Optimizing ultrasound-assisted extraction with custom design and response surface methodology: A case study using Ulva spp.

This study presents an educational and structured optimization approach using a custom I-optimal response surface methodology to model and optimize ultrasound-assisted extraction (UAE), focusing on the recovery of ulvan, extraction of proteins, and phenolic compounds from Ulva spp. as a case study. The research serves as a replicable framework for researchers, educators and students in UAE from complex biomass substrates. The experimental design incorporated four independent variables: specific energy input (SEI, 10-110 J/mL), solid-liquid ratio (SLR, 1:60-1:30 w/w), amplitude (20-100 %, corresponding to 21-86 W and 9-46 μm), and temperature (30-90 °C). Although SEI and amplitude are partially related, they were treated as independent variables in the experimental design to assess their individual effects, with no multicollinearity detected. Response criteria included extraction or recovery yield (mg/g dry biomass), in dry extract (mg/g dry extract), and specific energy demand (kW·h/kg). SEI, SLR, and temperature were identified as the most influential factors, with amplitude playing a less important role. Higher SEI and temperature generally improved extraction but also increased energy consumption, highlighting the trade-offs relevant for industrial applications. The optimization scenarios favoured ulvan recovery under lower temperature and ultrasonication energy-efficient conditions, demonstrating the need for a holistic approach rather than solely maximizing yield. The findings emphasize the importance of methodological design in optimizing UAE processes while ensuring practical applicability and scalability, reinforcing its educational value for process engineers and researchers.