Drying kinetics prediction and quality effect of ultrasonic synergy vacuum far‐infrared drying of Codonopsis pilosula

Abstract

By using ultrasonic synergy vacuum far‐infrared drying (US‐VFID), the effects of different conditions on the drying kinetics, functional properties, and microstructure of Codonopsis pilosula slices were studied. The sparrow search algorithm (SSA) was used to optimize the back‐propagation (BP) neural network to predict the moisture ratio during drying. With the increase of ultrasonic frequency, power and radiation temperature, the drying time of C. pilosula was shortened. The drying time of US‐VFID was 25% shorter than VFID, when radiation temperature was 50°C, ultrasonic power was 48 W, and frequency was 28 kHz. The SSA‐BP neural network, the average absolute error prediction was 0.0067. Compared with hot air drying (HAD), the total phenolic content and antioxidant activity of C. pilosula by US‐VFID were increased by 29.47% and 8.67%, respectively, and a reduction in color contrast of 16.19%. The dilation and generation of microcapillary of C. pilosula were more obvious. The study revealed US‐VFID could be used for the selection and process control of agro‐processing methods for C. pilosula products.

Drying Characteristics of Moutan Cortex by Rotary Wheel Microwave Vacuum Drying and Its Influence on Quality

“…The fitness curve illustrates the efficiency and capability of the NGO-BP neural network, as depicted in Figure 4b, showcasing rapid convergence and high accuracy after approximately 40 evolutions. The mean absolute error (MAE) was utilized as a criterion for evaluating the prediction results of the model [25], and the optimized MAE prediction values of the BP neural network and NGO-BP neural network were 0.01393 and 0.01346, which indicated that the NGO-BP neural network model could obtain a better prediction of the water ratio. The predicted and experimental values for the test dataset are shown in Figure 4c, where the experimental values and the moisture ratios predicted by NGO-BP are in good agreement and the model is well fitted.…”