Minor metabolites as chemical marker for the differentiation of cane, beet and coconut blossom sugar. From profiling towards identification of adulterations

• Published in: Food control Vol. 135; p. 108832
• Main Authors: Bachmann, René, Horns, Anna Lena, Paasch, Nele, Schrieck, Robbin, Weidner, Markus, Fransson, Iris, Schrör, Jan-Philipp
• Format: Journal Article
• Language: English
• Published: Elsevier Ltd 01.05.2022
• Subjects: Betaine; Browned beet sugar; Cane sugar; Coconut blossom sugar; Juice adulteration; Metabolomics; Trans-aconitic acid; Metabolomics; Betaine; Browned beet sugar; Cane sugar; Juice adulteration; Coconut blossom sugar; Trans-aconitic acid
• ISSN: 0956-7135; 1873-7129
• DOI: 10.1016/j.foodcont.2022.108832

The high similar look of different types of brown sugar in combination with high price discrepancies make these sugars a potential target of food fraud. We therefore analyzed the different metabolic profiles of browned beet sugar, unrefined cane sugar and coconut blossom sugar. The investigation was carried out by 1H NMR and supplementary ULPC-Q-TOF-MS analysis to confirm identified metabolites. In addition to the highly variable metabolic profiles, an unambiguous metabolite was identified for each sugar, which was not detectable in the other sugar types by NMR. Betaine was identified as a marker for browned beet sugar, trans-aconitic acid (TAA) for raw cane sugar and pyroglutamic acid as a unique marker for coconut blossom sugar. Based on the variable metabolic profile, we were also able to demonstrate the potential of a multivariate regression model to estimate the degree of adulteration of coconut blossom sugar. In the second part of our study, we additionally investigated the use of minor metabolites for the detection of added sugars in different foods. Using unrefined cane sugar as an example, we demonstrated the thermal and chemical stability of TAA as a marker metabolite. The results of this study show the high potential use of the different metabolic profiles for the detection of food fraud. In combination with multivariate data analysis even small amounts of admixtures can be detected in different types of sugar. [Display omitted] •Description of the polar, non volatile metabolome of coconut sugar.•Identification of unambiguous metabolites for differentiation of sugars.•Betaine, Pyrogluatamic Acid and TAA were identified as marker molecules.•Development of a multivariate regression model for admixture estimation.•Use of the identified metabolic profile for detection of food fraud with sugars.