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Optimization of Ultrasound-Assisted Extraction Condition for Phenolic Compounds Antioxidant Activity and Epigallocatechin Gallate in Lipid-Extracted Microalgae

机译:超声辅助脂质提取微藻中酚类化合物抗氧化活性和表没食子儿茶素没食子酸酯的提取条件的优化

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摘要

Lipid-extracted microalgae (LEM, KCTC 12236BP), a solid waste by-product obtained from algal biodiesel production, is typically considered a rich source of antioxidant compounds, including phenolic compounds. The purpose of this study was to apply a statistically-based methodology to enhance the extraction of total phenolic compounds (TPCs) and antioxidant activity (AA) from LEM and to verify the production of epigallocatechin gallate (EGCG), a bioactive material, under optimum conditions. The optimal extractions of TPC and AA were explored by varying the key variables, including the extraction temperature, ethanol concentration, extraction time, and ultrasonic power, through statistical optimization. The optimal extraction conditions were identified through 27 runs following the central composite design. The regression analyses of TPC and AA showed good fit of the experimental data to the second-order polynomial models, with coefficient of determination (R ) values of 0.8769 and 0.8432, respectively. In the variation experiment, the maximum TPC and AA values of 9.8 mg GAE/g and 91.8% were obtained respectively with an extraction temperature of 74.4 °C, ethanol concentration of 55.4%, extraction time of 59.6 min, and ultrasonic power of 700 W. HPLC coupled with diode array detection was used to identify and quantify the phenolic compounds in the extracts, and EGCG (0.12 mg/g DM) was identified as a major peak in the analysis, demonstrating that high value-added material with a bioactive property can be produced from LEM. The results indicated that statistical optimization is applicable for optimizing the extraction of TPC and AA from LEM and provided a scientific basis for applying ultrasound-assisted extraction on an industrial scale by optimizing the conditions. LEM has a high TPC value, particularly with regard to EGCG, and excellent AA, considering it is highly used as a functional material for food, cosmetics, and medicine.
机译:脂质提取的微藻类(LEM,KCTC 12236BP)是藻类生物柴油生产获得的固体废物副产物,通常被认为是抗氧化剂化合物(包括酚类化合物)的丰富来源。这项研究的目的是应用基于统计的方法,以增强LEM中总酚类化合物(TPC)的提取和抗氧化活性(AA),并验证在最佳条件下生物活性物质表没食子儿茶素没食子酸酯(EGCG)的产生条件。通过统计优化改变关键参数,包括提取温度,乙醇浓度,提取时间和超声功率,探索了TPC和AA的最佳提取方法。通过中央复合设计,通过27次运行确定了最佳提取条件。 TPC和AA的回归分析表明实验数据与二阶多项式模型非常吻合,确定系数(R)值分别为0.8769和0.8432。在变异实验中,萃取温度为74.4°C,乙醇浓度为55.4%,萃取时间为59.6 min,超声功率为700 W,分别获得的最大TPC和AA值为9.8 mg GAE / g和91.8%。 。HPLC结合二极管阵列检测技术用于鉴定和定量提取物中的酚类化合物,EGCG(0.12 mg / g DM)被鉴定为分析中的主要峰,表明具有生物活性的高附加值材料可以从LEM生产。结果表明,统计优化方法适用于从LEM中提取TPC和AA的提取,并通过优化条件为工业规模的超声辅助提取提供了科学依据。考虑到LEM被高度用作食品,化妆品和药品的功能材料,LEM具有很高的TPC值,尤其是在EGCG方面,并且具有出色的AA。

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