Employing DNA metabarcoding to determine the geographical origin of honey

Elmira Khansaritoreh; Yasaman Salmaki; Elias Ramezani; Tayebeh Akbari Azirani; Alexander Keller; Katrin Neumann; Kamaleddin Alizadeh; Shahin Zarre; Gudrun Beckh; Hermann Behling

doi:10.1016/j.heliyon.2020.e05596

Employing DNA metabarcoding to determine the geographical origin of honey

Heliyon. 2020 Nov 25;6(11):e05596. doi: 10.1016/j.heliyon.2020.e05596. eCollection 2020 Nov.

Authors

Affiliations

¹ University of Goettingen, Department of Palynology and Climate Dynamics, Untere Karspüle 2, 37073, Goettingen, Germany.
² Department of Plant Science, Center of Excellence in Phylogeny, School of Biology, College of Science, University of Tehran, P.O. Box 14155-6455, Tehran, Iran.
³ Department of Forestry, Faculty of Natural Resources, Urmia University, Urmia, Iran.
⁴ Department of Physical Geography, School of Earth Sciences, Shahid Beheshti University (S.B.U), Tehran, Iran.
⁵ Center for Computational and Theoretical Biology & Department of Bioinformatics, University of Würzburg, Am Hubland, 97074 Würzburg, Germany.
⁶ Lifeprint GmbH, Industriestrasse 12, 89257, Illertissen, Germany.
⁷ Quality Service International GmbH, Flughafendamm 9, 28199, Bremen, Germany.

Abstract

Unfavourable climatic conditions force Iranian beekeepers to translocate over large distances in the course of the year. However, irrespective of the main place of production, the honey is always labeled with the name of the beekeepers' hometown, which leads consequently to mislabeled products. The present study investigates the capability of DNA metabarcoding to locate the geographical origin of honey. The molecular markers (ITS2 and rbcL) allowed identification of 926 plant species in studied samples. A comprehensive review of floristic reference books specified 34 key species that could be used to successfully determine the geographical origin in 91.4% of samples. These key species were usually present in honey with tiny amounts and thus, conventional palynology might not be able to detect them. The present investigation indicates that although ITS2 is able to detect more species than rbcL, utilizing a combination of both markers provides more robust evidence of geographical origin.

Keywords: Food analysis; Food science; Food technology; Geographical origin; Honey; ITS2; Metabarcoding; Molecular biology; rbcL.