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Conference on Applied Statistics in Agriculture

2012

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Bayesian Mcmc Analyses For Regulatory Assessments Of Food Composition, Jay M. Harrison, Derek Culp, George G. Harrigan Apr 2012

Bayesian Mcmc Analyses For Regulatory Assessments Of Food Composition, Jay M. Harrison, Derek Culp, George G. Harrigan

Conference on Applied Statistics in Agriculture

In order to gain regulatory approval to market a new seed product derived with biotechnology, grain and forage composition data must be collected from field trials, and summaries must be reported to various government agencies. Currently, both tests of differences in composition between a genetically modified organism (GMO) and its control and tests of equivalence of the GMO to conventional genotypes are required by regulatory agencies. Bayesian analyses offer an attractive option for regulatory assessments by expressing results that can be interpreted more easily by a wide audience and by providing more ways to examine various hypotheses of interest. In …