Multilocus Metabarcoding for Floral Composition Analysis and Honey Bee Conservation

Honey is a nutritionally rich food with medicinal properties, and its authenticity depends strongly on botanical and geographical origin. Identifying the floral composition of the honey is essential for understanding bee diets, plant diversity, and ecosystem interactions. Traditional palynological methods, based on microscopic pollen analysis, are labor‑intensive process and require specialized expertise. Recent advances in the next‑generation sequencing (NGS) technology have introduced metabarcoding as a powerful alternative for pollen identification. In this study, two composite honey metagenomes were analyzed using three genetic loci (rbcL, matK, and ITS2) sequenced on the Illumina MiSeq platform. Classical palynological analyses were conducted in parallel to evaluate the performance of the molecular approach. Both methods successfully identified predominant floral taxa, but multilocus metabarcoding provided higher taxonomic resolution and improved sensitivity across diverse plant groups. Our findings demonstrate that NGS‑based metabarcoding offers a robust framework for comprehensive botanical profiling of honey, overcoming many limitations of classical microscopy. This approach not only enhances honey authentication but also contributes to biodiversity monitoring, sustainable apiculture, and conservation of pollinator–plant interactions. With the development of robust reference databases, metabarcoding has the potential to replace the traditional palynological studies and serve as a transformative tool in biodiversity research and honey bee conservation.