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Czech, H. ; Heide, J.* ; Ehlert, S.* ; Koziorowski, T.* ; Zimmermann, R.

Smart online coffee roasting process control: Modelling coffee roast degree and brew antioxidant capacity for real-time prediction by resonance-enhanced multi-photon ionization mass spectrometric (REMPI-TOFMS) monitoring of roast gases.

Foods 9:627 (2020)
Publ. Version/Full Text DOI PMC
Open Access Gold
Creative Commons Lizenzvertrag
Process control with high time resolution is essential to maintain high product quality in coffee roasting. However, analytical techniques for quality assurance or measurements of desired coffee properties are often labor-intensive and can only be conducted after dropping the coffee beans. Resonance-enhanced multi-photon ionization time-of-flight mass spectrometry (REMPI-TOFMS) at 248 nm and 266 nm was applied to analyze the composition of the roast gas from small-scale Arabica coffee roasting. Coffee beans were dropped after different roasting times, ground and analyzed by Colorette to obtain the roast degree. Additionally, the antioxidant capacity of the coffee brew was determined by Folin-Ciocalteu (FC) assay. Models for the prediction of Colorette and FC values from REMPI mass spectra were constructed by partial least squares (PLS) regression. REMPI-TOFMS enables the prediction of Colorette values with a root-mean-square error in prediction (RMSEP) below 5 for both wavelengths. FC values could be predicted using REMPI at 248 nm with an RMSE(P)of 80.3 gallic acid equivalents (GA-eq) mg L-1, while REMPI at 266 nm resulted in RMSE(P)of 151 GA-eq mg L-1. Finally, the prediction of Colorette and FC value at 5 s time resolution were demonstrated with online measurements.
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Publication type Article: Journal article
Document type Scientific Article
Corresponding Author
Keywords Photoionization Mass Spectrometry ; Polyphenols ; Process Control ; Real-time Monitoring ; Chemometrics ; Arabica Coffee; Near-infrared Spectroscopy; Net Analyte Signal; Least-squares Regression; Flavor Formation; Tool; Products; Ms
ISSN (print) / ISBN 2304-8158
e-ISSN 2304-8158
Journal Foods
Quellenangaben Volume: 9, Issue: 5, Pages: , Article Number: 627 Supplement: ,
Publisher MDPI
Publishing Place Basel, Switzerland
Non-patent literature Publications
Reviewing status Peer reviewed
Institute(s) Cooperation Group Comprehensive Molecular Analytics (CMA)