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.
Analytical and Bioanalytical Chemistry, 2014, Vol 406, Issue 12, p. 2885-2897
HASH(0x2a8ffa8); Conventional agriculture; Long-term field trial; Metabolomics; Organic agriculture; White cabbage; Long-termfield trial; Organic agriculture .White cabbage; NUTRITIONAL QUALITY; LATENT STRUCTURES; PLANT FOODS; AUTHENTICATION; PROJECTIONS; BIOMARKERS; DATABASE; PRODUCTS; WORKFLOW; SYSTEMS; conventional agriculture; ling-term field trial; metabolomics; organic agriculture; white cabbage