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
- DOI
- 10.3390/foods9050627
- Published
- 2020-05-14
- Container
- Foods
- Publisher
- MDPI AG
- Open access
- unknown
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Cite this work
BibTeX
@article{allodium:10.3390/foods9050627,
title = {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},
author = {Hendryk Czech and Jan Heide and Sven Ehlert and Thomas Koziorowski and Ralf Zimmermann},
year = {2020},
journal = {Foods},
doi = {10.3390/foods9050627},
url = {https://doi.org/10.3390/foods9050627}
}RIS
TY - JOUR TI - 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 AU - Hendryk Czech AU - Jan Heide AU - Sven Ehlert AU - Thomas Koziorowski AU - Ralf Zimmermann PY - 2020 JO - Foods DO - 10.3390/foods9050627 UR - https://doi.org/10.3390/foods9050627 ER -
APA
Czech, H., Heide, J., Ehlert, S., Koziorowski, T., & Zimmermann, R. (2020). 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. https://doi.org/10.3390/foods9050627
Source records
- crossref · retrieved 2026-09-27T15:11:30.100Z