AMIGA partners released a new paper on a simulation model for field testing
AMIGA partners Paul W. Goedhart (Wageningen University, The Netherlands), Hilko van der Voet (DLO Research Institute, The Netherlands) Ferdinando Baldacchino and Salvatore Arpaia (ENEA, Italy) have jointly developed the paper “A statistical simulation model for field testing of non-target organisms in of genetically modified plants”, which has been released on the Ecology and Evolution Section of the Wiley Online Library on March, 14 2014. After more than one year and a half of intense research activity within the project, AMIGA researchers gathered data on the potential impacts and adverse effects that genetic modification can have on the environment. The paper describes a general framework for simulating data that is typically found in environmental risk assessment of genetically modified plants, to show how this can be used in the design of field experiments. Research activities on those issues, are increasingly drawing the attention of national bodies and European agencies to the benefits and risks of genetically modified plants (GMPs). This is the main reason why EFSA (European Food Safety Authority) require comparative safety assessments, which can make a comparison between the genetically modified plant and its conventional counterpart. The EU-funded project “Assessing and Monitoring the Impacts of Genetically modified plants on Agro-ecosystems” (AMIGA) includes as one of its main objectives the elaboration of statistically well-based protocols for the design and analysis of field trials. To prepare this action, an inventory of existing field studies in the literature was created, as well as a statistical simulation model developed to mimic ecological data, such as those found in practice. This simulation model can be used to generate count data having different statistical distributions (possibly with excess-zeroes). With this tool, researchers can simulate single or multiple trials across different environments, and enable genotype by environment interaction, by means of adding random variety effects. Finally, the simulation model allows researchers to include repeated measures in time, following a constant, linear or quadratic pattern, possibly with some form of autocorrelation. Moreover, the model makes it possible to add a set of reference varieties to the GM plants and its comparator to assess the natural variation which can then be used to set limits of concern for equivalence testing. To access the full paper, please click here: http://onlinelibrary.wiley.com/doi/10.1002/ece3.1019/full(opens in new window)
Countries
Austria, Belgium, Bulgaria, Cyprus, Czechia, Germany, Denmark, Estonia, Greece, Spain, Finland, France, Hungary, Ireland, Italy, Lithuania, Luxembourg, Latvia, Malta, Netherlands, Poland, Portugal, Romania, Sweden, Slovenia, United Kingdom