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Issue 9, 2018
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Fast and sensitive low density solvent-based dispersive liquid–liquid microextraction method combined with high-performance liquid chromatography for determining cholecalciferol (vitamin D3) in milk and yogurt drink samples

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Abstract

In this study, low density solvent-based dispersive liquid–liquid microextraction (LDS-DLLME) as a simple, fast and efficient microextraction method, followed by high-performance liquid chromatography was employed to determine cholecalciferol (vitamin D3) in milk and yogurt drink samples. The effective parameters in the microextraction process were optimized using the response surface methodology (RSM) based on central composite design (CCD). Under the optimum conditions, the calibration curves showed high linearity (R2 > 0.995) for vitamin D3 in the range of 2–500 ng mL−1. The relative standard deviation for seven analyses was less than 7.5%. Furthermore, the limit of detection and limit of quantitation were 0.9 ng mL−1 and 3 ng mL−1, respectively. The relative recoveries of vitamin D3 obtained were higher than 97%. High recovery, short extraction time, good linearity and no matrix interference are advantages of the proposed method. The performance of the proposed method was evaluated for determining vitamin D3 in various fortified milk and yogurt drink samples.

Graphical abstract: Fast and sensitive low density solvent-based dispersive liquid–liquid microextraction method combined with high-performance liquid chromatography for determining cholecalciferol (vitamin D3) in milk and yogurt drink samples

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Publication details

The article was received on 18 Dec 2017, accepted on 06 Feb 2018 and first published on 06 Feb 2018


Article type: Paper
DOI: 10.1039/C7AY02915B
Citation: Anal. Methods, 2018,10, 975-982
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    Fast and sensitive low density solvent-based dispersive liquid–liquid microextraction method combined with high-performance liquid chromatography for determining cholecalciferol (vitamin D3) in milk and yogurt drink samples

    M. Kamankesh, M. Shahdoostkhany, A. Mohammadi and A. Mollahosseini, Anal. Methods, 2018, 10, 975
    DOI: 10.1039/C7AY02915B

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