This study proposed a mathematical model which was used to predict the temperature and moisture content of Ganoderma lucidum (Ganoderma boninense) during the radio frequency (RF) assisted heat pump (HP) drying process. The simultaneous heat and mass transfer equations were established based on the physical and flat plate models for drying Ganoderma lucidum and the specific assumptions for the proposed problem. The finite difference method was used to solve the proposed heat transfer and moisture transfer problem, in which, pdepe function was adjusted and complemented with Matlab software. The temperature and moisture content of the material in the drying process was predicted. The effect of the output RF power on the temperature and moisture content of the material was evaluated. The drying process's input parameters were drying air temperature of 40 o C, air velocity of 1.2 m/s, and an output RF power of 1.95 kW, 0.65 and 0 kW. The results showed that when the output RF power increases, the heating rate increases, and the drying time is shortened significantly. The drying material temperature reaches the drying air temperature in 20 minutes, 30 minutes, and 220 minutes and the drying time is 465, 555, and 700 minutes, corresponding to output RF power of 1.95 kW, 0.65 and 0 kW. The predicted temperature and moisture content of the material were compared with experimental drying data, and a considerably good agreement was found.

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A radio-frequency (RF) generator applied in drying technology was designed and manufactured for drying Ganoderma lucidum. The drying experiments were conducted by drying method of RF-assisted heat pump in order to inspect the operating parameters of the RF generator and investigate the effects of the input drying parameters on drying rate in the RF-assisted heat pump drying of Ganoderma lucidum. The results have shown that the RF generator achieved the required operating parameters as design such as RF power of 3 kW and operating frequency of 27 MHz. In RF-assisted heat pump drying, increase in RF power and drying air temperature increases the drying rate. Meanwhile, drying air velocity does not significantly affect the drying rate. At RF power of 1.95 kW, the drying time reduces by 9, 17, and 33% in comparison with RF power of 1.3, 0.65, and 0 kW (heat pump drying). At drying air temperature of 50°C, the drying time reduces by 10% and 21% in comparison with drying air temperature of 40 and 45°C. Besides, increasing RF power retains the higher content of polysaccharide in Ganoderma lucidum, and the Ganoderma lucidum samples retain the color better after drying.

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The study focused on reviewing modern and effective drying methods assisted by infrared radiation, microwave and radio frequency. In which, the drying results of previous studies were reviewed to clarify the drying efficiency of drying methods with the support of infrared radiation, microwave and radio frequency. The review results showed that the radiant heating mechanism of infrared radiation and the volumetric heating mechanism of microwave and radio frequency supported the process of material heating and moisture diffusion within the material. As a result, the drying process achieved high drying efficiency, the drying time was significantly shortened and the quality of the dried products was improved both in terms of sensory quality and nutritional quality. The study of the application of infrared radiation, microwave and radio frequency in drying technique had a high scientific, technological and practical significance. This would be the foundation for finding suitable drying methods and drying modes to improve drying efficiency as well as the quality of dried products.

Equilibrium moisture content (EMC) of Ganoderma Lucidum was determined experimentally at three different experimental temperature (30, 40 and 50°C) and relative humidity ranged from 11.1 to 93.58% using a gravimetric technique. The experimental data of equilibrium moisture content obtained was fitted to four mathematical models (Modified Henderson, Modified Chung ˗ Pfost, Modified Oswin and Modified Haley). A non-linear least square regression analysis was used to evaluate the model constants based on the parameters as: standard error of estimate (SEE), the residual sum of squares (RSS), the quadratic regression coefficient (R2). The result showed that the modified Chung ˗ Pfost model best fitted the experimental data.

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