Ultrasound-assisted medium-wave infrared drying performance of Phyllanthus emblica and artificial neural network modeling

The medium-wave infrared drying performance of Phyllanthus emblica under different ultrasonic pre-treatment conditions were investigated in this paper. The effects of drying temperature (50 degree celsius, 60 degree celsius, 70 degree celsius), maximum operating infrared power (500 W, 1000 W, 1500 W), ultrasonic pre-treatment time (4 min, 7 min, 10 min) and power (200 W, 300 W, 400 W) on the drying performance were evaluated. It was found that an increase in drying temperature and a decrease in maximum operating infrared power could improve the drying rate and reduce the energy consumption and color change of the dried product, and the drying performance of Phyllanthus emblica can be maximized using the right ultrasonic pre-treatment time and ultrasonic power. The thin-layer drying model, BP-ANN model, and PSO-BP-ANN model were adopted to predict the moisture content variation of ultrasonically pre-treated Phyllanthus emblica in medium-wave infrared drying. The results indicated that the PSO-BP-ANN model fitted the experimental data best.