Animal Bioscience

  • 제34권9호
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  • Pages.1532-1543
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  • 2021
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  • 2765-0189(pISSN)
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  • 2765-0235(eISSN)
아세아태평양축산학회 (Asian Australasian Association of Animal Production Societies)
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A quantitative method for detecting meat contamination based on specific polypeptides

  • Feng, Chaoyan (Key Laboratory of Meat Processing and Quality Control, MOE, Key Laboratory of Meat Processing, MARA, Jiangsu Collaborative Innovation Center of Meat Production and Processing, Quality and Safety Control, College of Food Science and Technology, Nanjing Agricultural University) ;
  • Xu, Daokun (Nanjing institute for Food and Drug Supervision and Inspection) ;
  • Liu, Zhen (Nanjing institute for Food and Drug Supervision and Inspection) ;
  • Hu, Wenyan (Nanjing institute for Food and Drug Supervision and Inspection) ;
  • Yang, Jun (Nanjing institute for Food and Drug Supervision and Inspection) ;
  • Li, Chunbao (Key Laboratory of Meat Processing and Quality Control, MOE, Key Laboratory of Meat Processing, MARA, Jiangsu Collaborative Innovation Center of Meat Production and Processing, Quality and Safety Control, College of Food Science and Technology, Nanjing Agricultural University)
  • 투고 : 2020.09.03
  • 심사 : 2020.11.14
  • 발행 : 2021.09.01
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초록

Objective: This study was aimed to establish a quantitative detection method for meat contamination based on specific polypeptides. Methods: Thermally stable peptides with good responses were screened by high resolution liquid chromatography tandem mass spectrometry. Standard curves of specific polypeptide were established by triple quadrupole mass spectrometry. Finally, the adulteration of commercial samples was detected according to the standard curve. Results: Fifteen thermally stable peptides with good responses were screened. The selected specific peptides can be detected stably in raw meat and deep processed meat with the detection limit up to 1% and have a good linear relationship with the corresponding muscle composition. Conclusion: This method can be effectively used for quantitative analysis of commercial samples.

키워드

과제정보

This study was funded by BE2016624 and CARS-35.

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