1H NMR-based metabolomics of saffron reveals markers for its quality deterioration. (April 2015)

• Record Type: Journal Article
• Authors: Ordoudi, Stella A.; Cagliani, Laura R.; Lalou, Sofia; Naziri, Eleni; Tsimidou, Maria Z.; Consonni, Roberto
• Is Part Of: Food research international. Volume 70(2015)
• Page Start: 1
• Page End: 6
• Publication Date: 2015-04
• Subjects: Saffron -- Storage -- Quality marker -- NMR -- PCA -- OPLS-DA; Food -- Analysis -- Periodicals; Food industry and trade -- Periodicals; Food industry and trade -- Canada -- Periodicals; Food Technology -- Periodicals; Food -- Periodicals; Food-Processing Industry -- Periodicals; Aliments -- Industrie et commerce -- Périodiques; Aliments -- Industrie et commerce -- Canada -- Périodiques; Aliments -- Recherche -- Périodiques; Food industry and trade; Canada; Periodicals; Electronic journals; 664.005
• DOI: 10.1016/j.foodres.2015.01.021
• Languages: English
• ISSNs: 0963-9969

Abstract

Abstract: 1 H NMR-based metabolomics is proposed here for the quality control of saffron upon storage using the ability to detect a wide range of chemical compounds with minimal sample preparation. Saffron quality deterioration is the result of enzymatic, oxidative and hydrolytic reactions that change the content and structure of the glycosides of crocetin and picrocrocin, which are the metabolites responsible for the major sensory properties of this most expensive spice. Several authentic saffron samples (n = 98) of known storage history after processing were examined. The Principal Component Analysis shows a clear-cut separation of samples into two groups based on the storage period regardless of the sample origin. The S-plot derived from the Orthogonal Projections to Latent Structures-Discriminant Analysis (OPLS-DA) model shows the markers for quality deterioration, i.e., sugars bound to crocetin, glucose in picrocrocin, free sugars and fatty acids. These new markers become critical for the samples that were stored for more than 4 years. The OPLS-DA model was validated with a test set and proved to be properly designed to predict the length of storage after harvest. The answer to the question set in the market of "when" and "why" a saffron sample can no longer be considered fresh is supported by our findings. Highlights: NMR based metabolite fingerprinting for saffron quality characterisation Identification of storage threshold (4 years) for freshness of saffron Identification of specific markers to monitor storage effects