Volume 94, Issue 13 p. 2605-2612
Research Article

Metabolite profiling on wheat grain to enable a distinction of samples from organic and conventional farming systems

Anja Bonte

Anja Bonte

Max Rubner-Institut, Schützenberg 12, 32756 Detmold, Germany

Faculty of Biology and Centre for Biotechnology, Bielefeld University, 33615 Bielefeld, Germany

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Heiko Neuweger

Heiko Neuweger

Faculty of Biology and Centre for Biotechnology, Bielefeld University, 33615 Bielefeld, Germany

Present address: Bruker Daltonik GmbH, Fahrenheitstr. 4, 28359 Bremen, Germany.Search for more papers by this author
Alexander Goesmann

Alexander Goesmann

Faculty of Biology and Centre for Biotechnology, Bielefeld University, 33615 Bielefeld, Germany

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Cécile Thonar

Cécile Thonar

Research Institute of Organic Agriculture (FiBL), 5070 Frick, Switzerland

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Paul Mäder

Paul Mäder

Research Institute of Organic Agriculture (FiBL), 5070 Frick, Switzerland

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Georg Langenkämper

Corresponding Author

Georg Langenkämper

Max Rubner-Institut, Schützenberg 12, 32756 Detmold, Germany

Correspondence to: Georg Langenkämper, Max Rubner-Institut, Schützenberg 12, 32756 Detmold, Germany. E-mail: georg.langenkaemper@mri.bund.deSearch for more papers by this author
Karsten Niehaus

Karsten Niehaus

Faculty of Biology and Centre for Biotechnology, Bielefeld University, 33615 Bielefeld, Germany

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First published: 15 January 2014
Citations: 25
This paper was given as an oral presentation at the 2nd International Conference on Organic Food Quality and Health Research, Warsaw, Poland, 5–7 June 2013.

Abstract

BACKGROUND

Identification of biomarkers capable of distinguishing organic and conventional products would be highly welcome to improve the strength of food quality assurance. Metabolite profiling was used for biomarker search in organic and conventional wheat grain (Triticum aestivum L.) of 11 different old and new bread wheat cultivars grown in the DOK system comparison trial. Metabolites were extracted using methanol and analysed by gas chromatography–mass spectrometry.

RESULTS

Altogether 48 metabolites and 245 non-identified metabolites (TAGs) were detected in the cultivar Runal. Principal component analysis showed a sample clustering according to farming systems and significant differences in peak areas between the farming systems for 10 Runal metabolites. Results obtained from all 11 cultivars indicated a greater influence of the cultivar than the farming system on metabolite concentrations. Nevertheless, a t-test on data of all cultivars still detected 5 metabolites and 11 TAGs with significant differences between the farming systems.

CONCLUSION

Based on individual cultivars, metabolite profiling showed promising results for the categorization of organic and conventional wheat. Further investigations are necessary with wheat from more growing seasons and locations before definite conclusions can be drawn concerning the feasibility to evolve a combined set of biomarkers for organically grown wheat using metabolite profiles. © 2014 Society of Chemical Industry

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