Advertisement

Duplex digital PCR for the determination of meat proportions of sausages containing meat from chicken, turkey, horse, cow, pig and sheep

  • René Köppel
  • Arthika Ganeshan
  • Stefan Weber
  • Klaus Pietsch
  • Christoph Graf
  • Rupert Hochegger
  • Kate Griffiths
  • Sabine Burkhardt
Original Paper
  • 50 Downloads

Abstract

The probability of accidental or intentional addition of another species of meat in meat products is high. Meat is expensive and in the context of food waste, it is reasonable to reduce loss of this precious material during the production. However, the line between fraud and waste reduction is thin. Minor variations, e.g., up to 1% of unexpected meat content, may be tolerated. But to distinguish between minor variations and severe deviations to the list of ingredients, analytical methods with a low measurement uncertainty are required. The recent introduction of digital PCR indicated that this new method may lead to a reduction of the measurement uncertainty. We present the measurement of proportions of beef, pork, chicken, turkey, sheep and horse meat in a cooked sausage matrix and a procedure to calculate the proportions (w/w) based on target DNA concentrations measured using droplet digital PCR. Six laboratories applied these methods and determined the w/w proportions of 20 sausage samples. It was shown that these methods in conjunction with conversion factors can be used to estimate meat proportions in mixed meat products with superior accuracy and precision compared to results generated by real-time PCR.

Keywords

Droplet digital PCR Chicken Turkey Beef Pork Horse Sheep Conversion factor 

Notes

Acknowledgements

We thank the cantonal laboratory of Zürich, the Official Food Control Authority of the Canton St. Gallen, Cantonal Office of Consumer Protection Bern. Austrian Agency for Health and Food Safety, Vienna, Austria, Chemisches und Veterinäruntersuchungsamt Freiburg, Germany and National Measurement Institute, Sindey, Australia and Berlin-Brandenburg State Laboratory (LLBB), Germany, for providing the resources for this work.

Compliance with ethical standards

Conflict of interest

The authors declare that they have no conflict of interest.

Compliance with ethics requirements

This article does not contain any studies with human or living animal subjects.

References

  1. 1.
    Swiss Food Legislation Verordnung über Lebensmittel tierischer Herkunft; 16. Dezember 2016; Art. 9 Abs. 5Google Scholar
  2. 2.
    Sawyer J, Wood C, Shanahan D, Gout S, McDowell D (2003) Real-time PCR for quantitative meat species testing. Food Control 14:579–583CrossRefGoogle Scholar
  3. 3.
    Brodmann P, Moor D (2003) Sensitive and semi-quantitative TaqMan® real-time polymerase chain reaction systems for the detection of beef (Bos taurus) and the detection of the family Mammalia in food and feed. Meat Sci 65:599–607CrossRefGoogle Scholar
  4. 4.
    Lopez-Andreo M, Lugo L, Garrido-Pertierra A, Prieto I, Puyet A (2005) Identification and quantitation of species in complex DNA mixtures by real-time polymerase chain reaction. Anal Biochem 339:73–82CrossRefGoogle Scholar
  5. 5.
    Laube I, Zagon J, Broll H (2007) Quantitative determination of commercially relevant species in foods by real-time PCR. Int J Food Sci Technol 42:336–341CrossRefGoogle Scholar
  6. 6.
    Eugster A, Ruf J, Rentsch J, Hübner P, Köppel R (2008) Quantification of beef and pork fraction in sausages by real-time PCR analysis: results of an interlaboratory trial. Eur Food Res Technol 227:17–20CrossRefGoogle Scholar
  7. 7.
    Köppel R, Ruf J, Rentsch J (2011) Multiplex real-time PCR for the detection and quantification of DNA from beef, pork, horse and sheep. Eur Food Res Technol 232:151–155CrossRefGoogle Scholar
  8. 8.
    Köppel R, Ruf J, Zimmerli F, Breitenmoser A (2008) Multiplex real-time PCR for the detection and quantification of DNA from beef, pork, chicken and turkey. European. Food Res Technol 227(4):1199–1203CrossRefGoogle Scholar
  9. 9.
    Jonker KM, Tilburg JHC, Hägele GH, De Boer E (2008) Species identification in meat products using real-time. PCR Food Addit Contam 25(5):527–533CrossRefGoogle Scholar
  10. 10.
    Köppel R, Eugster A, Ruf J, Rentsch J (2012), Quantification of meat proportions by measuring DNA contents in raw and boiled sausages using matrix adapted calibrators and multiplex real-time PCR. AOAC Int 95(2):494(6)–499(6)Google Scholar
  11. 11.
    Uhlig S, Baldauf H, Simon K, Methodenringversuch “All Meat” zum quantitativen Nachweis von DNA der Tierarten Huhn, Pute, Rind und Schwein mittels Tetraplex real-time PCR, Quodata Dresden (in preparation) Google Scholar
  12. 12.
    Uhlig S, Baldauf H, Simon K, zum quantitativen Nachweis von DNA der Tierarten Pferd, Rind, Schaf und Schwein mittels Multiplex Realtime-PCR Tetraplex-Teil “AllHorse”, Quodata Dresden (in preparation) Google Scholar
  13. 13.
    Cai Y, Li X, Lv R, Yang J, Li J, He Y, Pan L (2014) Quantitative analysis of pork and chicken products by Droplet Digital PCR BioMed Res Int 2014:6 (article ID 810209) Google Scholar
  14. 14.
    Floren C, Wiedemann I, Brenig B, Schütz E, Beck J (2015) Species identification and quantification in meat and meat products using Droplet Digital PCR (ddPCR). Food Chem 173:1054–1058CrossRefGoogle Scholar
  15. 15.
    Hanan R, Shehata J, Li S, Chen H, Redda S, Cheng N, Tabujara H, Li K, Warriner R, Hanner (2017) Droplet digital polymerase chain reaction (ddPCR) assays integrated with an internal control for quantification of bovine, porcine, chicken and turkey species in food and feed. PLoS One.  https://doi.org/10.1371/journal.pone.018 CrossRefGoogle Scholar
  16. 16.
    Qiang Wang Y, Cai Y, He L, Yang J, Li L, Pan (2018) Droplet digital PCR (ddPCR) method for the detection and quantification of goat and sheep derivatives in commercial meat products. Eur Food Res Technol 244:767–774CrossRefGoogle Scholar
  17. 17.
    Köppel R, Ganeshan A, van Velsen F, Weber S, Schmid J, Graf C, Hochegger R (2018) Digital duplex versus real time PCR for the determination of meat proportions from sausages containing pork and beef. Eur Food Res Technol.  https://doi.org/10.1007/s00217-018-3147-8 CrossRefGoogle Scholar
  18. 18.
    Siegel M, Schnur K, Boernsen B, Pietsch K, Waiblinger HU (2012) First ring trial validation of real-time PCR methods for the quantification of allergenic food ingredients. Eur Food Res Technol 235:619–630CrossRefGoogle Scholar
  19. 19.
    Gerdes L, Iwobi A, Busch U, Pecoraro S (2016) Optimization of digital droplet polymerase chain reaction for quanitifcation of genetically modified organism. Biomol Detect Quantif 7:9–20CrossRefGoogle Scholar

Copyright information

© Springer-Verlag GmbH Germany, part of Springer Nature 2019

Authors and Affiliations

  • René Köppel
    • 1
  • Arthika Ganeshan
    • 1
  • Stefan Weber
    • 2
  • Klaus Pietsch
    • 3
  • Christoph Graf
    • 4
  • Rupert Hochegger
    • 5
  • Kate Griffiths
    • 6
  • Sabine Burkhardt
    • 7
  1. 1.Official Food Control Authority of the Canton ZürichZurichSwitzerland
  2. 2.Official Food Control Authority of the Canton St. GallenSt. GallenSwitzerland
  3. 3.Chemisches und Veterinäruntersuchungsamt FreiburgFreiburgGermany
  4. 4.Official Food Control Authority of the Canton BernBernSwitzerland
  5. 5.Austrian Agency for Health and Food SafetyViennaAustria
  6. 6.National Measurement InstituteSydneyAustralia
  7. 7.Berlin-Brandenburg State Laboratory (LLBB)BerlinGermany

Personalised recommendations