Ecosystem discrimination and fingerprinting of Romanian propolis by hierarchical fuzzy clustering and image analysis of TLC patterns
- Resource Type
- Authors
- Costel Sârbu; Augustin Cătălin Moţ
- Source
- Talanta. 85:1112-1117
- Subject
- Time Factors
Fuzzy clustering
Geography
Romania
Chemistry
business.industry
Analytical chemistry
Pattern recognition
Sample (statistics)
Propolis
Fuzzy partition
Fuzzy logic
Plot (graphics)
Pattern Recognition, Automated
Analytical Chemistry
Hierarchical clustering
Image (mathematics)
Fuzzy Logic
Cluster Analysis
Chromatography, Thin Layer
Artificial intelligence
business
Ecosystem
- Language
- ISSN
- 0039-9140
The fingerprinting capacity of thin layer chromatography (TLC) and image analysis in the case of propolis samples collected in different area in Romania has been investigated. Fuzzy divisive hierarchical clustering approach was used as a powerful tool of samples discrimination and fingerprinting according to the geographical origin and local flora. The fuzzy partition and patterns obtained by membership degrees plot were in a very good agreement with floral origin and geographic location of Romanian propolis samples, and clearly illustrate the fuzziness concerning their similarities and difference. The results obtained strongly support that TLC via image analysis can be successfully employed in the fingerprinting methodologies if they are combined with appropriate fuzzy clustering method. The method developed in this paper might be also extended in the authenticity and origin control of fruits, herbs or derived products.