Ultrasound-assisted, machine learning-optimized extraction of silver carp viscera fish oil and microencapsulation via complex coacervation.

ABSTRACT: Silver carp viscera, a lipid‑rich byproduct typically discarded, poses environmental pollution and resource wastage. Utilizing this byproduct for fish oil extraction offers a sustainable alternative; however, conventional enzymatic methods are inefficient, labor‑intensive to optimize, and yield oil susceptible to rapid oxidation. For the first time, this study developed an integrated ultrasound pretreatment and artificial neural network-genetic algorithm (ANN‑GA) strategy to maximize fish oil extraction efficiency, followed by microencapsulation in gelatin-hexametaphosphate complex coacervation microcapsules (GSM). The ANN demonstrated excellent predictive accuracy (R² = 0.99). Under GA-optimized conditions (ultrasonic power: 150  W, ultrasound pretreatment: 20.75  min, protease

SUBMITTER: Zhou Y 

PROVIDER: S-EPMC12271628 | biostudies-literature | 2025 Jun

REPOSITORIES: biostudies-literature