Comparison of IRMS, GC-MS and E-Nose data for the discrimination of saffron samples with different origin, process and age. (December 2019)

• Record Type: Journal Article
• Authors: Rocchi, Rachele; Mascini, Marcello; Faberi, Angelo; Sergi, Manuel; Compagnone, Dario; Di Martino, Vincenzo; Carradori, Simone; Pittia, Paola
• Is Part Of: Food control. Volume 106(2019)
• Publication Date: 2019-12
• Subjects: Saffron -- Stable isotope ratio analysis -- Volatile pattern analysis -- Quality -- E-Nose -- SPME-GC-MS; 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.2019.106736
• Languages: English
• ISSNs: 0956-7135

Abstract

Abstract: In this study the use of conventional (Isotope-ratio mass spectrometry-IRMS and solid-phase microextraction gas chromatography mass spectrometric, SPME-GC-MS) and non-conventional analytical techniques (Electronic Nose) to characterize and discriminate origin, drying and age of 35 saffron samples was investigated. The IRMS technique by the analysis of the stable carbon and nitrogen isotopes has proved to be a reliable method in discriminating the geographical origin of saffron. Taking into account the chemical classes of the detected volatile compounds, the SPME-GC-MS was able to discriminate the different origin, drying and age. An E-Nose was used as alternative and rapid tool to characterize the complex aroma patterns and to exploit authenticity of saffron samples. Overall, the innovative AuNP-peptide based sensors array showed only a good discrimination of their origin. Results of this study could contribute to select and identify routine quality control methods for quality and authentication of saffron. Highlights: Instrumental methods were applied to discriminate saffron samples. E-nose (peptide gas sensors array) was used as complementary tool to GC-MS. IRMS has proved to be reliable in discriminating saffron origin. GC-MS allowed to classify saffron (origin, drying and age) based on different VOCs. Results could contribute to select tools and methods for saffron quality control.