; Wang, C.; Zhao, M.; Peng, S. Q. J. Chromatogr. B 2003, 794, 193–203.
  • 14. Tang, P. W.; Law, W. C.; Wan, T. J. Chromatogr. B Biomed. Sci. Appl. 2001, 754, 229–44.
  • 15. Lu, Z.; Kong, X.; Qiang, H.; Zhang, L.; Li, J. Se Pu 2014, 32, 559–65.
  • 16. Rocha, D. G.; Lana, M.; Augusti, R.; Faria, A. F. Food Anal. Method. 2019, 12, 1914–26.
  • 17. Chen, S. L.; Xue-Gui, W. U.; Wang, Y. C.; Wang, F. G.; Huang, X. F.; Xiao-Mei, L. I. J. Food Saf. Qual. 2019.
  • 18. Chen, L.; Wang, B.; Diao, Z.; Zhao, M.; Wang, J. Molecules (Basel, Switzerland) 2019, 24, 2652.
  • 19. Chen, D.; Liu, F.; Yang, C. Food Sci. Tech-Brazil 2014, 28, 61–2.
  • 20. Liu, K.; Kang, K.; Li, N.; An, J.; Lian, K.; Kang, W. J. AOAC Int. 2020, 103, 265–71.
Typ dokumentu
Bibliografia
Identyfikator YADDA
bwmeta1.element.baztech-ba560bda-4aba-42b6-b7eb-df9bfdb8ecd9
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