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Ultrasound-assisted extraction of phenolic acids, flavonols, and flavan-3-ols from muscadine grape skins and seeds using natural deep eutectic solvents and predictive modelling by artificial neural networking
The objective of this study was to investigate the extraction efficiency of 9 natural deep eutectic solvents (NDES) with the assistance of ultrasound for phenolic acids, flavonols, and flavan-3-ols in muscadine grape (Carlos) skins and seeds in comparison to 75% ethanol. Artificial neural networking...
Autores principales: | , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Elsevier
2021
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8517384/ https://www.ncbi.nlm.nih.gov/pubmed/34649165 http://dx.doi.org/10.1016/j.ultsonch.2021.105773 |
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author | Alrugaibah, Mohammed Washington, Taylor L. Yagiz, Yavuz Gu, Liwei |
author_facet | Alrugaibah, Mohammed Washington, Taylor L. Yagiz, Yavuz Gu, Liwei |
author_sort | Alrugaibah, Mohammed |
collection | PubMed |
description | The objective of this study was to investigate the extraction efficiency of 9 natural deep eutectic solvents (NDES) with the assistance of ultrasound for phenolic acids, flavonols, and flavan-3-ols in muscadine grape (Carlos) skins and seeds in comparison to 75% ethanol. Artificial neural networking (ANN) was applied to optimize NDES water content, ultrasonication time, solid-to-solvent ratio, and extraction temperature to achieve the highest extraction yields for ellagic acid, catechin and epicatechin. A newly formulated NDES (#1) consists of choline chloride: levulinic acid: ethylene glycol 1:1:2 and 20% water extracted the highest amount of ellagic acid in the skin at 22.1 mg/g. This yield was 1.73-fold of that by 75% ethanol. A modified NDES (#3) consisting of choline chloride: proline: malic acid 1:1:1 and 30% water extracted the highest amount of catechin (0.61 mg/g) and epicatechin (0.89 mg/g) in the skin, and 2.77 mg/g and 0.37 mg/g in the seed, respectively. The optimal yield of ellagic acid in the skin using NDES #1 was 25.3 mg/g (observed) and 25.3 mg/g (predicted). The optimal yield of (catechin + epicatechin) in seed using NDES #3 was 9.8 mg/g (observed) and 9.6 mg/g (predicted). This study showed the high extraction efficiency of selected NDES for polyphenols under optimized conditions. |
format | Online Article Text |
id | pubmed-8517384 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2021 |
publisher | Elsevier |
record_format | MEDLINE/PubMed |
spelling | pubmed-85173842021-10-21 Ultrasound-assisted extraction of phenolic acids, flavonols, and flavan-3-ols from muscadine grape skins and seeds using natural deep eutectic solvents and predictive modelling by artificial neural networking Alrugaibah, Mohammed Washington, Taylor L. Yagiz, Yavuz Gu, Liwei Ultrason Sonochem Original Research Article The objective of this study was to investigate the extraction efficiency of 9 natural deep eutectic solvents (NDES) with the assistance of ultrasound for phenolic acids, flavonols, and flavan-3-ols in muscadine grape (Carlos) skins and seeds in comparison to 75% ethanol. Artificial neural networking (ANN) was applied to optimize NDES water content, ultrasonication time, solid-to-solvent ratio, and extraction temperature to achieve the highest extraction yields for ellagic acid, catechin and epicatechin. A newly formulated NDES (#1) consists of choline chloride: levulinic acid: ethylene glycol 1:1:2 and 20% water extracted the highest amount of ellagic acid in the skin at 22.1 mg/g. This yield was 1.73-fold of that by 75% ethanol. A modified NDES (#3) consisting of choline chloride: proline: malic acid 1:1:1 and 30% water extracted the highest amount of catechin (0.61 mg/g) and epicatechin (0.89 mg/g) in the skin, and 2.77 mg/g and 0.37 mg/g in the seed, respectively. The optimal yield of ellagic acid in the skin using NDES #1 was 25.3 mg/g (observed) and 25.3 mg/g (predicted). The optimal yield of (catechin + epicatechin) in seed using NDES #3 was 9.8 mg/g (observed) and 9.6 mg/g (predicted). This study showed the high extraction efficiency of selected NDES for polyphenols under optimized conditions. Elsevier 2021-10-08 /pmc/articles/PMC8517384/ /pubmed/34649165 http://dx.doi.org/10.1016/j.ultsonch.2021.105773 Text en © 2021 The Author(s) https://creativecommons.org/licenses/by-nc-nd/4.0/This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/). |
spellingShingle | Original Research Article Alrugaibah, Mohammed Washington, Taylor L. Yagiz, Yavuz Gu, Liwei Ultrasound-assisted extraction of phenolic acids, flavonols, and flavan-3-ols from muscadine grape skins and seeds using natural deep eutectic solvents and predictive modelling by artificial neural networking |
title | Ultrasound-assisted extraction of phenolic acids, flavonols, and flavan-3-ols from muscadine grape skins and seeds using natural deep eutectic solvents and predictive modelling by artificial neural networking |
title_full | Ultrasound-assisted extraction of phenolic acids, flavonols, and flavan-3-ols from muscadine grape skins and seeds using natural deep eutectic solvents and predictive modelling by artificial neural networking |
title_fullStr | Ultrasound-assisted extraction of phenolic acids, flavonols, and flavan-3-ols from muscadine grape skins and seeds using natural deep eutectic solvents and predictive modelling by artificial neural networking |
title_full_unstemmed | Ultrasound-assisted extraction of phenolic acids, flavonols, and flavan-3-ols from muscadine grape skins and seeds using natural deep eutectic solvents and predictive modelling by artificial neural networking |
title_short | Ultrasound-assisted extraction of phenolic acids, flavonols, and flavan-3-ols from muscadine grape skins and seeds using natural deep eutectic solvents and predictive modelling by artificial neural networking |
title_sort | ultrasound-assisted extraction of phenolic acids, flavonols, and flavan-3-ols from muscadine grape skins and seeds using natural deep eutectic solvents and predictive modelling by artificial neural networking |
topic | Original Research Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8517384/ https://www.ncbi.nlm.nih.gov/pubmed/34649165 http://dx.doi.org/10.1016/j.ultsonch.2021.105773 |
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