Chemical profiling of saffron for authentication of origin. (December 2019)

• Record Type: Journal Article
• Authors: Wakefield, Joshua; McComb, Kiri; Ehtesham, Emad; Van Hale, Robert; Barr, David; Hoogewerff, Jurian; Frew, Russell
• Is Part Of: Food control. Volume 106(2019)
• Publication Date: 2019-12
• Subjects: Provenance -- Saffron -- Stable isotope -- Trace metal -- Iran -- Spain; Food -- Quality -- Periodicals; Food -- Analysis -- Periodicals; Food handling -- Periodicals; Food industry and trade -- Quality control -- Periodicals; Aliments -- Industrie et commerce -- Qualité -- Contrôle -- Périodiques; Aliments -- Qualité -- Périodiques; Aliments -- Analyse -- Périodiques; Hygiène alimentaire -- Périodiques; Food -- Analysis; Food handling; Food -- Quality; Periodicals; Electronic journals; 664.07
• DOI: 10.1016/j.foodcont.2019.06.025
• Languages: English
• ISSNs: 0956-7135

Abstract

Abstract: Saffron, the dried red stigmas of Crocus sativus L. is the world's most expensive spice. The expense of Saffron has led to greater incidences of fraudulent practice within this market. The importation and rebranding of cheaper growing regions to be passed off as regions of higher quality is one such practice. Analytical techniques have been reported in literature for rapid detection of these fraud issues. These techniques can be affected by post harvest processing, therefore more confirmatory techniques with direct links to the environment should also be considered. Trace element concentrations and stable isotopic ratios are investigated in this study to differentiate the geographic origins of Saffron grown in Khorasan Province, Iran and the La Mancha region of Spain. Statistical analysis of the data using Linear Discriminate Analysis (LDA) resulted in a classification model which could determine saffron from each origin, suggesting this is a feasible confirmatory approach for origin verification of Saffron. Highlights: Authentic samples representing the 2010-11 growing season in Spain and Iran. Provides comparison data for further studies i.e. interannual variability. Data calibrated to international standards for inclusion in food origin databases. Analytical parameters of interest to others wishing to conduct similar assays. Loadings for the PCA of value to those conducting multivariate statistical analyses.