Wood profiling by non-targeted high-resolution mass spectrometry: Part 1, Metabolite profiling in Cedrela wood for the determination of the geographical origin.

Affiliation

Creydt M(1), Ludwig L(2), Köhl M(3), Fromm J(4), Fischer M(5).
Author information:
(1)Hamburg School of Food Science, Institute of Food Chemistry, University of Hamburg, Grindelallee 117, 20146 Hamburg, Germany; Cluster of Excellence, Understanding Written Artefacts, University of Hamburg, Warburgstraße 26, 20354 Hamburg, Germany. Electronic address: [Email]
(2)Hamburg School of Food Science, Institute of Food Chemistry, University of Hamburg, Grindelallee 117, 20146 Hamburg, Germany.
(3)Institute of Wood Science, Research Unit World Forestry, University of Hamburg, Leuschnerstrasse 91e, 21031, Hamburg, Germany.
(4)Cluster of Excellence, Understanding Written Artefacts, University of Hamburg, Warburgstraße 26, 20354 Hamburg, Germany; Institute of Wood Science, Research Unit Wood Biology, University of Hamburg, Leuschnerstrasse 91d, 21031, Hamburg, Germany.
(5)Hamburg School of Food Science, Institute of Food Chemistry, University of Hamburg, Grindelallee 117, 20146 Hamburg, Germany; Cluster of Excellence, Understanding Written Artefacts, University of Hamburg, Warburgstraße 26, 20354 Hamburg, Germany.

Abstract

The determination of the geographical origin of wood can be highly relevant for several reasons: On the one hand, it can help to prevent illegal logging and timber trade, on the other hand, it is of special interest for archaeological artefacts made of wood, as well as for a variety of biological questions. For this reason, different extraction methods were first tested for the analysis of polar and non-polar metabolites using liquid chromatography coupled electrospray ionization quadrupole time-of-flight mass spectrometry (UHPLC-ESI-QTOF-MS). A two-phase extraction with chloroform, methanol and water proved to be particularly successful. Subsequently, cedrela (Cedrela odorata) samples from South America were measured to distinguish geographic origin. Using multivariate data analysis, numerous origin-dependent differences could be extracted. The identification of the marker substances indicated that several metabolic pathways were affected by the geographical influences, some of them probably indicating pest infections.