Optimization of Intensification of Freeze-Drying Rate of Banana: Combined Applications of IR Radiation and Cryogenic Freezing

Quality and Process Optimization of Infrared Combined Hot Air Drying of Yam Slices Based on BP Neural Network and Gray Wolf Algorithm

In this paper, the effects on drying time (Y1), the color difference (Y2), unit energy consumption (Y3), polysaccharide content (Y4), rehydration ratio (Y5), and allantoin content (Y6) of yam slices were investigated under different drying temperatures (50-70 °C), slice thicknesses (2-10 mm), and radiation distances (80-160 mm). The optimal drying conditions were determined by applying the BP neural network wolf algorithm (GWO) model based on response surface methodology (RMS). All the above indices were significantly affected by drying conditions (p < 0.05). The drying rate and effective water diffusion coefficient of yam slices accelerated with increasing temperature and decreasing slice thickness and radiation distance. The selection of lower temperature and slice thickness helped reduce the energy consumption and color difference. The polysaccharide content increased and then decreased with drying temperature, slice thickness, and radiation distance, and it was highest at 60 °C, 6 mm, and 120 mm. At 60 °C, lower slice thickness and radiation distance favored the retention of allantoin content. Under the given constraints (minimization of drying time, unit energy consumption, color difference, and maximization of rehydration ratio, polysaccharide content, and allantoin content), BP-GWO was found to have higher coefficients of determination (R2 = 0.9919 to 0.9983) and lower RMSEs (reduced by 61.34% to 80.03%) than RMS. Multi-objective optimization of BP-GWO was carried out to obtain the optimal drying conditions, as follows: temperature 63.57 °C, slice thickness 4.27 mm, radiation distance 91.39 mm, corresponding to the optimal indices, as follows: Y1 = 133.71 min, Y2 = 7.26, Y3 = 8.54 kJ·h·kg-1, Y4 = 20.73 mg/g, Y5 = 2.84 kg/kg, and Y6 = 3.69 μg/g. In the experimental verification of the prediction results, the relative error between the actual and predicted values was less than 5%, proving the model's reliability for other materials in the drying technology process research to provide a reference.

Effects of intermittent CO2 convection under far-infrared radiation on vacuum drying of pre-osmodehydrated watermelon

BACKGROUND

Watermelon, a tropical seasonal fruit with high nutrient content, requires preservation through drying due to its perishable nature. Nevertheless, drying of watermelon through conventional processes has a negative impact either on the drying time or on the final product quality. In this work, osmotic dehydration of watermelon followed by far-infrared radiation-assisted vacuum drying (FIRRAVD) was optimized to develop dehydrated watermelon with minimum moisture content. Significantly, during FIRRAVD, an attempt was made to further intensify the drying rate by forced convection through intermittent CO₂ injection. Drying kinetics of each operation and physicochemical qualities of dried products were evaluated.

RESULTS

FIRRAVD was a viable method of watermelon drying with appreciably high moisture diffusivity (D_eff,m ) of 4.97 × 10^-10 to 1.49 × 10^-9 m² s^-1 compared to conventional tray drying. Moreover, intermittent CO₂ convection during FIRRAVD (ICFIRRAVD) resulted in appreciable intensification of drying rate, with enhanced D_eff,m (9.93 × 10^-10 to 1.99 × 10^-9 m² s^-1 ). Significantly, ICFIRRAVD required less energy and approximately 16% less time compared to FIRRAVD. The quality of the final dehydrated watermelon was superior compared to conventional drying protocols.

CONCLUSIONS

The novel CO₂ convective drying of watermelon in the presence of far-infrared radiation demonstrated an energy-efficient and time-saving operation rendering a dehydrated watermelon with acceptable quality parameters. © 2017 Society of Chemical Industry.