Optimization of ultrasonic-assisted extraction of total flavonoids from Oxalis corniculata by a hybrid response surface methodology-artificial neural network-genetic algorithm (RSM-ANN-GA) approach, coupled with an assessment of antioxidant activities†

Deng-Zhao Jiang, Dan-Ping Yu, Ming Zeng, Wen-Bo Liu, Dong-Lin Li, Ke-Yue Liu · 2024

Read Optimization of ultrasonic-assisted extraction of total flavonoids from Oxalis corniculata by a hybrid response surface methodology-artificial neural network-genetic algorithm (RSM-ANN-GA) approach, coupled with an assessment of antioxidant activities† by Deng-Zhao Jiang, Dan-Ping Yu, Ming Zeng, Wen-Bo Liu, Dong-Lin Li, Ke-Yue Liu (2024) in the Tower of Babel, a free online library of public-domain works preserved in clean, searchable text. No sign-up. The full text is served as a plain-text file at a predictable URL, where text is present: https://antarctic-labs.com/tower-of-babel/pmc-11629873.txt.

Description

Deng-Zhao Jiang and co-authors tune an ultrasound method to pull flavonoids from a small creeping herb, in a 2024 study. The herb, Oxalis corniculata, holds flavonoids prized as natural antioxidants. Getting more of them out, with less waste, takes the right blend of alcohol strength, liquid ratio, power, and time. The team pitted a classic tuning method against a hybrid that adds a neural network and a genetic search.

The hybrid found a slightly better recipe and foresaw yields with sharper accuracy. Its best mix used mid-strength alcohol, a lean liquid ratio, and about an hour of ultrasound near top power. The plain method's best mix sat close by, at a hair lower yield. The extract then mopped up three kinds of free radicals in dish tests. The authors pitch both the recipe and the plant as a source of natural antioxidants.

Catalog record

CREATORDeng-Zhao Jiang, Dan-Ping Yu, Ming Zeng, Wen-Bo Liu, Dong-Lin Li, Ke-Yue Liu
YEAR2024
COLLECTIONPAPERS
FORMATTXT
FILE SIZE40 KB
VERSION1.0
LICENSECC BY 4.0
RIGHTSCC BY
SOURCEEurope PMC

Source: https://europepmc.org/articles/PMC11629873

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