Browsing by Person "Torun, Sedef"

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Spectral similarity score (SSS)-barcoding for the quality control of LACTEM emulsifiers by high-performance thin-layer chromatography
(2026) Schuster, Katharina; Torun, Sedef; Kainz, Inès; Schwarz-Blankart, Max; Hinrichs, Jörg; Steliopoulos, Panagiotis; Oellig, Claudia; Schuster, Katharina; Department of Food Chemistry and Analytical Chemistry (170a), Institute of Food Chemistry, University of Hohenheim, Garbenstrasse 28, Stuttgart, Germany; Torun, Sedef; Department of Food Chemistry and Analytical Chemistry (170a), Institute of Food Chemistry, University of Hohenheim, Garbenstrasse 28, Stuttgart, Germany; Kainz, Inès; Department of Soft Matter Science and Dairy Technology (150e), Institute of Food Science and Biotechnology, University of Hohenheim, Garbenstrasse 21, Stuttgart, Germany; Schwarz-Blankart, Max; Department of Soft Matter Science and Dairy Technology (150e), Institute of Food Science and Biotechnology, University of Hohenheim, Garbenstrasse 21, Stuttgart, Germany; Hinrichs, Jörg; Department of Soft Matter Science and Dairy Technology (150e), Institute of Food Science and Biotechnology, University of Hohenheim, Garbenstrasse 21, Stuttgart, Germany; Steliopoulos, Panagiotis; Chemisches und Veterinäruntersuchungsamt (CVUA), Weißenburgerstrasse 3, Karlsruhe, Germany; Oellig, Claudia; Department of Food Chemistry and Analytical Chemistry (170a), Institute of Food Chemistry, University of Hohenheim, Garbenstrasse 28, Stuttgart, Germany
LACTEM emulsifiers are widely applied in the food industry to adjust and improve techno-functional properties of food products. The study introduces a high-performance thin-layer chromatography−fluorescence detection (HPTLC−FLD) fingerprint method for the similarity assessment of these emulsifiers using a straightforward barcoding approach based on the concept of spectral similarity scores (SSS), referred to as SSS-barcoding. Analysis of 21 LACTEM emulsifiers showed similarities between two emulsifiers as low as 67%, despite the same product labeling. The method also revealed batch-to-batch variability. Limitations were identified when applying the method to fatty matrices. Finally, partial least-squares regression (PLSR) was applied as a proof-of-concept to predict the techno-functional properties of aerosol whipping cream, such as drainage, apparent viscosity, foam firmness, particle size (D90,3), and overrun, from the densitometric data.