A correlative algorithmic optimization study for an integrated soft computing technique in aqueous two-phase protein extraction from Litopenaeus vannamei waste

• Published in: Biomass conversion and biorefinery 2023-12, Vol.13 (18), p.16819-16833
• Main Authors: Saravana Pandian, P., Sindhanaiselvan, S., Subathira, A., Saravanan, S.
• Format: Article
• Language: English
• Subjects: Binary systems; Biomass; Biotechnology; Energy; Genetic algorithms; Industrial applications; Optimization; Original Article; Particle swarm optimization; Polyethylene glycol; Production costs; Proteins; Renewable and Green Energy; Response surface methodology; Shrimps; Sodium citrate; Soft computing
• ISSN: 2190-6815; 2190-6823
• DOI: 10.1007/s13399-022-02355-x

A waste biomass is found to be a good source for many value-added products. Shrimp waste is one of the ultimate sources of proteins. The high-value-added protein recovery using aqueous two-phase system (ATPS) from shrimp Litopenaeus vannamei waste (LVW) is investigated. The factors influencing protein extraction were optimized using response surface methodology (RSM) coupled genetic algorithm (GA) and particle swarm optimization (PSO) as two distinct approaches. A three-level, four-factor (CCD) central composite design was employed to evaluate parameters that influence protein extraction yield and determine the suitable conditions for ATPS. Polyethylene glycol (PEG) 2000 concentration (A), trisodium citrate (TSC) concentration (B), pH (C) and temperature (D) are the four factors that influence the protein extraction yield examined by implementing RSM-GA and RSM-PSO. In RSM-GA, the highest protein yield of 94.99% was achieved with optimal extraction conditions of PEG 2000 concentration of 15.8% (w/w), TSC concentration of 16.0% (w/w), pH 8.0, and temperature 35.0 °C. In RSM-PSO, the highest protein yield of 94.16% was achieved from the PEG/TSC ATPS system with optimal extraction conditions of PEG concentration of 16% (w/w), the salt concentration of 15.8% (w/w), pH 8 and temperature 35 °C. The results obtained from RSM-GA and RSM-PSO were compared and experimentally validated. Hence, RSM-PSO was a potential tool compared to RSM-GA for parametric optimization of ATPS for protein extraction from LVW. Using waste biomass in industrial applications could reduce the production cost and increase the industry’s circular economy.