| Title: | Toward Smart Online Coffee Roasting Process Control: Feasibility of Real-Time Prediction of Coffee Roast Degree and Brew Antioxidant Capacity by Single-Photon Ionization Mass Spectrometric Monitoring of Roast Gases |
| Author(s): | Heide J; Czech H; Ehlert S; Koziorowski T; Zimmermann R; |
| Address: | "Joint Mass Spectrometry Centre, Chair of Analytical Chemistry, Institute of Chemistry, University of Rostock, Dr.-Lorenz-Weg 2, 18059 Rostock, Germany. Joint Mass Spectrometry Centre, Cooperation Group 'Comprehensive Molecular Analytics', Helmholtz Zentrum Munchen-German Research Center for Environmental Health GmbH, Gmunder Strasse 37, 81379 Munchen, Germany. Photonion GmbH, Hagenower Strasse 73, 19061 Schwerin, Germany. Department Life, Light & Matter, University of Rostock, Albert-Einstein-Strasse 25, 18059 Rostock, Germany. PROBAT-Werke von Gimborn Maschinenfabrik GmbH, Reeser Strasse 94, 46446 Emmerich am Rhein, Germany" |
| ISSN/ISBN: | 1520-5118 (Electronic) 0021-8561 (Linking) |
| Abstract: | "Precise controlling and monitoring the status of the coffee roasting process is essential for consistent product quality and optimization toward targeted coffee properties. In small-scale roasting experiments, the chemical composition of the roasting off-gas was analyzed by online single-photon ionization time-of-flight mass spectrometry (SPI-TOFMS) at 118 nm with 5 s time resolution. Subsequently, mass spectra at the drop of the coffee beans were combined with off-line measurements of roast degree, described by color value 'Colorette', and the antioxidant capacity, obtained from the Folin-Ciocalteu (FC) assay, in an explanatory projection on latent structure regression model. While the roast degree gives an indication of the coffee flavor, antioxidants in brewed coffee are regarded as beneficial for human health. Colorette and FC values could be derived from the SPI mass spectra with root-mean-square errors from Monte Carlo cross-validation of 6.0 and 139 mg of gallic acid equiv L(-1), respectively, and explained covariance (R(2)(CV)) better than 89%. Finally, the regression models were applied to the SPI mass spectra over the entire roast to demonstrate the predictive ability for online process control in real time" |
| Keywords: | Antioxidants/*chemistry Automation/instrumentation/*methods Coffea/*chemistry Cooking Gases/*chemistry Hot Temperature Mass Spectrometry/*methods Seeds/chemistry Time Volatile Organic Compounds/chemistry Colorette FC assay photoionization mass spectrometr; |
| Notes: | "MedlineHeide, Jan Czech, Hendryk Ehlert, Sven Koziorowski, Thomas Zimmermann, Ralf eng Evaluation Study 2020/01/23 J Agric Food Chem. 2020 Apr 29; 68(17):4752-4759. doi: 10.1021/acs.jafc.9b06502. Epub 2020 Jan 22" |
