Skip to main content
padlock icon - secure page this page is secure

Simulating kernel lot sampling: the effect of heterogeneity on the detection of GMO contaminations

Buy Article:

$35.00 + tax (Refund Policy)

Guidelines defining kernel sampling strategies for quality analyses have been provisionally adopted for the detection of genetically modified (GM) contamination in kernel lots. However, these guidelines are not specific for GM material detection and are not intended for the sampling of non-uniform distributions, a probable situation with respect to the presence of GM material in kernel lots. An analysis of the problem of non-random distribution, through the investigation of the effectiveness of different sampling techniques in producing representative bulk samples, is presented.

The analysis is based on a two-step modelling procedure: 1) the kernel lot is created and 2) the lot is sampled to produce a bulk sample. This allows the identification of optimal sampling techniques as a function of specific combinations of population characteristics. For each of 5 levels of GM impurity, varying between 0.1% and 2%, we investigated the effect of 5 levels of stratification (lot size=107 kernels). Our results indicate: 1) For every GM level, the higher the heterogeneity level, the more unstable the GM estimate becomes; even modest levels of stratification affect the stability of GM estimates. 2) As the number of increment samples increases, the coefficient of variation (CV) of the estimate decreases. Although the pattern of decrease remains similar across stratification levels, the estimated CV changes: with low levels of stratification, 50 samples are enough to obtain estimates with CV<10%. In the case of modest levels of stratification even 100 samples are not sufficient to maintain CV<10%. In case of strongly heterogeneous lots estimates based on 100 units have CVs around 50%. At the same time, the likelihood of false negative results increases significantly.
No Reference information available - sign in for access.
No Citation information available - sign in for access.
No Supplementary Data.
No Article Media
No Metrics

Document Type: Research Article

Publication date: October 1, 2003

More about this publication?
  • Seed Science and Technology (SST) is one of the leading international journals featuring original papers and review articles on seed quality and physiology as related to seed production, harvest, processing, sampling, storage, distribution and testing. This widely recognised journal is designed to meet the needs of researchers, advisers and all those involved in the improvement and technical control of seed quality.
  • Editorial Board
  • Information for Authors
  • Subscribe to this Title
  • Membership Information
  • Ingenta Connect is not responsible for the content or availability of external websites
  • Access Key
  • Free content
  • Partial Free content
  • New content
  • Open access content
  • Partial Open access content
  • Subscribed content
  • Partial Subscribed content
  • Free trial content
Cookie Policy
Cookie Policy
Ingenta Connect website makes use of cookies so as to keep track of data that you have filled in. I am Happy with this Find out more