Estimation of the percentage of transgenic Bt maize in maize flour mixtures using perfusion and monolithic reversed-phase high-performance liquid chromatography and chemometric tools

The estimation of the percentage of transgenic Bt maize in maize flour mixtures has been achieved in this work by high-performance liquid chromatography using perfusion and monolithic columns and chemometric analysis. Principal component analysis allowed a preliminary study of the data structure. Th...

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Bibliographic Details
Published in:Food chemistry 2008-11, Vol.111 (2), p.483-489
Main Authors: Rodríguez-Nogales, J.M., Cifuentes, A., García, M.C., Marina, M.L.
Format: Article
Language:English
Subjects:
Bacillus thuringiensis
Biological and medical sciences
blended foods
Cereal and baking product industries
Chemometric analysis
chemometric tools
corn
corn flour
cultivars
estimation
food analysis
food composition
Food industries
Fundamental and applied biological sciences. Psychology
genetically modified foods
Maize proteins
monolithic reversed-phase high-performance liquid chromatography
Monolithic RP-HPLC
perfusion
Perfusion RP-HPLC
reversed-phase high performance liquid chromatography
Transgenic Bt maize
transgenic plants
Zea mays
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Summary:The estimation of the percentage of transgenic Bt maize in maize flour mixtures has been achieved in this work by high-performance liquid chromatography using perfusion and monolithic columns and chemometric analysis. Principal component analysis allowed a preliminary study of the data structure. Then, linear discriminant analysis was used to develop decision rules to classify samples in the established categories (percentages of transgenic Bt maize). Finally, linear regression (LR) and multivariate regression models (namely, principal component analysis regression (PCR), partial least squares regression (PLS-1), and multiple linear regression (MLR)) were assayed for the prediction of the percentages of transgenic Bt maize present in a maize flour mixture. Using the relative areas of the protein peaks, MLR provided the best models and was able to predict the percentage of transgenic Bt maize in flour mixtures with an error of ±5.3%, ±2.3%, and ±3.8% in the predictions of Aristis Bt, DKC6575, and PR33P67, respectively.
ISSN:0308-8146
1873-7072
DOI:10.1016/j.foodchem.2008.03.079