Quantification of the percentage proportion of individual animal species in meat products by multiplex qPCR and digital PCR

0576045 - ÚŽFG 2024 RIV NL eng J - Journal Article
Nesvadbová, M. - Dziedzinská, Radka - Hulánkova, R. - Babák, V. - Králík, Petr
Quantification of the percentage proportion of individual animal species in meat products by multiplex qPCR and digital PCR.
Food Control. Roč. 154, DEC (2023), č. článku 110024. ISSN 0956-7135. E-ISSN 1873-7129
Institutional support: RVO:67985904
Keywords : qPCR * Quantification * Meat species content
OECD category: Food and beverages
Impact factor: 6, year: 2022
Method of publishing: Limited access
https://asep.lib.cas.cz/arl-cav/cs/csg/?repo=crepo1&key=48941820897

Determining the composition of food and verifying the manufacturer's declaration continues to represent a methodological challenge. Various methods based on the analysis of proteins (peptides), chemical examination or even DNA detection fail to analyze a complex sample composed of more than one species. Since manufacturers declare the composition of products in percentage weight, the problem for all analytical methods is to determine the 100% muscle and fat tissues containing different amounts of DNA, as water or ice do not contain any DNA. The aim of this study was, therefore, to investigate the possibility of quantifying the percentage of the dominant meat species (pork, chicken and beef) in samples of 2- and 3-component mixtures and in meat products. Two different calculation methods were applied to qPCR and it was shown that a calibration curve is not necessarily required for composition evaluation. Comparison of qPCR and ddPCR showed that these two methods provide comparable data with a low level of discrepancy. The data obtained by qPCR and ddPCR were compared with each other and with the theoretical number of genomic copies. The study showed that the percentage of meat constituents in products with high muscle content can be quantified with high confidence even without taking the heat treatment into account. It was, however, shown that fat can negatively affect the calculation of component proportions and complicate the interpretation of the data.
Permanent Link: https://hdl.handle.net/11104/0345942