Nowadays most animal feed products imported into Europe have a GMO (genetically modified organism) label. This means that they contain European Union (EU)-authorized GMOs. For enforcement of these labeling requirements, it is necessary, with the rising number of EU-authorized GMOs, to perform an increasing number of analyses. In addition to this, it is necessary to test products for the potential presence of EU-unauthorized GMOs. Analysis for EU-authorized and -unauthorized GMOs in animal feed has thus become laborious and expensive. Initial screening steps may reduce the number of GMO identification methods that need to be applied, but with the increasing diversity also screening with GMO elements has become more complex. For the present study, the application of an informative detailed 24-element screening and subsequent identification strategy was applied in 50 animal feed samples. Almost all feed samples were labeled as containing GMO-derived materials. The main goal of the study was therefore to investigate if a detailed screening strategy would reduce the number of subsequent identification analyses. An additional goal was to test the samples in this way for the potential presence of EU-unauthorized GMOs. Finally, to test the robustness of the approach, eight of the samples were tested in a concise interlaboratory study. No significant differences were found between the results of the two laboratories.

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In most countries, systems are in place to analyse food products for the potential presence of genetically modified organisms (GMOs), to enforce labelling requirements and to screen for the potential presence of unauthorised GMOs. With the growing number of GMOs on the world market, a larger diversity of methods is required for informative analyses. In this paper, the specificity of an extended screening set consisting of 32 screening methods to identify different crop species (endogenous genes) and GMO elements was verified against 59 different GMO reference materials. In addition, a cost- and time-efficient strategy for DNA isolation, screening and identification is presented. A module for semiautomated analysis of the screening results and planning of subsequent event-specific tests for identification has been developed. The Excel-based module contains information on the experimentally verified specificity of the element methods and of the EU authorisation status of the GMO events. If a detected GMO element cannot be explained by any of the events as identified in the same sample, this may indicate the presence of an unknown unauthorised GMO that may not yet have been assessed for its safety for humans, animals or the environment.Electronic supplementary materialThe online version of this article (doi:10.1007/s00216-017-0333-7) contains supplementary material, which is available to authorized users.

To improve the efficacy of the in-house validation of GMO detection methods (DNA isolation and real-time PCR, polymerase chain reaction), a study was performed to gain insight in the contribution of the different steps of the GMO detection method to the repeatability and in-house reproducibility. In the present study, 19 methods for (GM) soy, maize canola and potato were validated in-house of which 14 on the basis of an 8-day validation scheme using eight different samples and five on the basis of a more concise validation protocol. In this way, data was obtained with respect to the detection limit, accuracy and precision. Also, decision limits were calculated for declaring non-conformance (>0.9%) with 95% reliability. In order to estimate the contribution of the different steps in the GMO analysis to the total variation variance components were estimated using REML (residual maximum likelihood method). From these components, relative standard deviations for repeatability and reproducibility (RSDr and RSDR) were calculated. The results showed that not only the PCR reaction but also the factors ‘DNA isolation’ and ‘PCR day’ are important factors for the total variance and should therefore be included in the in-house validation. It is proposed to use a statistical model to estimate these factors from a large dataset of initial validations so that for similar GMO methods in the future, only the PCR step needs to be validated. The resulting data are discussed in the light of agreed European criteria for qualified GMO detection methods.Electronic supplementary materialThe online version of this article (doi:10.1007/s00216-009-3315-6) contains supplementary material, which is available to authorized users.