Optimization of accelerated solvent extraction of ellagitannins in black raspberry seeds using artificial neural network coupled with genetic algorithm

被引：24

作者：

Lee, Ga Eun ^{[1
,2
,3
]}

Kim, Ryun Hee ^{[1
,2
,3
]}

Lim, Taehwan ^{[4
]}

Kim, Jaecheol ^{[1
,2
,3
]}

Kim, Suna ^{[5
]}

Kim, Hyoung-Geun ^{[6
,7
]}

Hwang, Keum Taek ^{[1
,2
,3
]}

机构：

[1] Seoul Natl Univ, Dept Food & Nutr, Seoul 08826, South Korea

[2] Seoul Natl Univ, Res Inst Human Ecol, Seoul 08826, South Korea

[3] Seoul Natl Univ, BK21 FOUR Educ & Res Team Sustainable Food & Nutr, Seoul 08826, South Korea

[4] Tufts Univ, Dept Biomed Engn, 4 Colby St, Medford, MA 02155 USA

[5] Korea Natl Open Univ, Coll Nat Sci, Div Human Ecol, Seoul 03078, South Korea

[6] Kyung Hee Univ, Grad Sch Biotechnol, Yongin 17104, South Korea

[7] Kyung Hee Univ, Dept Oriental Med Biotechnol, Yongin 17104, South Korea

来源：

FOOD CHEMISTRY | 2022年 / 396卷

基金：

新加坡国家研究基金会;

关键词：

Black raspberry seeds; Ellagitannin; Accelerated solvent extraction; Artificial neural network; Genetic algorithm; Optimization; SANGUIIN H-6; HYDROLYZABLE TANNINS; ELLAGIC ACID; ANTIOXIDANT; IDENTIFICATION; PEDUNCULAGIN; RECEPTOR; WINE; WOOD; L;

D O I：

10.1016/j.foodchem.2022.133712

中图分类号：

O69 [应用化学];

学科分类号：

081704 ;

摘要：

This study aimed to identify ellagitannins in black raspberry seeds (BRS) and to optimize accelerated solvent extraction of ellagitannins using an artificial neural network (ANN) coupled with genetic algorithm. Fifteen monomeric and dimeric ellagitannins were identified in BRS. For ANN modeling, extraction time, extraction temperature, and solvent concentration were set as input variables, and total ellagitannin content was set as output variable. The trained ANN had a mean squared error value of 0.0102 and a regression correlation coefficient of 0.9988. The predicted optimal extraction conditions for maximum total ellagitannin content were 63.7% acetone, 4.21 min, and 43.9 degrees C. The actual total ellagitannin content under the optimal extraction conditions was 13.4 +/- 0.0 mg/g dry weight, and the prediction error was 0.75 +/- 0.27%. This study is the first attempt to analyze the composition of ellagitannins in BRS and to determine optimal extraction conditions for maximum total ellagitannin content from BRS.

引用

页数：9