Optimization of Ultrasound-Assisted Extraction Conditions for Pigment Compounds of the Brown Algae Sargassum angustifolium Using Response Surface Methodology

Subject Areas :

Niloofar Aghajanpoor Sourkohi ¹ (Fisheries Department, Faculty of Natural Resources, University of Guilan, Sowmeh Sara, Iran)
Aria Babakhani ² (1Fisheries Department, Faculty of Natural Resources, University of Guilan, Sowmeh Sara, Iran 2 Department of Marine Science, Caspian Sea Basin Research Center, University of Guilan, Rasht, Iran)

Received: 2023-05-12 Accepted : 2023-08-04 Published : 2023-09-20

Keywords: Sargassum angustifolium, / Optimization, / Pigment, / Ultrasound-Assisted Extraction, / Brown algae,

Abstract :

This study aimed to optimize the ultrasound-assisted extraction (UAE) of pigment compounds from the brown alga Sargassum angustifolium. UAE offers potential advantages over conventional extraction methods, including reduced solvent consumption, shorter extraction times, and improved yields. To systematically investigate and optimize the extraction process, response surface methodology (RSM) was employed. A central composite design (CCD) was utilized to examine the effects and interactions of four critical process variables: ethanol concentration (ranging from 50% to 100%), extraction time (10 to 30 minutes), solid-liquid ratio (1:5 to 1:15), and ultrasound power (80 to 400 watts). The impact of these variables on four key responses was evaluated: chlorophyll a content, total chlorophyll content, total carotenoid content, and fucoxanthin content. Statistical analysis of the experimental data revealed that optimal conditions for maximizing fucoxanthin and total carotenoid yields were: 75% ethanol concentration, 20 minutes extraction time, 1:5 solid-liquid ratio, and 240 watts ultrasound power. Under these optimized conditions, fucoxanthin yield reached 0.42 mg/g, while total carotenoid yield attained 1.11 mg/g of dry algal biomass. The developed models demonstrated high predictive capability, with experimental results closely aligning with model predictions. This agreement validated the appropriateness and reliability of the RSM approach for optimizing the UAE process. Additionally, the study provided insights into the relative importance and interactions of the investigated process variables. These findings offer a foundation for the efficient and scalable extraction of high-value pigments from S. angustifolium using UAE.