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Highlighting extraction and derivatization method comparisons for optimal sample preparation of Nannochloropsis sp. algal oils prior to FAME determination

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Abstract

Microwave assisted extraction derivatization (MAED) was investigated for preparing fatty acid methyl ester (FAME) derivatives to analyse the fatty acid (FA) composition of Nannochloropsis sp. algae. This method was compared against the conventional methods of oven assisted derivatization and direct derivatization without prior extraction. The derivatized FAMEs were analysed using GC-MS to identify and quantify the FAs present. Conventional methods have been carried out for years, but they are time consuming and require high temperatures and harmful chemicals. The MAED approach developed is 5 times (15 min) faster compared to the conventional and direct derivatization methods (75 min) optimised for FA analysis of Nannochloropsis sp. algae. The MAED method recovered significantly more FAs (51 wt%) from algal samples compared to conventional (42 wt%) and direct derivatization (34 wt%). Additionally it was shown that a sample extraction step is critical to improving the derivatization yield of algal samples for both oven assisted and MAED techniques. Fourteen FA components were identified in Nannochloropsis sp. algal samples and were evaluated for their potential use for biodiesel and biopharmaceutical products. The developed MAED method allows for a rapid, robust and accurate preparation of algal samples in order to determine their FA composition.

Graphical abstract: Highlighting extraction and derivatization method comparisons for optimal sample preparation of Nannochloropsis sp. algal oils prior to FAME determination

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Supplementary files

Article information


Submitted
10 Oct 2019
Accepted
19 Dec 2019
First published
20 Dec 2019

Anal. Methods, 2020, Advance Article
Article type
Paper

Highlighting extraction and derivatization method comparisons for optimal sample preparation of Nannochloropsis sp. algal oils prior to FAME determination

B. Brennan, F. Regan, R. Fernández, J. I. Amor, Y. Delaure, S. Mangini and M. R. Jacobs, Anal. Methods, 2020, Advance Article , DOI: 10.1039/C9AY02190F

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