ArticleInternational journal of molecular sciences2022
The Development of Honey Recognition Models Based on the Association between ATR-IR Spectroscopy and Advanced Statistical Tools.
Article in International journal of molecular sciences, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 9 papers.
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Who cites it
9 citing papers in PubMed, 27 citations in OpenAlex.
- Rapid Assessment of Honey Physicochemical Properties by Mid-Infrared Spectroscopy and Chemometric Modeling.ACS omega · 2026Article
- The Journey of Artificial Intelligence in Food Authentication: From Label Attribute to Fraud Detection.Foods (Basel, Switzerland) · 2025Review
- Honey Differentiation Using Infrared and Raman Spectroscopy Analysis and the Employment of Machine-Learning-Based Authentication Models.Foods (Basel, Switzerland) · 2025Article
- New Insights on Quality, Safety, Nutritional, and Nutraceutical Properties of Honeydew Honeys from Italy.Molecules (Basel, Switzerland) · 2025Article
- Honey Adulteration Detection via Ultraviolet-Visible Spectral Investigation Coupled with Chemometric Analysis.Foods (Basel, Switzerland) · 2024Article
- Portable NIR Spectroscopy to Simultaneously Trace Honey Botanical and Geographical Origins and Detect Syrup Adulteration.Foods (Basel, Switzerland) · 2024Article
- Drug-Delivery Silver Nanoparticles: A New Perspective for Phenindione as an Anticoagulant.Biomedicines · 2023Article
- Drug-Loaded Silver Nanoparticles-A Tool for Delivery of a Mebeverine Precursor in Inflammatory Bowel Diseases Treatment.Biomedicines · 2023Article
- Botanical Origin Influence on Some Honey Physicochemical Characteristics and Antioxidant Properties.Foods (Basel, Switzerland) · 2023Article
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Authors and funding
4 authors at 1 institution in 1 country.
Funding
Abstract
The newly developed prediction models, having the aim to classify Romanian honey samples by associating ATR-FTIR spectral data and the statistical method, PLS-DA, led to reliable differentiations among the samples, in terms of botanical and geographical origin and harvesting year. Based on this approach, 105 out of 109 honey samples were correctly attributed, leading to true positive rates of 95% and 97% accuracy for the harvesting differentiation model. For the botanical origin classification, 83% of the investigated samples were correctly predicted, when four honey varieties were simultaneously discriminated. The geographical assessment was achieved in a percentage of 91% for the Transylvanian samples and 85% of those produced in other regions, with overall accuracy of 88% in the cross-validation procedure. The signals, based on which the best classification models were achieved, allowed the identification of the most significant compounds for each performed discrimination.
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Registered trials
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