Modeling and Optimization of Microwave Vacuum Drying for Pinelliae Rhizoma: Integrating Drying Kinetics, Artificial Neural Networks, and Quality Preservation

文献类型: 外文期刊

第一作者: Wang, Pan

作者: Wang, Pan;Yang, Xiaoping;Huang, Xiaopeng;Ma, Guojun;Zhu, Zewen;Xu, Yanrui;Zang, Zepeng;Liu, Xu;Zhang, Shidong;Wang, Siqi;Wang, Ming

作者机构:

关键词: artificial neural networks; drying characteristics; microstructure; microwave vacuum drying; Pinellia ternata (Thunb.) Breit; Pinelliae Rhizoma

期刊名称:FOOD SCIENCE & NUTRITION ( 影响因子:3.8; 五年影响因子:4.5 )

ISSN: 2048-7177

年卷期: 2025 年 13 卷 8 期

页码:

收录情况: SCI

摘要: This study investigated the effects of drying temperature and vacuum degree on the drying characteristics, color, rehydration ratio, nucleoside content, and microstructure of Pinelliae Rhizoma (PR) during microwave-vacuum drying (MVD). The results demonstrated that MVD significantly reduced the drying time and enhanced processing efficiency. Four different mathematical models and artificial neural network (ANN) predictive models are developed for further comparison. Among the models, the Midilli model provided the best fit for all samples (R 2 = 0.99012, Pearson's r = 0.99509). However, the ANN approach has shown a better performance than the Midilli model. MVD resulted in a decrease in L* values, an increase in a* and b* values, and a higher BI index in dried Pinelliae Rhizoma (PR). No significant difference was observed in Delta E, indicating that the combined effects of temperature, vacuum degree, pigment stability, and water migration led to a similar degree of color change. Principal component analysis (PCA) and Pearson's correlation analysis revealed that MVD drying at 40 degrees C and -60 kPa were the optimal conditions for efficiently drying Pinelliae Rhizoma (PR). Under this condition, most nucleosides are well preserved with the exception of adenosine. Overall, MVD technology, as demonstrated in this study, is a promising and suitable drying method in terms of processing efficiency for Pinelliae Rhizoma (PR).

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