2020
DOI: 10.5219/1317
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Comparison of heat-stable peptides using a multiple-reaction monitoring method to identify beef muscle tissue

Abstract: Nowadays, proteomics is widely used as an analytical control method. A new method for determining animal tissue species-specificity based on a combination of two effective methods of food analysis, liquid chromatography (LC) and mass spectrometry (MS), was used in this work. Using this approach, it became possible to detect peptides. This work presents a comparison of species-specific, heat-stable peptides for the identification of beef. The objects of the study were native and boiled model mixtures containing… Show more

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Cited by 5 publications
(3 citation statements)
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“…The peptides were totally extracted within the range of 0.17-0.23% of the total sample. The highest content of free peptides was noted in the HH product (0.23%), which is explained by the partial destruction of proteins and the formation of new peptide sequences due to the conditions of the canning food technology (the cans are sterilized at a temperature of 115 °C -as described [17]). The rate of peptides extraction from aortas without heat treatment was equal to 0.17-0.18%.…”
Section: Analysis Of the Peptide Fraction In The Samplesmentioning
confidence: 99%
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“…The peptides were totally extracted within the range of 0.17-0.23% of the total sample. The highest content of free peptides was noted in the HH product (0.23%), which is explained by the partial destruction of proteins and the formation of new peptide sequences due to the conditions of the canning food technology (the cans are sterilized at a temperature of 115 °C -as described [17]). The rate of peptides extraction from aortas without heat treatment was equal to 0.17-0.18%.…”
Section: Analysis Of the Peptide Fraction In The Samplesmentioning
confidence: 99%
“…Proteins were extracted from the samples and digested with trypsin based on previously published studies [17]. Peptide mixtures were analyzed by LC-MS with a threequadrupole mass spectrometer (6410, Agilent Technologies, Santa Clara, California, USA) [23].…”
Section: Selection Of Marker Peptides With the Help Of Lc-ms/msmentioning
confidence: 99%
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