响应面优化超声提取绿色棉纤维总黄酮
Extraction of total flavonoids from green cotton fiber by ultrasonic-based response surface optimization
陈沛 1鲍军秀 1王斐 2汤寿伍 3刘海峰 3李鸿彬4
作者信息
- 1. 石河子大学生命科学学院,新疆石河子 832003
- 2. 石河子大学生命科学学院,新疆石河子 832003;绿洲城镇与山盆系统生态兵团重点实验室,新疆石河子 832000;新疆植物药资源利用教育部重点实验室,新疆石河子 832000
- 3. 中国彩棉(集团)股份有限公司,乌鲁木齐 830001
- 4. 石河子大学生命科学学院,新疆石河子 832003;绿洲城镇与山盆系统生态兵团重点实验室,新疆石河子 832000;新疆植物药资源利用教育部重点实验室,新疆石河子 832000;中国彩棉(集团)股份有限公司,乌鲁木齐 830001
- 折叠
摘要
[目的]优化超声提取绿色棉纤维中总黄酮工艺条件,为合理利用及鉴别天然绿色棉纤维提供依据.[方法]以天然绿色棉纤维为原料,利用超声空化效应加速黄酮溶解于乙醇中,在单因素试验基础上,结合Box-Benhnken中心组合原理及响应面设计优化试验条件.[结果]料液比为 1∶50 g/mL时,总黄酮得率达到最大值,提取最适料液比为1∶50 g/mL,响应面试验中建立的模型的CV值=0.87%,影响绿色棉纤维总黄酮得率的顺序为提取时间>乙醇浓度>料液比,A料液比为1∶50 g/mL、B乙醇浓度50%、C提取时间50 min为最佳提取条件.[结论]超声波法提取绿色棉纤维总黄酮的最佳条件参数为料液比1∶50 g/mL、乙醇浓度50%、提取时间50 min;获得平均总黄酮得率为5.25%.
Abstract
[Objective]This study is to optimize ultrasonic extraction conditions of total flavonoids in NGC fibers,in the hope of providing the basis for reasonable utilization and identification of NGC fibers.[Methods]The NGC fibers were used as raw materials and were utilized for total flavonoids extract by ultra-sonic cavitation effect to accelerate the dissolution of flavonoids in ethanol,to optimize the experimental condi-tions with Box-Benhnken center combination principle and response surface design.[Results]The optimal extraction conditions were as follows:solid-liquid ratio of 1∶50 g/mL,ethanol concentration of 50%,and ex-traction time of 50 min.Under these conditions,the average yield of total flavonoids was 5.25%,which was the best condition for the extraction of total flavonoids from NGC fibers by ultrasonic method.[Conclusion]The optimal condition Parameter for ultrasonic extraction of total flavonoids from green cotton fibers is a liquid to material ratio of 1∶50 g/mL,ethanol concentration50%,extraction time50 min,obtaining an average total fla-vonoid yield of 5.25%.
关键词
绿色棉纤维/总黄酮/响应面法/最佳提取条件/超声波细胞破碎Key words
green cotton fiber/total flavonoids/response surface method/optimum extraction condition/ultrasionic cell-break引用本文复制引用
基金项目
新疆维吾尔自治区创新环境建设专项(2020D14035)
新疆生产建设兵团科技攻关与成果转化项目(2016AC017)
出版年
2024
国家科技期刊平台
NSTL
万方数据