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 2020, 9, 627.
https://doi.org/10.3390/foods9050627
AMA Style
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. 2020; 9(5):627.
https://doi.org/10.3390/foods9050627
Chicago/Turabian Style
Czech, Hendryk, Jan Heide, Sven Ehlert, Thomas Koziorowski, and Ralf Zimmermann.
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 9, no. 5: 627.
https://doi.org/10.3390/foods9050627
APA Style
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, 9(5), 627.
https://doi.org/10.3390/foods9050627
