Butia spp. (Arecaceae) LC-MS-Based Metabolomics for Species and Geographical Origin Discrimination.

Abstract

The metabolic variability of fruit from Butia spp. (Arecaceae) genotypes from different geographical locations was characterized using untargeted metabolomics by liquid chromatography-mass spectrometry (LC-MS) followed by multivariate data analyses. Principal component analysis (PCA) and partial least-squares discriminant analysis (PLS-DA) from LC-MS data sets showed a clear distinction among Butia catarinensis, Butia odorata, Butia paraguayensis, and Butia yatay. The major metabolites that contributed to species discrimination were primary metabolites including sugars and organic acids and specialized metabolites such as tetrahydroxy-trans-stilbene and rutin. B. odorata fruit from Tapes, RS, Brazil, showed a high content of organic acids and flavonoids, whereas B. odorata fruits from Capão do Leão, RS, Brazil, showed a high sugar content. The results demonstrate that LC-ESI-qToF-MS-based metabolic profiling coupled with chemometric analysis can be used to discriminate among Butia species and between geographical origins of B. odorata and to identify primary and specialized metabolites responsible for the discrimination.