Potential challenges and guidelines for ultrasound and ultrasound-assisted enzymatic treatment of seaweed biomass
Year: 2025
Type: article
Abstract: Seaweed biomass is increasingly recognized as a promising renewable resource for sustainable applications in the food, pharmaceutical, cosmetic and bioenergy sectors. Unlike terrestrial biomass, seaweed requires no additional delignification pretreatments, enabling direct processing. This reduces chemical and energy inputs while improving extraction and saccharification efficiency. Ultrasound technology has gained substantial importance in recent decades as a novel and promising approach for biomass processing. Enzymatic treatments have also been widely investigated for seaweed valorization, although they are often limited by long processing times. To overcome this, ultrasound-assisted enzymatic treatments have been proposed to increase enzymatic efficiency and reduce treatment times. Nonetheless, research practices in this field have not yet been sufficiently standardized, limiting reproducibility and hindering innovation. This review aims to provide the fundamental theoretical background of ultrasound-assisted extraction (UAE) and ultrasound-assisted enzymatic extraction (UAEE), with a particular focus on seaweed biomass. The literature is critically analyzed, the ultrasound-specific factors that most significantly affect processing (frequency, amplitude, power, biomass concentration and working mode) are presented, and their roles and interactions in biomass disruption and extraction are explained. Finally, this review proposes guidelines and fair practices for designing and reporting experiments involving UAE and UAEE of seaweed biomass and recommends the use of two ultrasound-specific parameters (i.e., ultrasonic intensity (W/cm 2 ) and energy input (W·s/g)) as parameters to compare different processes.
Institutions: KU Leuven, University of Oxford
Language: English
Subfield: Aquatic Science
Domain: Life Sciences
Open Access status: hybrid
Estimated APC paid: $5,220
OpenAlex ID: W4414308310
