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A Heat and Mass Transfer Model of Peanut Convective Drying Based on a Two-Component Structure
In order to optimize the convective drying process parameters of peanuts and to provide a theoretical basis for the scientific use of energy in the drying process, this study took single-particle peanuts as the research object and analyzed the heat and mass transfer process during convective drying....
Autores principales: | , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
MDPI
2023
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10178041/ https://www.ncbi.nlm.nih.gov/pubmed/37174361 http://dx.doi.org/10.3390/foods12091823 |
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author | Chen, Pengxiao Chen, Nan Zhu, Wenxue Wang, Dianxuan Jiang, Mengmeng Qu, Chenling Li, Yu Zou, Zhuoyun |
author_facet | Chen, Pengxiao Chen, Nan Zhu, Wenxue Wang, Dianxuan Jiang, Mengmeng Qu, Chenling Li, Yu Zou, Zhuoyun |
author_sort | Chen, Pengxiao |
collection | PubMed |
description | In order to optimize the convective drying process parameters of peanuts and to provide a theoretical basis for the scientific use of energy in the drying process, this study took single-particle peanuts as the research object and analyzed the heat and mass transfer process during convective drying. In addition, a 3D two-component moisture heat transfer model for peanuts was constructed based on the mass balance and heat balance theorem. Moreover, the changes in the internal temperature and concentration fields of peanut pods during the whole drying process were investigated by simulations using COMSOL Multiphysics. The model was validated by thin-layer drying experiments, compared with the one-component model, and combined with low-field NMR technology to further analyze the internal moisture distribution state of peanut kernel drying process. The results show that both models can effectively simulate the peanut thin-layer drying process, and consistency is found between the experimental and simulated values, with the maximum errors of 10.25%, 9.10%, and 7.60% between the simulated moisture content and the experimental values for the two-component model, peanut shell, and peanut kernel models, respectively. Free water and part of the weakly bound water was the main water lost by peanuts during the drying process, the change in oil content was small, and the bound water content was basically unchanged. The results of the study provide a theoretical basis to accurately predict the moisture content within different components of peanuts and reveal the mechanism of moisture and heat migration during the drying process of peanut pods. |
format | Online Article Text |
id | pubmed-10178041 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2023 |
publisher | MDPI |
record_format | MEDLINE/PubMed |
spelling | pubmed-101780412023-05-13 A Heat and Mass Transfer Model of Peanut Convective Drying Based on a Two-Component Structure Chen, Pengxiao Chen, Nan Zhu, Wenxue Wang, Dianxuan Jiang, Mengmeng Qu, Chenling Li, Yu Zou, Zhuoyun Foods Article In order to optimize the convective drying process parameters of peanuts and to provide a theoretical basis for the scientific use of energy in the drying process, this study took single-particle peanuts as the research object and analyzed the heat and mass transfer process during convective drying. In addition, a 3D two-component moisture heat transfer model for peanuts was constructed based on the mass balance and heat balance theorem. Moreover, the changes in the internal temperature and concentration fields of peanut pods during the whole drying process were investigated by simulations using COMSOL Multiphysics. The model was validated by thin-layer drying experiments, compared with the one-component model, and combined with low-field NMR technology to further analyze the internal moisture distribution state of peanut kernel drying process. The results show that both models can effectively simulate the peanut thin-layer drying process, and consistency is found between the experimental and simulated values, with the maximum errors of 10.25%, 9.10%, and 7.60% between the simulated moisture content and the experimental values for the two-component model, peanut shell, and peanut kernel models, respectively. Free water and part of the weakly bound water was the main water lost by peanuts during the drying process, the change in oil content was small, and the bound water content was basically unchanged. The results of the study provide a theoretical basis to accurately predict the moisture content within different components of peanuts and reveal the mechanism of moisture and heat migration during the drying process of peanut pods. MDPI 2023-04-28 /pmc/articles/PMC10178041/ /pubmed/37174361 http://dx.doi.org/10.3390/foods12091823 Text en © 2023 by the authors. https://creativecommons.org/licenses/by/4.0/Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https://creativecommons.org/licenses/by/4.0/). |
spellingShingle | Article Chen, Pengxiao Chen, Nan Zhu, Wenxue Wang, Dianxuan Jiang, Mengmeng Qu, Chenling Li, Yu Zou, Zhuoyun A Heat and Mass Transfer Model of Peanut Convective Drying Based on a Two-Component Structure |
title | A Heat and Mass Transfer Model of Peanut Convective Drying Based on a Two-Component Structure |
title_full | A Heat and Mass Transfer Model of Peanut Convective Drying Based on a Two-Component Structure |
title_fullStr | A Heat and Mass Transfer Model of Peanut Convective Drying Based on a Two-Component Structure |
title_full_unstemmed | A Heat and Mass Transfer Model of Peanut Convective Drying Based on a Two-Component Structure |
title_short | A Heat and Mass Transfer Model of Peanut Convective Drying Based on a Two-Component Structure |
title_sort | heat and mass transfer model of peanut convective drying based on a two-component structure |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10178041/ https://www.ncbi.nlm.nih.gov/pubmed/37174361 http://dx.doi.org/10.3390/foods12091823 |
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