Please use this identifier to cite or link to this item: https://hdl.handle.net/2440/96714
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dc.contributor.authorMilavec, M.en
dc.contributor.authorDobnik, D.en
dc.contributor.authorYang, L.en
dc.contributor.authorZhang, D.en
dc.contributor.authorGruden, K.en
dc.contributor.authorŽel, J.en
dc.date.issued2014en
dc.identifier.citationAnalytical and Bioanalytical Chemistry, 2014; 406(26):6485-6497en
dc.identifier.issn1618-2642en
dc.identifier.issn1618-2650en
dc.identifier.urihttp://hdl.handle.net/2440/96714-
dc.description.abstractCultivation and marketing of genetically modified organisms (GMOs) have been unevenly adopted worldwide. To facilitate international trade and to provide information to consumers, labelling requirements have been set up in many countries. Quantitative real-time polymerase chain reaction (qPCR) is currently the method of choice for detection, identification and quantification of GMOs. This has been critically assessed and the requirements for the method performance have been set. Nevertheless, there are challenges that should still be highlighted, such as measuring the quantity and quality of DNA, and determining the qPCR efficiency, possible sequence mismatches, characteristics of taxon-specific genes and appropriate units of measurement, as these remain potential sources of measurement uncertainty. To overcome these problems and to cope with the continuous increase in the number and variety of GMOs, new approaches are needed. Statistical strategies of quantification have already been proposed and expanded with the development of digital PCR. The first attempts have been made to use new generation sequencing also for quantitative purposes, although accurate quantification of the contents of GMOs using this technology is still a challenge for the future, and especially for mixed samples. New approaches are needed also for the quantification of stacks, and for potential quantification of organisms produced by new plant breeding techniques.en
dc.description.statementofresponsibilityMojca Milave, David Dobnik, Litao Yang, Dabing Zhang, Kristina Gruden, Jana Želen
dc.language.isoenen
dc.publisherSpringeren
dc.rights© Springer-Verlag Berlin Heidelberg 2014en
dc.subjectGMOs; quantification; real-time PCR; digital PC; new generation sequencingen
dc.titleGMO quantification: valuable experience and insights for the futureen
dc.typeJournal articleen
dc.identifier.doi10.1007/s00216-014-8077-0en
pubs.publication-statusPublisheden
dc.identifier.orcidZhang, D. [0000-0003-3181-9812]en
Appears in Collections:Agriculture, Food and Wine publications

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