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Development of sampling approaches for the determination of the presence of genetically modified organisms at the field level.
Sustar-Vozlic, Jelka; Rostohar, Katja; Blejec, Andrej; Kozjak, Petra; Cergan, Zoran; Meglic, Vladimir.
Afiliação
  • Sustar-Vozlic J; Agricultural Institute of Slovenia, Hacquetova 17, 1000 Ljubljana, Slovenia. jelka.vozlic@kis.si
Anal Bioanal Chem ; 396(6): 2031-41, 2010 Mar.
Article em En | MEDLINE | ID: mdl-20069281
ABSTRACT
In order to comply with the European Union regulatory threshold for the adventitious presence of genetically modified organisms (GMOs) in food and feed, it is important to trace GMOs from the field. Appropriate sampling methods are needed to accurately predict the presence of GMOs at the field level. A 2-year field experiment with two maize varieties differing in kernel colour was conducted in Slovenia. Based on the results of data mining analyses and modelling, it was concluded that spatial relations between the donor and receptor field were the most important factors influencing the distribution of outcrossing rate (OCR) in the field. The approach for estimation fitting function parameters in the receptor (non-GM) field at two distances from the donor (GM) field (10 and 25 m) for estimation of the OCR (GMO content) in the whole receptor field was developed. Different sampling schemes were tested; a systematic random scheme in rows was proposed to be applied for sampling at the two distances for the estimation of fitting function parameters for determination of OCR. The sampling approach had already been validated with some other OCR data and was practically applied in the 2009 harvest in Poland. The developed approach can be used for determination of the GMO presence at the field level and for making appropriate labelling decisions. The importance of this approach lies in its possibility to also address other threshold levels beside the currently prescribed labelling threshold of 0.9% for food and feed.
Assuntos

Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Assunto principal: Bioestatística / Plantas Geneticamente Modificadas / Zea mays / Mineração de Dados Tipo de estudo: Evaluation_studies / Prognostic_studies Idioma: En Revista: Anal Bioanal Chem Ano de publicação: 2010 Tipo de documento: Article País de afiliação: Eslovênia

Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Assunto principal: Bioestatística / Plantas Geneticamente Modificadas / Zea mays / Mineração de Dados Tipo de estudo: Evaluation_studies / Prognostic_studies Idioma: En Revista: Anal Bioanal Chem Ano de publicação: 2010 Tipo de documento: Article País de afiliação: Eslovênia