Abstract
The aim of this study was to explore feasibility of 1H NMR metabolic fingerprinting for discrimination of authenticity of saffron using principal component analysis (PCA) modeling. Authentic reference Iranian saffron (n = 31) and commercial samples (n = 32) were used. Cross-validated PCA models based on 1H NMR spectra of solutions prepared by direct extraction of grinded saffron with methanol-d4 distinguished reference Iranian saffron samples from commercial samples that formed several distinct clusters, some of which represent falsified samples as confirmed by microscopic analysis. The production sites and drying conditions of the authentic reference Iranian samples were not reflected in the current dataset. Picrocrocin and glycosyl esters of crocetin emerged as the most important 1H NMR markers of authentic saffron by using statistical correlation spectroscopy. In conclusion, 1H NMR spectra of saffron extracts combined with pattern recognition by PCA provide immediate means of unsupervised classification of saffron samples.
Originalsprog | Engelsk |
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Tidsskrift | Metabolomics |
Vol/bind | 6 |
Udgave nummer | 4 |
Sider (fra-til) | 511-517 |
ISSN | 1573-3882 |
DOI | |
Status | Udgivet - dec. 2010 |
Emneord
- Det tidligere Farmaceutiske Fakultet