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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) -
Jan Heide,
Hendryk Czech,
Sven Ehlert,
Thomas Koziorowski,
Ralf Zimmermann
Publication year - 2020
Publication title -
journal of agricultural and food chemistry
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.203
H-Index - 297
eISSN - 1520-5118
pISSN - 0021-8561
DOI - 10.1021/acs.jafc.9b06502
Subject(s) - roasting , chemistry , food science , antioxidant capacity , process (computing) , degree (music) , process engineering , antioxidant , computer science , organic chemistry , engineering , physics , acoustics , operating system
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.

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