Improving floral authentication of geographically labeled Anzer honey through ITS-based metabarcoding and traditional melissopalynology

Türker Z., ÇOŞKUNÇELEBİ K., GÜZEL M. E., MAKBUL S.

Journal of Food Composition and Analysis, cilt.148, 2025 (SCI-Expanded) identifier

  • Yayın Türü: Makale / Tam Makale
  • Cilt numarası: 148
  • Basım Tarihi: 2025
  • Doi Numarası: 10.1016/j.jfca.2025.108478
  • Dergi Adı: Journal of Food Composition and Analysis
  • Derginin Tarandığı İndeksler: Science Citation Index Expanded (SCI-EXPANDED), Scopus, Academic Search Premier, PASCAL, Analytical Abstracts, BIOSIS, Biotechnology Research Abstracts, CAB Abstracts, Food Science & Technology Abstracts, Veterinary Science Database
  • Anahtar Kelimeler: Anzer, DNA metabarcoding, Honey, Illumina, Melissopalynology, Pollen
  • Karadeniz Teknik Üniversitesi Adresli: Evet

Özet

This study utilized next-generation sequencing (NGS) of nrDNA ITS regions (ITS1 and ITS2) for the first time to analyze three honey samples from Anzer (Ballıköy), Rize province, Türkiye. The NGS results were evaluated alongside melissopalynological data. NGS results produced 310,745 paired-end reads for ITS1 and 39,835 reads for ITS2. Of these, 75.2 % of ITS1 reads and 68.4 % of ITS2 reads were identified to at least the family level. NGS analysis detected 27 plant families and 54 taxa, a 37 % increase in taxa detection compared to melissopalynology, which identified 19 families and 34 taxa. Both approaches consistently identified dominant floral components, with NGS providing greater species-level resolution. Spearman's correlation revealed a moderate linear relation between the two methodologies for two of the three samples. However, the Shannon-Wiener and Pielou indices were lower in metabarcoding than in melissopalynology due to the uneven distribution of read counts for some species. The R-coefficient results of all the families showed over- or underrepresentation, except for Caryophyllaceae (0.85) and Asteraceae (0.93). While to date, melissopalynology has been the prime identification method for determining the geographical origin of honey, this study, for the first time, presents a comprehensive and reliable metabarcoding dataset for Anzer honey identification.