European Food Research and Technology

, Volume 224, Issue 1, pp 129–139

Kernel lot distribution assessment (KeLDA): a study on the distribution of GMO in large soybean shipments

  • Claudia Paoletti
  • Andreas Heissenberger
  • Marco Mazzara
  • Sara Larcher
  • Emanuele Grazioli
  • Philippe Corbisier
  • Norbert Hess
  • Gilbert Berben
  • Peter S. Lübeck
  • Marc De Loose
  • Gillian Moran
  • Christine Henry
  • Carlo Brera
  • Imma Folch
  • Jaroslava Ovesna
  • Guy Van den Eede
Original Paper

DOI: 10.1007/s00217-006-0299-8

Cite this article as:
Paoletti, C., Heissenberger, A., Mazzara, M. et al. Eur Food Res Technol (2006) 224: 129. doi:10.1007/s00217-006-0299-8

Abstract

The reliability of analytical testing is strongly affected by sampling uncertainty. Sampling is always a source of error and the aim of “good” sampling practice is to minimize this error. Generally the distribution of genetically modified (GM) material within lots is assumed to be random in order to use binomial distribution to make inferences. This assumption was never verified in practice and no experimental data investigating the distribution of genetically modified organisms (GMOs) exist. The objectives of the KeLDA project were: (1) to assess the distribution of GM material in soybean lots (2) to estimate the amount of variability of distribution patterns among lots. The GM content of 15 soybean lots imported into the EU was estimated (using real-time PCR methodology) analyzing 100 increment samples systematically sampled from each lot at predetermined time intervals during the whole period of off-loading. The distribution of GM material was inferred by the one-dimensional (temporal) distribution of contaminated increments. All the lots display significant spatial structuring, indicating that randomness cannot be assumed a priori. The evidence that the distribution of GM material is heterogeneous highlights the need to develop sampling protocols based on statistical models free of distribution requirements.

Keywords

Sampling Bulk commodities Spatial autocorrelation Heterogeneity Soybean GMOs 

Copyright information

© Springer-Verlag 2006

Authors and Affiliations

  • Claudia Paoletti
    • 1
    • 13
  • Andreas Heissenberger
    • 2
  • Marco Mazzara
    • 1
  • Sara Larcher
    • 1
  • Emanuele Grazioli
    • 1
  • Philippe Corbisier
    • 3
  • Norbert Hess
    • 4
  • Gilbert Berben
    • 5
  • Peter S. Lübeck
    • 6
  • Marc De Loose
    • 7
  • Gillian Moran
    • 8
  • Christine Henry
    • 9
  • Carlo Brera
    • 10
  • Imma Folch
    • 11
  • Jaroslava Ovesna
    • 12
  • Guy Van den Eede
    • 1
  1. 1.European Commission, Joint Research Centre, Institute for Health and Consumer Protection (IHCP)Biotechnology and GMOs UnitIspra (VA)Italy
  2. 2.Umweltbundesamt GmbHWienAustria
  3. 3.European Commission, Joint Research CentreInstitute for Reference Materials and Measurements (IRMM)GeelBelgium
  4. 4.Behörde für Umwelt und GesundheitHamburgGermany
  5. 5.The Walloon Agricultural Research Centre (CRA-W)Department Quality of Agricultural ProductsGemblouxBelgium
  6. 6.Ministry of Food, Agriculture and FisheriesThe Danish Plant DirectorateLyngbyDenmark
  7. 7.CLO/DVPMelleBelgium
  8. 8.Scottish Agricultural Science AgencyEdinburghUK
  9. 9.Central Science LaboratorySand HuttonUK
  10. 10.Italian National Institute for Health, National Centre for Food Quality and Risk AssessmentGMO and Mycotoxin UnitRomeItaly
  11. 11.IRTA GenBarcelonaSpain
  12. 12.Research Institute of Crop ProductionRuzyneCzech Republic
  13. 13.European Food Safety Authority (EFSA)ParmaItaly

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