Issue 43, 2023

Assessment of collagen content in fish skin – development of a flow analysis method for hydroxyproline determination

Abstract

This work describes the development of a flow injection method to determine hydroxyproline (HYP), one of collagen's most abundant amino acids. Collagen is a protein with several applications and high nutritional value. Evaluating the feasibility of using collagen from fish skin over its mammalian source is essential. The determination of HYP requires the pre-treatment and hydrolysis of the fish skin to break down collagen into its amino acids, and the HYP value quantified relates to the collagen content. The determination was based on the HYP oxidation with permanganate in an alkaline medium and the consequent decrease of colour intensity registered. Under optimal conditions, the developed method enables the determination of the HYP within the dynamic range of 23.8 to 500 mg L−1, with a limit of detection (LOD) of 2.6 mg L−1 and a limit of quantification (LOQ) of 23.8 mg L−1. Different samples were processed, and the digests were analysed by the proposed method and with the conventional procedure with good correlation (relative error < 7%). Moreover, the analyte quantification is performed faster, simpler, and more accurately, with less toxic solutions. The reproducibility of the developed method was also evaluated by calculating the relative standard deviation of the calibration curve slope (RSD < 1%).

Graphical abstract: Assessment of collagen content in fish skin – development of a flow analysis method for hydroxyproline determination

Supplementary files

Article information

Article type
Technical Note
Submitted
08 Sep 2023
Accepted
10 Oct 2023
First published
30 Oct 2023
This article is Open Access
Creative Commons BY license

Anal. Methods, 2023,15, 5901-5908

Assessment of collagen content in fish skin – development of a flow analysis method for hydroxyproline determination

M. M. P. Melo, R. B. R. Mesquita, E. R. Coscueta, M. E. Pintado and A. O. S. S. Rangel, Anal. Methods, 2023, 15, 5901 DOI: 10.1039/D3AY01589K

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