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通过响应表面方法学来增值Cistus, Acacia和Lemon verbena:优化研究和在制药和营养药行业的潜在应用

Filipa A Fernandes^1,2,3, Márcio Carocho^1,2, Tiane C Finimundy^1,2

¹Centro de Investigação de Montanha (CIMO), Instituto Politécnico de Bragança, Campus de Santa Apolónia, 5300-253 Bragança, Portugal.

Pharmaceuticals (Basel, Switzerland)

|May 25, 2024

概括

优化了Cistus, Acacia和Lemon Verbena的提取方法,确定了最大限度地提取有价值的化合物的理想条件. 超声辅助提取 (UAE) 和热辅助提取 (HAE) 在制药和营养食品应用方面进行了比较.

科学领域:

植物化学植物化学
分析化学分析化学
过程优化过程优化

背景情况:

像Cistus ladanifer,Acacia dealbata和Aloysia citrodora这样的药用植物是生物活性化合物的丰富来源.
这些化合物的有效提取对于它们在药品和营养保健品中的应用至关重要.
优化提取技术可以提高目标化合物的产量和纯度.

研究的目的:

为了优化从Cistus ladanifer,Acacia dealbata和Aloysia citrodora中提取化合物的提取条件.
为了比较不同植物矩阵和目标化合物的热辅助提取 (HAE) 和超声辅助提取 (UAE) 的效率.
为潜在的工业应用定义最大限度地提高高价值化合物产量的最佳参数.

主要方法:

使用响应表面方法优化了两个提取技术,热辅助提取 (HAE) 和超声辅助提取 (UAE).
四个因素是不同的:乙醇百分比,提取时间,温度/功率和固体/液体 (S/L) 比率.
使用二极管阵列检测和电喷射电离化质谱仪 (HPLC-DAD-ESI/MS) 的高性能液态染色学分析了烯特征.

主要成果:

确定了每个植物中特定的化合物的最佳条件:Cistus (阿联) 中的punicalagins,Acacia (阿联) 中的procyanidin,Acacia (阿联) 中的myricetin,Lemon Verbena (阿联) 中的martynoside和Lemon Verbena (阿联) 中的forsythiaside.
阿联被证明是最有效的Cistus punicalagins提取.
为每个目标化合物和工厂确定了特定的优化参数 (乙醇%,时间,功率/温度,S/L比率).

结论:

该研究成功地定义了利用HAE和UAE从Cistus, Acacia和Lemon Verbena提取特定的高价值化合物的最佳条件.
这些发现为制药和营养食品应用的可扩展和高效的提取过程提供了基础.
在HAE和UAE之间做出选择取决于目标化合物和植物矩阵,以最大限度地提高提取效率.

关键词:

阿卡西亚 dealbata L. L. 的时间.阿洛西亚树 (Aloysia citrodora) 在帕拉乌州生长.西斯图斯·拉达尼弗 L. 拉达尼弗提取优化提取的优化类化合物类化合物类化合物响应表面方法的方法.

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