Multi-objective optimization of phenolic compound extraction from fresh and dried rosemary (Salvia rosmarinus) using evolutionary algorithms.

BACKGROUND: A practical challenge in rosemary (Salvia rosmarinus Spenn.) processing is selecting aqueous extraction conditions that balance total phenolic content (TPC) recovery across fresh and dried matrices. This study combined a Box-Behnken design, Folin-Ciocalteu quantification, complete second-order response-surface models, and NSGA-II to identify operating regions and testable compromise conditions within a shared temperature-time-mass domain. RESULTS: Temperature was the principal driver of the modeled response, whereas extraction time showed an early plateau. The dried-rosemary model showed a tighter fit (R2 = 0.905; RMSE = 1.93 g GAE kg-1 sample) and broader modeled high-response regions than the fresh-rosemary model (R2 = 0.818; RMSE = 3.71 g GAE kg-1 sample). The temperature × mass interaction was supported for fresh rosemary (P = 5.02 × 10-7) but not for dried rosemary (P = 0.667). The Pareto front revealed matrix-dependent trade-offs. Under equal desirability weights, the selected compromise was 90.0 °C, 4.6 min, and 0.50 g, with predicted TPC values of 30.15 g GAE kg-1 sample for fresh rosemary and 24.31 g GAE kg-1 sample for dried rosemary (D* = 0.663). CONCLUSION: The matched framework provided a common basis for balancing aqueous TPC recovery across raw-material states. The selected condition and neighboring Pareto solutions are model-based candidates rather than validated operating recommendations. Independent confirmation runs are required to quantify external prediction error, local robustness, and application potential before bench- or pilot-scale transfer. © 2026 Society of Chemical Industry.