Abstract
This paper illustrates the advantages that a fuzzy-based aggregation method could bring into the validation of a multiplex method for GMO detection (DualChip® GMO kit, Eppendorf). Guidelines for validation of chemical, bio-chemical, pharmaceutical and genetic methods have been developed and ad hoc validation statistics are available and routinely used, for in-house and inter-laboratory testing, and decision-making. Fuzzy logic allows summarising the information obtained by independent validation statistics into one synthetic indicator of overall method performance. The microarray technology, introduced for simultaneous identification of multiple GMOs, poses specific validation issues (patterns of performance for a variety of GMOs at different concentrations). A fuzzy-based indicator for overall evaluation is illustrated in this paper, and applied to validation data for different genetically modified elements. Remarks were drawn on the analytical results. The fuzzy-logic based rules were shown to be applicable to improve interpretation of results and facilitate overall evaluation of the multiplex method.
Similar content being viewed by others
References
Acutis M, Trevisiol P, Confalonieri R, Bellocchi G, Grazioli E, Van den Eede G, Paoletti C (2007) AMPE: a software tool for analytical method validation. J AOAC Int 90:1432–1438
Bellocchi G, Acutis M, Fila G, Donatelli M (2002) An indicator of solar radiation model performance based on a fuzzy expert system. Agron J 94:1222–1233
Bellocchi G, Grazioli E, Acutis M, Confalonieri R, Paoletti C, Trevisiol P (2006) Application of software AMPE to evaluate the performance of GM grains detection methods. In: Fotyma M, Kamiñska B (eds) Proceedings of the 9th European Society for Agronomy Congress, 4–6 September, vol 2. Warsaw Agricultural University, Warsaw, pp 743–744
Bellocchi G, Acutis M, Paoletti C, Confalonieri R, Trevisiol P, Grazioli E, Delobel C, Savini C, Mazzara M, Van den Eede G (2008) Expanding horizons in the validation of GMO analytical methods: fuzzy-based expert systems. Food Anal Methods 2:126–135. doi:10.1007/s12161-008-9021-8
Clarke B, Rahman S (2005) A microarray analysis of wheat grain hardness. Theor Appl Genet 110:1259–1267. doi:10.1007/s00122-005-1962-3
EC (2003a) Regulation (EC) No. 1829/2003 of the European Parliament and of the Council of 22nd September 2003 on genetically modified food and feed. Off J Eur Union L 268(1)
EC (2003b) Regulation (EC) No 1830/2003 of the European Parliament and of the Council of 22nd September 2003 concerning the traceability and labelling of genetically modified organisms and the traceability of food and feed products produced from genetically modified organisms and amending Directive 2001/18/EC. Off J Eur Union L 268(24)
Engel K-H, Moreano F, Ehlert A, Busch U (2006) Quantification of DNA from genetically modified organisms in composite and processed foods. Trends Food Sci Technol 17:490–497. doi:10.1016/j.tifs.2006.04.008
Europe ILSI (2001) Novel Food Task Force in collaboration with the European Commission’s Joint Research Center (JRC) and ILSI International Food Biotechnology Committee. Method development in relation to regulatory requirements for detection of GMOs in the food chain. ILSI Europe report series. ILSI Europe, Brussels, Belgium
Green JM (1996) A practical guide to analytical method validation. Anal Chem 68:305–309
Gregersen PL, Brinch-Pedersen H, Holm PB (2005) A microarray-based comparative analysis of gene expression profiles during grain development in transgenic and wild type wheat. Transgenic Res 14:887–905. doi:10.1007/s11248-005-1526-y
Hamels S, Leimanis S, Mazzara M, Bellocchi G, Foti N, Moens W, Remacle J, Van den Eede G (2007) Microarray method for the screening of EU approved GMOs by identification of their genetic elements. Report of validation coordinated by the Community Reference Laboratory for GM Food and Feed of the Joint Research Centre, Institute for Health and Consumer Protection, Biotechnology and GMOs Unit. Available at http://biotech.jrc.it/home/docs.htm
ISO 5725 (1994) Accuracy (trueness and precision) of measurements methods and results (International Organization for Standardization, Genéve, 1994), parts 1–6
Leimanis S, Hamels S, Nazé F, Mbongolo Mbella G, Sneyers M, Hochegger R, Broll H, Roth L, Dallmann K, Micsinai A, La Paz JL, Pla M, Brünen-Nieweler C, Papazova N, Taverniers I, Hess N, Kirschneit B, Bertheau Y, Audeon C, Laval V, Busch U, Pecoraro S, Neumann K, Rösel S, van Dijk J, Kok E, Bellocchi G, Foti N, Mazzara M, Moens W, Remacle J, van Den Eede G (2008) Validation of a GMO multiplex screening assay by the use of microarray. Eur Food Res Technol 227:1621–1632. doi:10.1007/s00217-008-0886-y
Pla M, La Paz J-L, Peñas G, García N, Palaudelmàs M, Esteve T, Messeguer J, Melé E (2006) Assessment of real-time PCR based methods for quantification of pollen mediated gene flow from GM to conventional maize in a field study. Transgenic Res 15:219–228. doi:10.1007/s11248-005-4945-x
Ratola N, Barros P, Simões T, Cerdeira A, Venâncio A, Alves A (2006) Worldwide interlaboratory study on the determination of ochratoxin A in different wine type samples. Talanta 70:720–731. doi:10.1016/j.talanta.2006.05.031
Su H-S (2001) Taiwan’s GM foods labelling legislation—a review. Trends Food Sci Technol 12:465–468. doi:10.1016/S0924-2244(02)00025-0
Sugeno M (1985) An introductory survey of fuzzy control. Inf Sci 36:59–83. doi:10.1016/0020-0255(85)90026-X
Zadeh LA (1965) Fuzzy sets. Inf Contr 8:338–353. doi:10.1016/S0019-9958(65)90241-X
Zarrilli S (2005) International trade in GMOs and GM products, national and multilateral legal frameworks. United Nations Publication, New York and Geneva
Acknowledgments
This study was financially supported by the European Commission through the Integrated Project “Co-Extra”, contract 007158, under the 6th Framework Programme, priority 5, food quality and safety. This support is gratefully acknowledged. Thanks also to Laura Bonfini, Hermann Broll, Marco Mazzara, and Maddalena Querci (European Commission Joint Research Centre, Institute for Health and Consumer Protection, Ispra, Italy) for constructive criticism and suggestions.
Author information
Authors and Affiliations
Corresponding author
Rights and permissions
About this article
Cite this article
Bellocchi, G., Bertholet, V., Hamels, S. et al. Fuzzy-logic based strategy for validation of multiplex methods: example with qualitative GMO assays. Transgenic Res 19, 57–65 (2010). https://doi.org/10.1007/s11248-009-9293-9
Received:
Accepted:
Published:
Issue Date:
DOI: https://doi.org/10.1007/s11248-009-9293-9