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Mechanism modeling and application of Salvia miltiorrhiza percolation process
Percolation is a common extraction method of food processing industry. In this work, taking the percolation extraction of salvianolic acid B from Salvia miltiorrhiza (Salviae Miltiorrhizae Radix et Rhizoma) as an example, the percolation mechanism model was derived. The volume partition coefficient...
Autores principales: | , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Nature Publishing Group UK
2023
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10205710/ https://www.ncbi.nlm.nih.gov/pubmed/37221365 http://dx.doi.org/10.1038/s41598-023-35529-2 |
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author | Wang, Wanying Ding, Feng Qu, Haibin Gong, Xingchu |
author_facet | Wang, Wanying Ding, Feng Qu, Haibin Gong, Xingchu |
author_sort | Wang, Wanying |
collection | PubMed |
description | Percolation is a common extraction method of food processing industry. In this work, taking the percolation extraction of salvianolic acid B from Salvia miltiorrhiza (Salviae Miltiorrhizae Radix et Rhizoma) as an example, the percolation mechanism model was derived. The volume partition coefficient was calculated according to the impregnation. experiment. The bed layer voidage was measured by single-factor percolation experiment and the internal mass transfer coefficient was calculated by the parameters obtained by fitting the impregnation kinetic model. After screening, the Wilson and Geankoplis, and Koch and Brady formulas were used to calculate the external mass transfer coefficient and the axial diffusion coefficient, respectively. After substituting each parameter into the model, the process of percolation of Salvia miltiorrhiza was predicted, and the coefficient of determination R(2) was all greater than 0.94. Sensitivity analysis was used to show that all the parameters studied had a significant impact on the prediction effect. Based on the model, the design space including the range of raw material properties and process parameters was established and successfully verified. At the same time, the model was applied to the quantitative extraction and endpoint prediction of the percolation process. |
format | Online Article Text |
id | pubmed-10205710 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2023 |
publisher | Nature Publishing Group UK |
record_format | MEDLINE/PubMed |
spelling | pubmed-102057102023-05-25 Mechanism modeling and application of Salvia miltiorrhiza percolation process Wang, Wanying Ding, Feng Qu, Haibin Gong, Xingchu Sci Rep Article Percolation is a common extraction method of food processing industry. In this work, taking the percolation extraction of salvianolic acid B from Salvia miltiorrhiza (Salviae Miltiorrhizae Radix et Rhizoma) as an example, the percolation mechanism model was derived. The volume partition coefficient was calculated according to the impregnation. experiment. The bed layer voidage was measured by single-factor percolation experiment and the internal mass transfer coefficient was calculated by the parameters obtained by fitting the impregnation kinetic model. After screening, the Wilson and Geankoplis, and Koch and Brady formulas were used to calculate the external mass transfer coefficient and the axial diffusion coefficient, respectively. After substituting each parameter into the model, the process of percolation of Salvia miltiorrhiza was predicted, and the coefficient of determination R(2) was all greater than 0.94. Sensitivity analysis was used to show that all the parameters studied had a significant impact on the prediction effect. Based on the model, the design space including the range of raw material properties and process parameters was established and successfully verified. At the same time, the model was applied to the quantitative extraction and endpoint prediction of the percolation process. Nature Publishing Group UK 2023-05-23 /pmc/articles/PMC10205710/ /pubmed/37221365 http://dx.doi.org/10.1038/s41598-023-35529-2 Text en © The Author(s) 2023 https://creativecommons.org/licenses/by/4.0/Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/ (https://creativecommons.org/licenses/by/4.0/) . |
spellingShingle | Article Wang, Wanying Ding, Feng Qu, Haibin Gong, Xingchu Mechanism modeling and application of Salvia miltiorrhiza percolation process |
title | Mechanism modeling and application of Salvia miltiorrhiza percolation process |
title_full | Mechanism modeling and application of Salvia miltiorrhiza percolation process |
title_fullStr | Mechanism modeling and application of Salvia miltiorrhiza percolation process |
title_full_unstemmed | Mechanism modeling and application of Salvia miltiorrhiza percolation process |
title_short | Mechanism modeling and application of Salvia miltiorrhiza percolation process |
title_sort | mechanism modeling and application of salvia miltiorrhiza percolation process |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10205710/ https://www.ncbi.nlm.nih.gov/pubmed/37221365 http://dx.doi.org/10.1038/s41598-023-35529-2 |
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