Abstract
The influence of organic and conventional farming practices on the content of single nutrients in plants is disputed in the scientific literature. Here, large-scale untargeted LC-MS-based metabolomics was used to compare the composition of white cabbage from organic and conventional agriculture, measuring 1,600 compounds. Cabbage was sampled in 2 years from one conventional and two organic farming systems in a rigidly controlled long-term field trial in Denmark. Using Orthogonal Projection to Latent Structures–Discriminant Analysis (OPLS-DA), we found that the production system leaves a significant (p = 0.013) imprint in the white cabbage metabolome that is retained between production years. We externally validated this finding by predicting the production system of samples from one year using a classification model built on samples from the other year, with a correct classification in 83 % of cases. Thus, it was concluded that the investigated conventional and organic management practices have a systematic impact on the metabolome of white cabbage. This emphasizes the potential of untargeted metabolomics for authenticity testing of organic plant products.Electronic supplementary materialThe online version of this article (doi:10.1007/s00216-014-7704-0) contains supplementary material, which is available to authorized users.
Highlights
ObjectivesThe objective of this study was to explore the effect of organic and conventional growing conditions on the overall chemical composition of a crop using non-targeted metabolomics
Organic agriculture, in contrast to its conventional counterpart, does by regulation not make use of synthetically produced fertilizers and pesticides
The production of white cabbage samples was managed according to the best practice within organic or conventional plant production and, in the case of the O1 and O2 samples, in full compliance with the European Union guidelines for organic farming [20, 19]
Summary
The objective of this study was to explore the effect of organic and conventional growing conditions on the overall chemical composition of a crop using non-targeted metabolomics. The main objective of this work was to investigate the effect of the agricultural production system on the metabolome of the crop. As the main objective of this work was the investigation of metabolome-wide differences rather than the isolation of individual biomarkers, we did not focus on providing further compound identification at this point. A more conservative approach appears unnecessary here because our aim was not the discovery of individual biomarkers for organic or conventional production
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