Revealing the botanical composition of honey and the environment it is produced in is essential for ensuring food safety, quality control, and biodiversity monitoring. Such information also supports sustainable agricultural management and enhances our understanding of plant–pollinator interactions. This study aimed to simultaneously characterize plant communities from honey, airborne particles, and pollen using an integrated DNA metabarcoding approach.

Samples were collected from a total of 13 fields over a period of 6 months and analyzed using high-throughput sequencing of plant DNA. Taxonomic identifications were conducted using reference databases, enabling direct comparison of plant assemblages among the sample types.

The results indicated that honey reflected a broad range of floral sources visited by bees, while airborne DNA provided complementary insights into the local vegetation and environmental exposure. Pollen data offered finer-resolution information on specific floral interactions. Multivariate analyses (Bray–Curtis dissimilarity and PERMANOVA) revealed significant compositional differences between the sample types, yet common taxa such as Populus nigra, Hedera helix, and Cistus laurifolius were consistently detected across all matrices, highlighting key components of regional biodiversity.

This combined eDNA-based workflow offers a robust and non-invasive tool for tracing the botanical origin of honey and monitoring plant diversity dynamics. Beyond advancing food authenticity verification, the approach holds promise for applications in sustainable agriculture, ecological assessments, and biodiversity conservation.