2006Yunnan Chemical TechnologyRequires access

Process for the Extraction of Flavones from Ginkgo Leaves

Yingying Fan

Open publisher page 1 citations

Abstract

Process for the extraction of flavones from Ginkgo leaves with ethanol-water was studied,and content of flavones was determined by spectrophotometry.The optimal condition was chosen by orthogonal tests as extraction with 70% ethanol at 70 oC,ratio of solid to liquid 1: 20 and at pH 8,and the extraction rate of flavones reach 92.2%.

About this research paper

What this paper is about

Process for the extraction of flavones from Ginkgo leaves with ethanol-water was studied,and content of flavones was determined by spectrophotometry.The optimal condition was chosen by orthogonal tests as extraction with 70% ethanol at 70 oC,ratio of solid to liquid 1: 20 and at pH 8,and the extraction rate of flavones reach 92.2%.

Why it matters

OpenAlex reports 1 citations for this work. Citation counts describe recorded attention and do not establish research quality.

Key contribution

A contribution statement is not available in the OpenAlex record.

Method / approach

Method details are not available in the OpenAlex metadata.

Main findings

Findings are not separately available in the OpenAlex metadata.

Limitations

Limitations are not available in the OpenAlex metadata.

Applications

Application details are not available in the OpenAlex metadata.

Available abstract

Process for the extraction of flavones from Ginkgo leaves with ethanol-water was studied,and content of flavones was determined by spectrophotometry.The optimal condition was chosen by orthogonal tests as extraction with 70% ethanol at 70 oC,ratio of solid to liquid 1: 20 and at pH 8,and the extraction rate of flavones reach 92.2%.

Key concepts: Flavones, Extraction (chemistry), Ginkgo, Chemistry, Chromatography, Ethanol, Spectrophotometry, Botany

Related papers

Back to paper searchBrowse research topicsOriginal source
Process for the Extraction of Flavones from Ginkgo Leaves — Research Paper | ScholarLens