Predictive modeling, multi-objective optimization and morphological characterization of spray-dried Tiliacora triandra leaf extract

This study optimized the spray-drying conditions for Tiliacora triandra extract using response surface methodology integrated with weighted aggregated sum product assessment (WASPAS) and a genetic algorithm (GA). The effects of inlet air temperature (120–140°C), feed flow rate (500–1,000 mL/h), and air velocity (1.2–3.0 m/s) on powder production, total phenolic content and DPPH radical scavenging activity were evaluated. Second-order polynomial models demonstrated strong predictive performance, with coefficients of determination values ranging from 0.9224 to 0.9691. WASPAS with entropy-based weighting was employed to identify the best-performing experimental runs, while the GA predicted optimum operating conditions of 124.07°C inlet air temperature, 814.81 mL/h feed flow rate, and 1.20 m/s air velocity. Under these optimized parameters, the predicted responses were 50.94 g/L powder production, 28.38 mg GAE/g total phenolic content, and 76.62% DPPH radical scavenging activity, with a predicted WASPAS score of 0.9812. These findings demonstrate the applicability of the integrated framework for optimizing spray-drying conditions of T. triandra extract.