Machine learning-aided enhancement of white tea extraction efficiency using hybridized GMDH models in microwave-assisted extraction.
GMDH
Genetic algoritm
Harmony search
Microwave assisted extraction
White tea
Journal
Scientific reports
ISSN: 2045-2322
Titre abrégé: Sci Rep
Pays: England
ID NLM: 101563288
Informations de publication
Date de publication:
29 10 2024
29 10 2024
Historique:
received:
25
08
2024
accepted:
23
10
2024
medline:
29
10
2024
pubmed:
29
10
2024
entrez:
29
10
2024
Statut:
epublish
Résumé
White tea is valuable for having a high antioxidant content, which is considered to possess numerous beneficial effects on health. This study investigated the application of microwave-assisted extraction (MAE) for the extraction of total phenolic compounds from white tea. The experimental setup included four independent variables: microwave power (ranging from 100 to 300 W), extraction time (ranging from 10 to 40 min), temperature (ranging from 35 to 50 °C), and the ratio of food to solvent (ranging from 0.25 to 0.5 g/10 mL). The responses that were evaluated were IC
Identifiants
pubmed: 39468319
doi: 10.1038/s41598-024-77579-0
pii: 10.1038/s41598-024-77579-0
doi:
Substances chimiques
Tea
0
Phenols
0
Plant Extracts
0
Antioxidants
0
Types de publication
Journal Article
Langues
eng
Sous-ensembles de citation
IM
Pagination
25900Informations de copyright
© 2024. The Author(s).
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