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Publishing Language: Chinese

Research progress of moisture migration models in grain

Qingsong SHANG1,2, Lan WU1( ), Xiaopeng AN3
School of Mechanical and Electrical Engineering, Henan University of Technology, Zhengzhou 450001, China
College of Electrical Engineering, Henan University of Technology, Zhengzhou 450001, China
Guangdong Provincial Grain Reserve Management Group Co., Ltd., Guangzhou 510030, China
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Abstract

Food consumption patterns have been transmitted from “quantity safety” to “quality safety and nutritional balance” in the world. Precise moisture migration control is often required during post-harvest grain processing (drying and storage ventilation). Grain quality can be enhanced to reduce the economic losses. Consequently, it is very necessary to accurately regulate the moisture migration. Conventional modeling, such as porous medium and thermodynamics, has been widely used to provide valuable insights into macroscopic heat and moisture transfer patterns. The heat and moisture transfer have been significantly limited without considering several critical factors. Specifically, the moisture migration can also be governed by the pore heterogeneity, grain respiration, and the dynamic evolution of microstructures. Multi-scale modeling has emerged as a powerful alternative. The sub-models have been constructed from both microscopic and macroscopic perspectives. A systematic approach can help explore the moisture migration mechanisms during grain drying and storage ventilation. The complex interactions also occur at different scales, thus providing for more moisture migration. Various models can be integrated to more effectively capture the mechanisms of moisture migration at various scales. In this study, the existing models of the grain moisture migration were reviewed to determine their strengths and limitations. A systematic investigation was also made to explore the development and prominent features of multi-scale modeling. Its advantages were also highlighted to capture the mechanisms of moisture migration. The numerical computation and validation were offered practical guidance in the field. Furthermore, the challenges and prospects of the developing multi-scale models further advanced the application of multi-scale models during grain processing. Multi-scale modeling was also emphasized for the sub-model coupling and the modeling of microstructural heterogeneity, dynamics, and respiration. Some aspects were identified to enhance the accuracy and reliability of multi-scale models. The great contribution was then made to optimize the operational parameters of the post-harvest equipment. More precise control of moisture migration was achieved to improve the overall efficiency and quality of grain processing. Energy consumption and processing time were reduced to maintain the nutritional value and quality of the grain after optimization. Multi-scale modeling was identified as a key technical means for the quality upgrades over the entire grain industry chain. A scientific basis was provided to develop the advanced processing technologies and equipment, in order to promote the modernization and sustainability of the grain industry. This work can also offer valuable guidance for the multi-scale modeling of moisture dynamics in grain post-harvesting. Multi-scale modeling techniques can highlight the innovations during grain processing, in order to reduce the grain losses for high-quality and yield. The finding can provide a solid foundation for future research and practical applications in the field.

CLC number: S220.1 Document code: A Article ID: 1002-6819(2025)-21-0278-10

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Transactions of the Chinese Society of Agricultural Engineering
Pages 278-287

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Cite this article:
SHANG Q, WU L, AN X. Research progress of moisture migration models in grain. Transactions of the Chinese Society of Agricultural Engineering, 2025, 41(21): 278-287. https://doi.org/10.11975/j.issn.1002-6819.202503225

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Received: 28 March 2025
Revised: 05 September 2025
Published: 15 November 2025
© Chinese Society of Agricultural Engineering 2025