LC-QTOF-MS evaluation of rabbit-specific peptide markers for meat quantitation

 

Authors

Anna Stachniuk, Department of Bioanalytics, Medical University of LublinFollow
Anna Kozub, Department of Bioanalytics, Medical University of Lublin, ul. Jaczewskiego 8b, 20-090 Lublin, Poland
Renata Czeczko, Department of Chemistry, University of Live Sciences in Lublin, ul. Akademicka 15, 20-950 Lublin, Poland
Magdalena Montowska, Department of Meat Technology, Poznań University of Life Sciences, ul. Wojska Polskiego 31, 60-624 Poznań, Poland
Emilia Fornal, Department of Bioanalytics, Medical University of Lublin, ul. Jaczewskiego 8b, 20-090 Lublin, Poland

Abstract

Ten rabbit-specific tryptic peptide markers and one marker peptide specific to both rabbit and hare were evaluated for mass signal linearity in binary meat mixtures using liquid chromatography-quadrupole time-of-flight-mass spectrometry. Seven meat mixtures containing chicken and varying percentages of rabbit (1%, 5%, 10%, 30%, 60%, 90%, and 100%) were analyzed. Additionally, the signal linearity of twelve peptide markers for chicken meat was examined. The best candidate peptides for the quantification of meat content were selected. Five of eleven peptides for rabbit meat and five of twelve peptides for chicken meat showed good linearity (R2 > 0.97). The limits of detection and limits of quantification for these markers were in the range of 0.43–1.91% [w/w] and 1.44–6.38 % [w/w], respectively. The method allowed determination of the percentage content of rabbit and chicken meat in two- and three-component meat mixtures with good accuracy. The preliminary quantification data provide a starting point for developing label-free and absolute quantification methods for rabbit and chicken meat using multiple reaction monitoring of peptide markers.

Recommended Citation

Stachniuk, Anna; Kozub, Anna; Czeczko, Renata; Montowska, Magdalena; and Fornal, Emilia (2022) "LC-QTOF-MS evaluation of rabbit-specific peptide markers for meat quantitation," Journal of Food and Drug Analysis: Vol. 30 : Iss. 2 , Article 4.
Available at: https://doi.org/10.38212/2224-6614.3403

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