首页|Optimization of ultrasound-assisted extraction of bitter compounds and polyphenols from willow gentian underground parts

Optimization of ultrasound-assisted extraction of bitter compounds and polyphenols from willow gentian underground parts

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Willow gentian (Gentiana asclepiadea L., Gentianaceae) is a medicinal plant that is primarily used in the treat-ment of gastrointestinal and liver diseases in folk medicine. As a bitter raw material, it is also used in the food industry for liquors flavoring. In order to optimize the ultrasound-assisted extraction (UAE) of gentiopicroside, isovitexin, isoorientin, and isogentisin, as well as total polyphenols from the underground parts of willow gentian, the influence of process parameters was investigated. Extraction time (from 5 to 65 min), ethanol concentration (from 10 to 90% v/v), solid to liquid ratio (from 1:10 to 1:50 w/v), and extraction temperature (from 20 to 80 degrees C) were estimated at five levels as independent variables. The response surface methodology (RSM) and the artificial neural network (ANN) approach were employed to develop a predictive extraction model and to establish optimal extraction conditions to simultaneously maximize the extraction yield of all target compounds. Established optimal values of process parameters were: extraction time 50 min, ethanol concen-tration 53% (v/v), solid to liquid ratio 1:40 (w/v), and extraction temperature 65 degrees C. The obtained extraction yields under predicted optimal conditions for gentiopicroside (49.23 mg/g DW), isoorientin (1.00 mg/g DW), isovitexin (4.04 mg/g DW), isogentisin (1.14 mg/g DW), and TPC (10.03 mg of GAE/g DW) confirmed the adequacy of both RSM and ANN models. Compared with the RSM model, the ANN model fitted better with the experimental values of each compound (higher coefficient of determination and lower mean absolute deviation) indicating its higher predictive capacity. The developed high-accuracy extraction model provides the basis for further separation and purification, as well as for studying the bioactivity of selected compounds from under -ground parts of G. asclepiadea.

Gentiana asclepiadeaModellingArtificial neural networkResponse surface methodologyGreen extractionANTIOXIDANT

Matejic, Jelena、Kitic, Dusanka、Bigovic, Dubravka、Savikin, Katarina、Jovanovic, Milos、Mudric, Jelena、Drinic, Zorica

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Univ Nis

Inst Med Plants Res Dr Josif Pancic

2022

Separation and Purification Technology

Separation and Purification Technology

EISCI
ISSN:1383-5866
年,卷(期):2022.281
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