Journal
JOURNAL OF CHROMATOGRAPHIC SCIENCE
Volume 60, Issue 4, Pages 364-371Publisher
OXFORD UNIV PRESS INC
DOI: 10.1093/chromsci/bmab059
Keywords
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Funding
- Indian Council ofMedical Research, New Delhi [45/34/2018-NAN-BMS]
- King Saud University, Riyadh, Saudi Arabia [RSP-2020/261]
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A cost-effective, reliable, and rapid HPTLC method was developed for estimating GLA in borage oil, utilizing aluminum plates precoated with silica gel as the stationary phase and a hexane:toulene:glacial acetic acid mixture as the mobile phase. The method showed well-resolved spots for GLA and was validated for parameters like linearity, accuracy, specificity, and precision. The method demonstrated high sensitivity for GLA estimation in herbal oil samples and formulations.
Borage oil that is extracted from (Borago officinalis Linn.) is a well-known medicinal plant having various medicinal benefits. In this work, an affordable, simple, reliable, rapid and easily accessible high-performance thin-layer chromatography (HPTLC) method was developed for the estimation of gamma-linolenic acid (GLA) in borage oil. HPTLC method employs thin-layer chromatography (TLC) aluminum plates precoated with silica gel (G60F254) as the stationary phase, and the mixture of hexane:toulene:glacial acetic acid (3:7:1, v/v/v) was used as the mobile phase. Densitometric analysis of the TLC plates was carried out at 200 nm. The developed method showed well-resolved spots with retention factor (R-f) value of 0.53 +/- 0.04 for GLA. Various experimental conditions like saturation time for chamber, solvent phase migration and width of the band were studied intensely for selecting the optimum conditions. The method validation was performed for parameters like linearity, accuracy, specificity and precision. The values of limit of detection and limit of quantification for GLA were found to be 0.221 and 0.737 mu g/band, respectively. In nutshell, the developed HPTLC method was found to be highly sensitive for the estimation of GLA in the herbal oil samples and formulations.
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