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European-wide GMO-monitoring data management and analysis

Zugehörigkeit
BioMath GmbH, Rostock, Germany
Schmidt, K.;
GND
141232439
Zugehörigkeit
Federal Biological Research Centre for Agriculture and Forestry (BBA), Institute for Plant Virology, Microbiology and Biosafety, Brunswick, Germany
Schiemann, Joachim;
GND
1058993402
Zugehörigkeit
Federal Biological Research Centre for Agriculture and Forestry (BBA), Institute for Plant Virology, Microbiology and Biosafety, Brunswick, Germany
Wilhelm, Ralf

SinceGMOmonitoring is an European challenge, data from different observation systems and different cultivation areas must be managed and analysed in a centralised way. Wellfounded statistics that powerfully can analyse monitoring data for possible adverse effects of GMO cultivation needs precise definitions of monitoring characters and quantifications of such effects. Whereas today the fundamental concept for GMO monitoring seems to be clear (identification of protection goals, derivation of monitoring characters, analysis of these characters for adverse effects) the kind of gathering data, especially the use of existing networks, and therefore the amount of monitoring characters and their handling is still controversial. Of course GMO monitoring should take place where GMOs are cultivated. Therefore the network of monitoring locations is settled by cultivation areas. As a basic tool for GMO monitoring farm questionnaires have been established. Data gathered on monitoring characters for protection goals in the agro ecosystem build the fundamental database for the analyses on possible adverse effects. Additional information on characters which may be not provided by this tool can be gathered by existing environmental observation networks which were established to act as continuous and comprehensive reporting sys- ACHTUNGTRENUNGtems and therefore to survey and analyse environmental data. Considering the data management and analysis, each observation system has its own, but similar structure: monitoring characters are surveyed and analysed for trends or significant differences. While the data from farm questionnaires are clearly analysed for a GMO effect, the existing networks report on trends in general – where the causes for unusual or adverse trends – may even be unknown. A practical GMO monitoring therefore should use these sys- ACHTUNGTRENUNGtems by checking the reports on unusual trends for their possible connection to GMO cultivation. This can only be done by linking their data to the data gathered from cultivation sites, and therefore to the basic monitoring database – i. e. the data being surveyed by farm questionnaires. The data management systems and possible intersection points of farm questionnaires and other existing networks will be presented. A proposal for the organisation of a European-wide monitoring will be given.

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