Title: Kernel Lot Distribution Assessment (KeLDA): a Study on the Distribution of GMO in Large Soybean Shipments
Authors: PAOLETTI ClaudiaHEISSENBERGER AndreasMAZZARA MARCOLARCHER SARAGRAZIOLI EMANUELECORBISIER PHILIPPEBERBEN GilbertLÜBECK Peter S.DE LOOSE MarcMORAN GillianHENRY ChristineBRERA CarloFOLCH ImmaOVESNA JaroslavaVAN DEN EEDE GUYHESS Norbert
Citation: European Food Research and Technology vol. 224 p. 129-139
Publisher: SPRINGER
Publication Year: 2006
JRC Publication N°: JRC33379
URI: http://publications.jrc.ec.europa.eu/repository/handle/JRC33379
Type: Articles in Journals
Abstract: Reliability of analytical testing is strongly affected by sampling uncertainty. Sampling os always a source of error and aim of "good" sampling practice is to minimize this error. Generally the distribution of 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 GMOs exist. Objectives of the KeLDA projects are: 1) assess the distribution of GM material in soybean lots 2) estimate the amount of variability of distribution patterns among lots. The GM content of 15 soybean lots imported in the EU was estimated (using real-time PCR methodology) analyzing 100 increments systematically sampled from each lot. 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 GM material distribution is heterogenous highlights the need to develop sampling protocols based on statistical models free of distribution requirements.
JRC Institute:Institute for Reference Materials and Measurements

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