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Drying characteristics and neural network models of contact ultrasound strengthened cold air drying on yam

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Abstract:

In order to explore the strengthening effect of contact ultrasound on cold air drying(CAD) of yam, contact ultrasound strengthened cold air drying (CUCAD) experiments were carried out. The effects of ultrasonic power and cold air temperature on drying characteristics, microstructure and effective moisture diffusivity were studied, and the drying process was simulated by BP, RBF, Elman and RNN neural network models. The results showed that increasing ultrasonic power and drying temperature could significantly shorten the drying time of yam, facilitate the formation and expansion of micropores, and improve the internal mass and heat transfer of material. With the decrease of water content, the drying rate gradually decreased. The prediction performance results of the four neural network models were compared, and the RNN network model could achieve the highest fitting accuracy for the prediction of CUCAD process of yam. Therefore, contact ultrasound could achieve a significant strengthening effect during CUCAD process.

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Acknowledgements

The authors are thankful to the financial supporting from the College’s Innovation Talents Program in Henan (19HASTIT013) and the Henan Science and Technology Research Project (212102110080).

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Authors and Affiliations

  1. College of Food & Bioengineering, Henan University of Science and Technology, 471003, Luoyang, China

    Ziyu Li, Yinping Wang, Qingqing Shi, Jiaqi Gao, Chenlu Zhang, Xiaoyan Fan & Yunhong Liu

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  1. Ziyu Li
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Li, Z., Wang, Y., Shi, Q. et al. Drying characteristics and neural network models of contact ultrasound strengthened cold air drying on yam. Heat Mass Transfer 59, 1109–1120 (2023). https://doi.org/10.1007/s00231-022-03323-x

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