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.
Keywords: back-propagation; codonopsis pilosula; moisture ratio; sparrow search algorithm; ultrasonic.
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