Modeling of Microwave Vacuum Drying Kinetics of Bael (<italic>Aegle marmelos</italic> L.) Pulp by Using Artificial Neural Network: Fid-Bau Portal

Modeling of Microwave Vacuum Drying Kinetics of Bael (Aegle marmelos L.) Pulp by Using Artificial Neural Network

Dash, Kshirod K. / Chakraborty, S. / Singh, Y. R.

In microwave vacuum drying, the microwave energy was mainly absorbed by liquid water present in food that results in the temperature to rise, resulting in drying of bael pulp. In this study, modeling of microwave vacuum drying kinetics and effective moisture diffusivity of bael pulp was investigated. The effect of microwave power varying between 400 and 800 W and vacuum levels between 380 and 680 mm Hg was studied on the thin-layer drying kinetics of the extracted bael pulp. The drying kinetics of bael pulp during microwave vacuum drying was modeled by using artificial neural network. The artificial neural network with a topology of 3-6-1, transfer function of tansig and the Levenberg–Marquardt training algorithm showed the best performance with the minimum mean square error value. The microwave vacuum drying reduced the moisture content of the bael pulp from 3.84 kg water/kg dry matter to 0.09 kg water/kg dry matter. The values of effective moisture diffusivity were increased from 1.12 × 10⁻⁹ to 1.92 × 10⁻⁹ m²/s when microwave powers were increased from 400 to 800 W at the vacuum level of 380 mm Hg vacuum. Increase in the vacuum level from 380 to 680 mm Hg at power level of 800 W increased the effective moisture diffusivity from 1.92 × 10⁻⁹ to 2.19 × 10⁻⁹ m²/s, resulting in reduction in drying time. The microwave power and vacuum level was fitted with effective diffusivity by a nonlinear model. The model showed that both parameters have a positive effect on effective diffusivity, and hence, an increasing trend of effective diffusivity with the increase in microwave power and vacuum levels was observed.