Datasets on the optimization of alginate extraction from sargassum biomass using response surface methodology

Area of Science:

• Marine Biotechnology
• Biopolymer Extraction
• Chemical Engineering

Background:

• Sargassum seaweed is a significant marine biomass resource.
• Alginates are valuable biopolymers with diverse industrial applications.
• Efficient extraction methods are needed to valorize seaweed waste.

Purpose of the Study:

• To optimize the alkaline extraction of sodium alginate from waste Sargassum seaweed.
• To investigate the effects of key process variables on alginate yield.
• To validate the extraction model and characterize the obtained sodium alginate.

Main Methods:

• Response Surface Methodology (RSM) with a Box-Behnken Design (BBD) was employed.
• Key variables studied: temperature, extraction time, alkali concentration, and alkali excess volume.
• Characterization utilized High Performance Liquid Chromatography (HPLC), Gel Permeation Chromatography (GPC), Fourier Transform Infrared Spectroscopy (FTIR), and Nuclear Magnetic Resonance (NMR).

Main Results:

• The study identified optimal conditions for sodium alginate extraction.
• The developed model effectively predicted alginate yield based on process variables.
• Characterization confirmed the quality of the extracted sodium alginate.

Conclusions:

• The optimized extraction method demonstrates the potential to valorize Sargassum seaweed waste into a valuable sodium alginate product.
• The methodology is applicable to other macroalgae for commercial-grade alginate production.
• This approach contributes to sustainable resource utilization in marine biotechnology.