Skip to main content
SpringerLink
Log in

TaqMan Probes for Plant Species Identification and Quantification in Food and Feed Traceability

  • Protocol
  • First Online:
Plant Genotyping

Part of the book series: Methods in Molecular Biology ((MIMB,volume 2638))

Abstract

In the last few years, the traceability and labeling of processed food and feeds have gained increasing importance due to the impact that mislabeling and product fraud may have on human/animal health or on the quality of final products, such as milk, cheese, and meat, as a consequence of animal dietary. The presence of contaminants or possible frauds due to the use of alternative plant materials in food and feeds can greatly impact the economy; therefore, they are becoming important targets for product certification by competent institutional services. This is especially relevant when complex matrixes are considered, in which the visual identification of the different components is quite difficult or even impossible. Despite the existence of mandatory traceability requirements for the analysis of feed/food composition addressed by European Community regulations, the labels do not always provide a sufficient guarantee about the ingredients and additive composition of those products. In this sense, the development of new methodologies that aim to assess the traceability of feed and food complex matrixes is crucial. In this chapter, a general protocol is presented for the establishment of quantitative real-time PCR-based techniques based on TaqMan assays applied to feed/food traceability, with a special focus on applications in the areas of food and feed security (e.g., for the detection of plant species involved in allergenic reactions), fraud detection (e.g., genetically modified organisms), and certification (e.g., protected denomination of origin).

This is a preview of subscription content, log in via an institution to check access.

Access this chapter

Log in via an institution
Protocol
USD 49.95
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
eBook
USD 129.00
Price excludes VAT (USA)
  • Available as EPUB and PDF
  • Read on any device
  • Instant download
  • Own it forever
Softcover Book
USD 169.99
Price excludes VAT (USA)
  • Compact, lightweight edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info
Hardcover Book
USD 249.99
Price excludes VAT (USA)
  • Durable hardcover edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info

Tax calculation will be finalised at checkout

Purchases are for personal use only

Institutional subscriptions

References

  1. Danezis GP, Tsagkaris AS, Camin F, Brusic V, Georgiou CA (2016) Food authentication: techniques, trends and emerging approaches. Trends Anal Chem 85:123–132. https://doi.org/10.1016/j.trac.2016.02.026

    Article  CAS  Google Scholar 

  2. Lopez-Calleja IM, La Cruz SD, Pegels N, Gonzalez I, Garcia T, Martin R (2013) High resolution TaqMan real-time PCR approach to detect hazelnut DNA encoding for ITS rDNA in foods. Food Chem 141:1872–1880. https://doi.org/10.1016/j.foodchem.2013.05.076

    Article  CAS  Google Scholar 

  3. Ren G, Wang Y, Ning J, Zhang Z (2020) Using near-infrared hyperspectral imaging with multiple decision tree methods to delineate black tea quality. Spectrochim Acta A Mol Biomol Spectrosc 237:118407. https://doi.org/10.1016/j.saa.2020.118407

    Article  CAS  Google Scholar 

  4. Zhang B, Jiang X, Shen F, He X, Fang Y, Hu Q (2021) Rapid screening of DON contamination in whole wheat meals by Vis/NIR spectroscopy and computer vision coupling technology. Int J Food Sci Technol 56:2588–2595. https://doi.org/10.1111/ijfs.14775

    Article  CAS  Google Scholar 

  5. Gagneten M, del Pilar BM, Rodríguez SD (2021) Evaluation of SIMCA and PLS algorithms to detect adulterants in canola oil by FT-IR. Int J Food Sci Technol 56:2596–2603. https://doi.org/10.1111/ijfs.14866

    Article  CAS  Google Scholar 

  6. Nogales-Bueno J, Feliz L, Baca-Bocanegra B, Hernández-Hierro JM, Heredia FJ, Barroso JM et al (2020) Comparative study on the use of three different near infrared spectroscopy recording methodologies for varietal discrimination of walnuts. Talanta 206:120189. https://doi.org/10.1016/j.talanta.2019.120189

    Article  CAS  Google Scholar 

  7. Milinovic J, Garcia R, Rato AE, Cabrita MJ (2019) Rapid assessment of monovarietal portuguese extra virgin olive oil’s (EVOO’s) fatty acids by fourier-transform near-infrared spectroscopy (FT-NIRS). Eur J Lipid Sci Technol 121:1800392. https://doi.org/10.1002/ejlt.201800392

    Article  CAS  Google Scholar 

  8. Liu Z, Zhang W, Zhang Y, Chen T, Shao S, Zhou L et al (2019) Assuring food safety and traceability of polished rice from different production regions in China and Southeast Asia using chemometric models. Food Control 99:1–10. https://doi.org/10.1016/j.foodcont.2018.12.011

    Article  CAS  Google Scholar 

  9. Jiménez-Morillo NT, Palma V, Garcia R, Dias CB, Cabrita MJ (2020) Combination of stable isotope analysis and chemometrics to discriminate geoclimatically and temporally the virgin olive oils from three mediterranean countries. Foods 9:9121855. https://doi.org/10.3390/foods9121855

    Article  CAS  Google Scholar 

  10. Liu H, Qin Y, Ma Q, Zhao Q, Guo X, Ma L et al (2021) Discrimination the geographical origin of Yanchi Tan Lamb with different muscle sections by stable isotopic ratios and elemental profiles. Int J Food Sci Technol 56:2604–2611. https://doi.org/10.1111/ijfs.14900

    Article  CAS  Google Scholar 

  11. Anklam E, Gadani F, Heinze P, Pijnenburg H, Van Den Eede G (2002) Analytical methods for detection and determination of genetically modified organisms in agricultural crops and plant-derived food products. Eur Food Res Technol 214:3–26. https://doi.org/10.1007/s002170100415

    Article  CAS  Google Scholar 

  12. Braglia L, Gianì S, Breviario D, Gavazzi F, Mastromauro F, Morello L (2016) Development and validation of the modular Feed-code method for qualitative and quantitative determination of feed botanical composition. Anal Bioanal Chem 408:8299–8316. https://doi.org/10.1007/s00216-016-9943-8

    Article  CAS  Google Scholar 

  13. Braglia L, Morello L, Gavazzi F, Gianì S, Mastromauro F, Breviario D et al (2018) Interlaboratory comparison of methods determining the botanical composition of animal feed. J AOAC Int 101:227–234. https://doi.org/10.5740/jaoacint.17-0150

    Article  CAS  Google Scholar 

  14. Holzhauser T, Wangorsch A, Vieths S (2000) Polymerase chain reaction (PCR) for detection of potentially allergenic hazelnut residues in complex food matrixes. Eur Food Res Technol 211:360–365. https://doi.org/10.1007/s002170000152

    Article  CAS  Google Scholar 

  15. Herman L, de Block J, Viane R (2003) Detection of hazelnut DNA traces in chocolate by PCR. Int J Food Sci Technol 38:633–640. https://doi.org/10.1046/j.1365-2621.2003.00722.x

    Article  CAS  Google Scholar 

  16. Campos MD, Valadas V, Campos C, Morello L, Braglia L, Breviario D et al (2018) A TaqMan real-time PCR method based on alternative oxidase genes for detection of plant species in animal feed samples. PLoS One 13:0190668. https://doi.org/10.1371/journal.pone.0190668

    Article  CAS  Google Scholar 

  17. Cottenet G, Blancpain C, Sonnard V, Chuah PF (2013) Development and validation of a multiplex real-time PCR method to simultaneously detect 47 targets for the identification of genetically modified organisms. Anal Bioanal Chem 405:6831–6844. https://doi.org/10.1007/s00216-013-7125-5

    Article  CAS  Google Scholar 

  18. Marmiroli N, Maestri E (2007) Polymerase chain reaction (PCR). In: Picó Y (ed) Food toxicants analysis: techniques, strategies and developments. Elsevier BV, Amstardam et al, pp 147–187. https://doi.org/10.1016/B978-044452843-8/50007-9

    Chapter  Google Scholar 

  19. Campos MD, Patanita M, Campos C, Materatski P, Varanda CMR, Brito I et al (2019) Detection and quantification of Fusarium spp. (F. oxysporum, F. verticillioides, F. graminearum) and Magnaporthiopsis maydis in maize using real-time PCR targeting the ITS region. Agronomy 9:9020045. https://doi.org/10.3390/agronomy9020045

    Article  CAS  Google Scholar 

  20. Ribeiro JA, Albuquerque A, Materatski P, Patanita M, Varanda CMR, Félix MDR et al (2022) Tomato response to Fusarium spp. infection under field conditions: study of potential genes involved. Horticulturae 8:8050433. https://doi.org/10.3390/horticulturae8050433

    Article  Google Scholar 

  21. Espy MJ, Uhl JR, Sloan LM, Buckwalter SP, Jones MF, Vetter EA et al (2006) Real-time PCR in clinical microbiology: applications for routine laboratory testing. Clin Microbiol Rev 19:165–256. https://doi.org/10.1128/CMR.00022-06

    Article  CAS  Google Scholar 

  22. Johnson G, Nolan T, Bustin SA (2013) Real-time quantitative PCR, pathogen detection and MIQE. In: Wilks M (ed) PCR detection of microbial pathogens, Methods in molecular biology, vol 943. Humana, Totowa, pp 1–16. https://doi.org/10.1007/978-1-60327-353-4_1

    Chapter  Google Scholar 

  23. Cardoso HG, Nogales A, Frederico AM, Svensson JT, Macedo ES, Valadas V et al (2015) Natural AOX gene diversity. In: Gupta KJ, Mur LAJ, Neelwarne B (eds) Alternative respiratory pathways in higher plants. Wiley Blackwell, West Sussex, pp 241–254

    Google Scholar 

  24. Cardoso H, Campos MD, Nothnagel T, Arnholdt-Schmitt B (2011) Polymorphisms in intron 1 of carrot AOX2b-a useful tool to develop a functional marker? Plant Genet Resour 9:177–180. https://doi.org/10.1017/S1479262111000591

    Article  CAS  Google Scholar 

  25. Kutyavin IV, Afonina IA, Mills A, Gorn VV, Lukhtanov EA, Belousov ES et al (2000) 3′-minor groove binder-DNA probes increase sequence specificity at PCR extension temperatures. Nucleic Acids Res 28:655–661. https://doi.org/10.1093/nar/28.2.655

    Article  CAS  Google Scholar 

  26. Birnboim HC, Doly J (1979) A rapid alkaline extraction procedure for screening recombinant plasmid DNA. Nucleic Acids Res 7:1513–1523. https://doi.org/10.1093/nar/7.6.1513

    Article  CAS  Google Scholar 

  27. Broeders S, Huber I, Grohmann L, Berben G, Taverniers I, Mazzara M et al (2014) Guidelines for validation of qualitative real-time PCR methods. Trends Food Sci Technol 37:115–126. https://doi.org/10.1016/j.tifs.2014.03.008

    Article  CAS  Google Scholar 

  28. Cardoso H, Campos MD, Costa AR, Campos MC, Nothnagel T, Arnholdt-Schmitt B (2009) Carrot alternative oxidase gene AOX2a demonstrates allelic and genotypic polymorphisms in intron 3. Physiol Plant. https://doi.org/10.1111/j.1399-3054.2009.01299.x

  29. Nogales A, Nobre T, Cardoso HG, Muñoz-Sanhueza L, Valadas V, Campos MD et al (2016) Allelic variation on DcAOX1 gene in carrot (Daucus carota L.): an interesting simple sequence repeat in a highly variable intron. Plant Gene 5:49–55. https://doi.org/10.1016/j.plgene.2015.11.001

    Article  CAS  Google Scholar 

Download references

Acknowledgments

This work was supported by EU funds through the FP7-SME program [THEME (SME-2012-2)] under the Project Feed-Code (grant agreement 315464) and national funds through FCT under the Project UIDB/05183/2020.

Author information

Authors and Affiliations

  1. MED-Mediterranean Institute for Agriculture, Environment and Development & CHANGE-Global Change and Sustainability Institute, Institute for Advanced Studies and Research, Universidade de Évora, Evora, Portugal

    Maria Doroteia Campos, Catarina Campos & Hélia Cardoso

Authors
  1. Maria Doroteia Campos
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Catarina Campos
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. Hélia Cardoso
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to Hélia Cardoso .

Editor information

Editors and Affiliations

  1. College of Science and Engineering, Biological Sciences, Flinders University, Adelaide, SA, Australia

    Yuri Shavrukov

Rights and permissions

Reprints and permissions

Copyright information

© 2023 The Author(s), under exclusive license to Springer Science+Business Media, LLC, part of Springer Nature

About this protocol

Check for updates. Verify currency and authenticity via CrossMark

Cite this protocol

Campos, M.D., Campos, C., Cardoso, H. (2023). TaqMan Probes for Plant Species Identification and Quantification in Food and Feed Traceability. In: Shavrukov, Y. (eds) Plant Genotyping. Methods in Molecular Biology, vol 2638. Humana, New York, NY. https://doi.org/10.1007/978-1-0716-3024-2_21

Download citation

  • DOI: https://doi.org/10.1007/978-1-0716-3024-2_21

  • Published:

  • Publisher Name: Humana, New York, NY

  • Print ISBN: 978-1-0716-3023-5

  • Online ISBN: 978-1-0716-3024-2

  • eBook Packages: Springer Protocols

Publish with us

Policies and ethics

Search

Navigation