Analytical and Bioanalytical Chemistry

, Volume 396, Issue 6, pp 2031–2041 | Cite as

Development of sampling approaches for the determination of the presence of genetically modified organisms at the field level

  • Jelka Šuštar-VozličEmail author
  • Katja Rostohar
  • Andrej Blejec
  • Petra Kozjak
  • Zoran Čergan
  • Vladimir Meglič
Original Paper


In order to comply with the European Union regulatory threshold for the adventitious presence of genetically modified organisms (GMOs) in food and feed, it is important to trace GMOs from the field. Appropriate sampling methods are needed to accurately predict the presence of GMOs at the field level. A 2-year field experiment with two maize varieties differing in kernel colour was conducted in Slovenia. Based on the results of data mining analyses and modelling, it was concluded that spatial relations between the donor and receptor field were the most important factors influencing the distribution of outcrossing rate (OCR) in the field. The approach for estimation fitting function parameters in the receptor (non-GM) field at two distances from the donor (GM) field (10 and 25 m) for estimation of the OCR (GMO content) in the whole receptor field was developed. Different sampling schemes were tested; a systematic random scheme in rows was proposed to be applied for sampling at the two distances for the estimation of fitting function parameters for determination of OCR. The sampling approach had already been validated with some other OCR data and was practically applied in the 2009 harvest in Poland. The developed approach can be used for determination of the GMO presence at the field level and for making appropriate labelling decisions. The importance of this approach lies in its possibility to also address other threshold levels beside the currently prescribed labelling threshold of 0.9% for food and feed.


Maize GMO Outcrossing rate Sampling Field Labelling 



The authors would like to thank Prof. Marko Debeljak of the Jožef Stefan Institute, Ljubljana, Slovenia, for assistance in data mining analyses and modelling. This work was financially supported by the European Commission through the Sixth Framework Program, Integrated Project Co-Extra (Contract No. 007158) as well as by the Slovenian Research Agency and the Slovene Ministry of Agriculture, Forestry and Food (Grant L4-7573-0401-06).


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Copyright information

© Springer-Verlag 2010

Authors and Affiliations

  • Jelka Šuštar-Vozlič
    • 1
    Email author
  • Katja Rostohar
    • 1
  • Andrej Blejec
    • 2
  • Petra Kozjak
    • 1
  • Zoran Čergan
    • 1
  • Vladimir Meglič
    • 1
  1. 1.Agricultural Institute of SloveniaLjubljanaSlovenia
  2. 2.National Institute of BiologyLjubljanaSlovenia

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