The Effect of Pre-Treatment of Arabica Coffee Beans with Cold Atmospheric Plasma, Microwave Radiation, Slow and Fast Freezing on Antioxidant Activity of Aqueous Coffee Extract
Source abstract
Abstract
Thermal and non-thermal technologies used in food processing should be not only effective in terms of decontamination and preservation but also minimize undesirable losses of natural bioactive compounds. Arabica (Coffea arabica) is the most cultivated variety of coffee, making it a valuable source of phytonutrients, including antioxidants. In the present study, green and roasted Arabica coffee beans were treated with slow freezing (SF), fast freezing (FF), microwave radiation (MWR) and cold atmospheric plasma (CAP). Moisture content (MC) of coffee beans and antioxidant activity (AOA) of aqueous extracts were measured. Green coffee showed a decrease in MC after MWR treatment, and roasted coffee showed an increase in MC after freezing. After SF and FF at −19 °C for 24 h, all extract samples showed an increase in AOA by 4.1–17.2%. MWR treatment at 800 W for 60 s was accompanied by an increase in the AOA of green coffee extracts by 5.7%, while the changes in the AOA of roasted coffee extracts were insignificant. Sequential combined treatments of SF + MWR and FF + MWR resulted in an additive/synergistic increase in the AOA of green/roasted coffee extracts, up to +23.0%. After CAP treatment with dielectric barrier discharge (DBD) parameters of 1 μs, 15 kV and 200 Hz for 5 and 15 min, green coffee showed a decrease in the extract AOA by 3.8% and 9.7%, respectively, while the changes in the AOA of roasted coffee extracts were insignificant. A high positive correlation (r = 0.89, p < 0.001) between AOA and MC was revealed. The results obtained indicate that SF, FF, MWR and combined treatments may be applied at the pre-extraction stage of coffee bean preparation in order to increase the yield of antioxidant extractives.
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Research context
OpenAlex topics: Coffee research and impacts · Microbial Inactivation Methods · Plasma Applications and Diagnostics
SciVX discovery tags are terminology-based. OpenAlex topics are source-provided classifications.
Affiliations
Scientific and Innovation Center of Sensor Technologies, Ural State University of Economics, 8 Marta St., 62, 620144 Yekaterinburg, Russia
Department of Food Technology, Ural State University of Economics, 8 Marta St., 62, 620144 Yekaterinburg, Russia
Department of Physics and Chemistry, Ural State University of Economics, 8 Marta St., 62, 620144 Yekaterinburg, Russia
Institute of Electrophysics, Ural Branch of the Russian Academy of Sciences, Amundsen St., 106, 620016 Yekaterinburg, Russia
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