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首页> 外文期刊>Journal of Microbiology, Biotechnology and Food Sciences >OPTIMIZATION OF ANTIOXIDANT EXTRACTION FROM KALUMPIT (TERMINALIA MICROCARPA DECNE) FRUITS
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OPTIMIZATION OF ANTIOXIDANT EXTRACTION FROM KALUMPIT (TERMINALIA MICROCARPA DECNE) FRUITS

机译:Kalumpit(末端​​Microcarpa Degne)抗氧化提取的优化

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The effects of extraction parameters, including temperature (25 – 80 °C), time (30 – 90 min), solvent to sample (S/S) ratio (10 – 50 mL g-1), initial pH (3 - 8) and ethanol concentration (20 – 100%), on the % 2,2-Diphenyl-1-picrylhydrazyl (DPPH) radical scavenging activity of kalumpit were screened and optimized using 2-level factorial design and Box-Behnken design (BBD) of experiments. Temperature, S/S ratio, and ethanol concentration exhibited significant effects on the % DPPH radical scavenging activity of kalumpit extract. Response surface models developed for % DPPH and 2,2-azino-bis-3-ethylbenzothiazoline-6-sulfonic acid (ABTS) radical scavenging activities of kalumpit fruit extract adequately fit and were used to determine the optimum extraction conditions. A desirability function approach determined the optimum conditions for solvent extraction of antioxidants at 80.0 °C, 10 mL g-1 S/S, and 51.66% ethanol concentration. This resulted in a maximum desirability value of 0.977 and predicted % DPPH and ABTS radical scavenging activities of 66.63 and 82.14, respectively. Validation of the adequacy of the predictive models showed no significant difference between experimental data and predicted values (p 0.05), indicating that the models developed were adequate in describing the relationship between factors and responses.
机译:提取参数的影响,包括温度(25-80℃),时间(30-90分钟),溶剂对样品(S / S)比(10-50mL G-1),初始pH(3-8)和乙醇浓度(20-100%),在筛选和优化Kalumpit的%2,2-二苯基-1-富铬酰基(DPPH)自由基清除活性,使用2级因子设计和箱Behnken设计(BBD)的实验进行了优化。温度,S / S比和乙醇浓度对Kalumpit提取物的%DPPH自由基清除活性表现出显着影响。响应表面模型为%DPPH和2,2-氮杂-PIS-3-乙基苯并噻唑啉-6-磺酸(ABTS)自由基清除激发活性的Kalumpit水果提取物充分适合,用于确定最佳提取条件。期望功能方法确定80.0℃,10mL G-1 S / S和51.66%乙醇浓度下溶氧化剂的溶剂萃取的最佳条件。这导致最大的期望值为0.977并预测%DPPH,分别为66.63和82.14的激进清除活性。验证预测模型的充分性显示在实验数据和预测值之间没有显着差异(P> 0.05),表明所开发的模型是充分描述因素和反应之间的关系。

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