The high-resolution molecular portrait of coffee: A gateway to insights into its roasting chemistry and comprehensive authenticity profiles.

Autor: Pieczonka SA; Analytical Food Chemistry, TUM School of Life Sciences, Technical University of Munich, Freising, Germany; Analytical BioGeoChemistry, Helmholtz Association, Helmholtz Munich, Neuherberg, Germany. Electronic address: stefan.pieczonka@tum.de., Dzemajili A; Analytical Food Chemistry, TUM School of Life Sciences, Technical University of Munich, Freising, Germany; Analytical Chemistry, Department of Applied Sciences and Mechatronics, Munich University of Applied Sciences, Munich, Germany., Heinzmann SS; Analytical BioGeoChemistry, Helmholtz Association, Helmholtz Munich, Neuherberg, Germany., Rychlik M; Analytical Food Chemistry, TUM School of Life Sciences, Technical University of Munich, Freising, Germany., Schmitt-Kopplin P; Analytical Food Chemistry, TUM School of Life Sciences, Technical University of Munich, Freising, Germany; Analytical BioGeoChemistry, Helmholtz Association, Helmholtz Munich, Neuherberg, Germany. Electronic address: schmitt-kopplin@tum.de.
Jazyk: angličtina
Zdroj: Food chemistry [Food Chem] 2024 Sep 24; Vol. 463 (Pt 4), pp. 141432. Date of Electronic Publication: 2024 Sep 24.
DOI: 10.1016/j.foodchem.2024.141432
Abstrakt: The direct-infusion of 130 coffee samples into a Fourier-transform ion cyclotron mass spectrometer (FT-ICR-MS) provided an ultra-high resolution perspective on the molecular complexity of coffee: The exceptional resolving power and mass accuracy (± 0.2 ppm) facilitated the annotation of unambiguous molecular formulas to 11,500 mass signals. Utilizing this molecular diversity, we extracted hundreds of compound signals linked to the roasting process through guided Orthogonal Partial Least Squares (OPLS) analysis. Visualizations such as van Krevelen diagrams and Kendrick mass defect analysis provided deeper insights into the intrinsic compositional nature of these compounds and the complex chemistry underlying coffee roasting. Predictive OPLS-DA models established universal molecular profiles for rapid authentication of Coffea arabica versus Coffea canephora (Robusta) coffees. Compositional analysis revealed Robusta specific signals, indicative of tryptophan-conjugates of hydroxycinnamic acids. Complementary LC-ToF-MS 2 confirmed their compound class, building blocks and structures. Their water-soluble nature allows for application across raw and roasted beans, as well as in ready-made coffee products.
Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper.
(Copyright © 2024 The Authors. Published by Elsevier Ltd.. All rights reserved.)
Databáze: MEDLINE
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