Experimental investigation of convective drying behavior of in-shell hazelnuts: moisture diffusivity, transport phenomena, and pressure drop

Numerical investigation of coupled heat and mass transfer in deformable granular beds during humid-air and superheated-steam drying

Assessment of the effects of drying temperatures on effective moisture diffusion and quality properties of purple carrot slices dried by hot air method

This study examined the influence of hot-air drying temperature on the moisture ratio (MR), drying rate (DR), effective moisture diffusivity (Deff), color characteristics (L, a, b, C, and ΔE), and hardness (N) of purple carrot slices. A clear temperature-dependent response was observed for both the drying behavior and the quality attributes of the samples. Increasing the drying-air temperature resulted in a shorter drying period. The mean DR values obtained under the different drying conditions ranged from 0.0062 to 0.0201 g moisture/g dry matter·min. The calculated Deff values were within the range of 9.66 × 10⁻⁹ to 3.37 × 10⁻⁸ m²/s. Temperature also altered the color characteristics of the fresh purple carrot slices; specifically, the L and b values differed significantly from those of the fresh samples (p < 0.05). The α color values of fresh samples were preserved at 55 ºC and 65 ºC, the C color value at 55 ºC, and the ΔE color value at 55 ºC (p>0.05). The N values of fresh purple carrot slices are preserved at 75 ºC (p<0.05). Based on the findings, a temperature of 75 °C is recommended for the MR, DR, Deff, and N parameters, while a temperature of 55 °C is recommended for color characteristics.

Thin-layer drying characteristics of black solo garlic: Mathematical and ANN modelling, diffusivity, and antioxidant enhancement

Drying is a critical step in processing black solo garlic to enhance its stability and broaden its applications. This study investigated the effects of drying temperature (50–70 °C) on the convective oven drying kinetics, energy consumption, physicochemical properties, and antioxidant activity of black solo garlic slices. Drying behaviour, effective moisture diffusivity, and activation energy were evaluated. Several thin-layer models and an artificial neural network (ANN) were applied to describe the drying kinetics. Increasing drying temperature increased the drying rate, reduced drying time and energy consumption. The effective moisture diffusivity ranged from 4.16 × 10 −10 to 7.45 × 10 −10  m 2  s −1 , with an activation energy of 27.07 kJ mol −1 . Drying occurred entirely in the falling-rate period, indicating internal moisture diffusion as the dominant mechanism. The ANN model demonstrated excellent predictive performance comparable to that of the thin-layer models ( R 2 > 0.99; RMSE < 0.02). Higher drying temperatures promoted melanoidin formation and increased antioxidant activity (6.91–9.13 mg AAE/g db) while preserving phenolic content, although rehydration capacity decreased. Among the investigated conditions, 70 °C provided the best overall balance for the production of dried black solo garlic as a functional food ingredient. These findings demonstrate the potential of combining thin-layer mathematical modelling and ANN to optimise industrial drying processes for black solo garlic.

Integrated CFD simulation and thermal imaging for monitoring convective drying of tomato wedges

The overarching aim of this study was to develop and validate a computational fluid dynamics (CFD) model to predict heat and mass transfer processes during the convective drying of tomato wedges. Experimental drying trials were conducted at three air temperatures (60, 70, and 80 °C) to evaluate model performance by monitoring drying kinetics under controlled conditions. During the drying process, the moisture content of tomato wedges was reduced from an initial value of 15.67 kg water/kg dry matter to a final value of 0.17 kg water/kg dry matter, requiring 21, 13, and 11 h at 60, 70, and 80 °C, respectively. Spatiotemporal surface temperature distributions were continuously obtained from radiometric infrared thermography recorded by a highly sensitive thermal camera and was used for monitoring of temperature changes and for CFD model validation. The results revealed that a close correspondence was observed between experimental data and simulated results across all operating drying temperatures, with improved predictive accuracy observed at lower temperatures. The model also demonstrated good predictive performance for moisture content during drying, with root-mean-square error (RMSE), and chi-square (χ2) values of 0.812 and 0.313, respectively. Additionally, color change, lycopene content, antioxidant activity, and total phenols were determined to evaluate the impact of drying temperatures on tomato quality. Drying air temperature of 70 °C resulted in the highest lycopene retention and lower color change, while a higher temperature of 80 °C showed lower degradation of antioxidant activity and phenols, indicating that drying temperature not only affects drying rate but also influences the nutritional and quality values. Overall, the developed CFD model can serve as a robust tool for analyzing and predicting the drying behavior of tomato wedges, improving process optimization, quality preservation, and enhanced control of drying operations.

Hybrid infrared-hot air drying of cardamom: kinetic modeling, optimization, and quality assessment

Influence of climatic conditions on moisture storage in bio-based multilayer walls: a coupled heat and moisture transfer study