Literature DB >> 20629412

Construction of measurement uncertainty profiles for quantitative analysis of genetically modified organisms based on interlaboratory validation data.

Roy Macarthur1, Max Feinberg, Yves Bertheau.   

Abstract

A method is presented for estimating the size of uncertainty associated with the measurement of products derived from genetically modified organisms (GMOs). The method is based on the uncertainty profile, which is an extension, for the estimation of uncertainty, of a recent graphical statistical tool called an accuracy profile that was developed for the validation of quantitative analytical methods. The application of uncertainty profiles as an aid to decision making and assessment of fitness for purpose is also presented. Results of the measurement of the quantity of GMOs in flour by PCR-based methods collected through a number of interlaboratory studies followed the log-normal distribution. Uncertainty profiles built using the results generally give an expected range for measurement results of 50-200% of reference concentrations for materials that contain at least 1% GMO. This range is consistent with European Network of GM Laboratories and the European Union (EU) Community Reference Laboratory validation criteria and can be used as a fitness for purpose criterion for measurement methods. The effect on the enforcement of EU labeling regulations is that, in general, an individual analytical result needs to be < 0.45% to demonstrate compliance, and > 1.8% to demonstrate noncompliance with a labeling threshold of 0.9%.

Mesh:

Year:  2010        PMID: 20629412

Source DB:  PubMed          Journal:  J AOAC Int        ISSN: 1060-3271            Impact factor:   1.913


  2 in total

1.  Data processing of qualitative results from an interlaboratory comparison for the detection of "Flavescence dorée" phytoplasma: How the use of statistics can improve the reliability of the method validation process in plant pathology.

Authors:  Aude Chabirand; Marianne Loiseau; Isabelle Renaudin; Françoise Poliakoff
Journal:  PLoS One       Date:  2017-04-06       Impact factor: 3.240

2.  Modeling gene flow distribution within conventional fields and development of a simplified sampling method to quantify adventitious GM contents in maize.

Authors:  Enric Melé; Anna Nadal; Joaquima Messeguer; Marina Melé-Messeguer; Montserrat Palaudelmàs; Gisela Peñas; Xavier Piferrer; Gemma Capellades; Joan Serra; Maria Pla
Journal:  Sci Rep       Date:  2015-11-24       Impact factor: 4.379

  2 in total

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