Inputs for ANN (multihidden-layer feed-forward artificial neural network) models were drying time (t(i + 1)), initial temperature (T0), moisture content (MC0), microwave power, and vacuum pressure. The outputs were temperature (T(i + 1)) and moisture content (MC(i + 1)) at a given t(i + 1). After training the ANN models with experimental data using the Levenberg-Marquardt algorithm, a two-hidden-layer model (25-25) was determined to be the most appropriate model. The mean relative error (MRE) and mean absolute error (MAE) of this model for T(i + 1) were 1.53% and 0.77 degrees C, respectively. In the case of MC(i + 1), the MRE and MAE were 11.48% and 0.04 kg(water)/kg(dry), respectively. Using temperature (T(i)) and moisture content (MC(i)) values at t(i) in the input layer significantly reduced the computation errors such that MRE and MAE for T(i + 1) were 0.35% and 0.18 degrees C, respectively. In contrast, these error values for MC(i + 1) were 1.78% (MRE) and 0.01 kg(water)/kg(dry) (MAE). These results indicate that ANN models were able to recognize relationships between process parameters and product conditions. The model may provide information regarding microwave power and vacuum pressure to prevent thermal damage and improve drying efficiencies.

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Shiitake mushrooms were dehydrated by two different drying methods, i.e., microwave-vacuum drying (MVD) and microwave-vacuum combined with infrared drying (MVD + IR). MVD was operated at microwave powers of 56, 143, 209 and 267 W under absolute pressures of 18.66, 29.32, 39.99 and 50.65 kPa, whereas infrared radiation was added in MVD+IR at 100 and 200 W. The effects of microwave power, absolute pressure and infrared power on drying characteristics, qualities and specific energy consumption were investigated. It was found that drying rate increased with lower absolute pressure, higher microwave power and higher infrared power. In particular, the results also indicated that drying undergoing MVD+IR could provide better qualities in terms of color of dried shiitake mushroom, rehydration ratio and texture of rehydrated ones. Furthermore, the drying characteristics were described by fitting data to six different drying models. Based on their coefficient of determination, root mean square error, residual of sum square and chi-square, Modified Page model could accurately predict moisture ratio for all drying conditions. Within the range of this study, the suitable drying condition with respect to the product qualities and energy consumption was MVD+IR drying at 267 W of microwave power, 18.66 kPa of absolute pressure and 200 W of infrared power.

Fresh red chilli (Capsicum frutescens L.) was dried using microwave-vacuum drying (MVD) and the far-infrared radiation assisted microwave-vacuum drying (FIR-MVD) method. The MVD was operated using the microwave power of 100, 200 and 300 W under absolute pressure of 21.33, 28.00 and 34.66 kPa. In terms of FIR-MVD, far-infrared power was applied at 100, 200 and 300 W. The effect of drying conditions, i.e., microwave power, absolute pressure and FIR power, on drying characteristics and qualities of dried product were investigated. It was observed that an increase in microwave power and FIR power with a decrease in absolute pressure could accelerate the drying rate. It was also found that FIR-MVD method required shorter drying time than MVD. Moreover, qualities, i.e., color changes, texture, rehydration ability and shrinkage, of FIR-MVD chilli were found to be better than those of MVD. Consequently, the optimum drying condition of FIR-MVD within this study was microwave power of 300 W under absolute pressure of 21.33 kPa with FIR power of 300 W.