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超临界流体色谱法通过超临界流体萃取和加压液体萃取开发预测性分析工具,以选择性提取生物活性化合物。

Supercritical Fluid Chromatography development of a predictive analytical tool to selectively extract bioactive compounds by supercritical fluid extraction and pressurised liquid extraction.

机构信息

ICOA, CNRS UMR 7311, Université d'Orléans, rue de Chartres, BP 6759, 45067 Orléans Cedex 2, France.

ICOA, CNRS UMR 7311, Université d'Orléans, rue de Chartres, BP 6759, 45067 Orléans Cedex 2, France.

出版信息

J Chromatogr A. 2020 Nov 22;1632:461582. doi: 10.1016/j.chroma.2020.461582. Epub 2020 Sep 25.

Abstract

Selective extraction is a great concern in the field of natural products. The interest is to apply specific conditions favouring the solubility of targeted secondary metabolites and avoiding the simultaneous extraction of unwanted ones. Different ways exist to reach selective extractions with suited conditions. These conditions can be determined from experimental studies through experimental design, but a full experimental design takes time, energy, and uses plant samples. Prediction from varied solubility models can also be applied allowing a better understanding of the final selected conditions and eventually less experiments. The aim of this work was to develop and use a chromatographic model to determine optimal extraction conditions without the need for numerous extraction experiments. This model would be applied on the selective extraction of the desired antioxidant compounds in rosemary leaves (rosmarinic and carnosic acids) vs chlorophyll pigments to limit the green colour in extracts. This model was achieved with Supercritical Fluid Chromatography (SFC) and then applied to Supercritical Fluid Extraction (SFE) and Pressurised Liquid Extraction (PLE) assays. SFC models predicted low solubility of chlorophylls for low (5%) and high (100%) percentage of solvent in carbon dioxide. Also, low solubility was predicted with acetonitrile solvent compared to methanol or ethanol. This was confirmed with different extractions performed using SFE with different percentages of solvent (5, 30, and 70%) and with the three solvents used in the SFC models (acetonitrile, methanol and ethanol). Also extractions using PLE were carried out using the same neat solvents in order to confirm the SFC models obtained for 100% of solvent. Globally, extractions validated the SFC models. Only some differences were observed between ethanol and methanol showing the complexity of plant extraction due to matrix effect. For all these extracts, the content of carnosic acid and rosmarinic acid was also monitored and selective extraction conditions of bioactive compounds could be determined.

摘要

选择性提取是天然产物领域的一个重要关注点。其目的是应用特定条件,有利于目标次生代谢产物的溶解度,并避免同时提取不需要的产物。存在不同的方法来实现具有合适条件的选择性提取。这些条件可以通过实验设计从实验研究中确定,但完整的实验设计需要时间、精力,并使用植物样本。也可以应用各种溶解度模型进行预测,从而更好地了解最终选择的条件,最终减少实验次数。本工作的目的是开发和使用色谱模型来确定最佳提取条件,而无需进行大量的提取实验。该模型将应用于迷迭香叶中所需抗氧化化合物(迷迭香酸和鼠尾草酸)与叶绿素色素的选择性提取,以限制提取物的绿色。该模型是通过超临界流体色谱(SFC)实现的,然后应用于超临界流体萃取(SFE)和加压液体萃取(PLE)分析。SFC 模型预测低比例(5%)和高比例(100%)的二氧化碳溶剂中的叶绿素溶解度低。与甲醇或乙醇相比,乙腈溶剂的溶解度也较低。通过使用 SFE 进行不同溶剂比例(5%、30%和 70%)的不同提取以及在 SFC 模型中使用的三种溶剂(乙腈、甲醇和乙醇)进行的不同提取证实了这一点。还使用相同的纯溶剂进行了 PLE 提取,以确认为 100%溶剂获得的 SFC 模型。总体而言,提取验证了 SFC 模型。仅观察到乙醇和甲醇之间的一些差异,这表明由于基质效应,植物提取的复杂性。对于所有这些提取物,还监测了鼠尾草酸和迷迭香酸的含量,并确定了生物活性化合物的选择性提取条件。

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