ArticleFoods (Basel, Switzerland)2025
Honey Geographical Origin Characterization and Authentication Based on Spectrophotometric Assays, Physicochemical Parameters, and LC-MS/MS Polyphenolic Profiling.
Article in Foods (Basel, Switzerland), 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.
What it found
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
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Who cites it
4 citing papers in PubMed.
- NMR Profiling of European Oak Honeydew Honeys: Saccharide Diversity and Geographical Differentiation.Molecules (Basel, Switzerland) · 2026Article
- Authenticity Assessment of Five Monofloral Honeys Based on Phytochemical Profiles.Foods (Basel, Switzerland) · 2026Article
- Modern Fluorescence Strategies for Honey Characterization: Analytical Advances, Emerging Technologies, Methodological Challenges, and Future Perspectives.Foods (Basel, Switzerland) · 2026Review
- Honey Fraud as a Moving Analytical Target: Omics-Informed Authentication Within a Multi-Layer Analytical Framework.Foods (Basel, Switzerland) · 2026Review
Corrections and comments
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Authors and funding
7 authors.
Funding
Abstract
Honey is a widely consumed natural sweetener produced by honeybees from the nectar of plants, secretions of living parts of plants, or insect excretions. Its high value is due to its nutritional value and multiple benefits to human health. However, due to the diversity in geographical origins, the properties of honey can vary depending on the region of production, leading to discrepancies in honey pricing. Therefore, it is essential to examine these variations by analyzing several parameters in honey from diverse regions. In this work, honeys from eight countries were characterized by measuring several physicochemical parameters and spectrophotometric assays aiming at geographical origin authentication. In addition, the polyphenolic profile of the samples was obtained by LC-LRMS. An acceptable discrimination of the samples was obtained when considering all variables altogether, with classification errors lower than 31.9%.
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Registered trials
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