Optimisation of Microwave-Assisted Extraction of Phenolic Compounds from Pithecellobium dulce Fruit Peels: Comparative Process Modelling Using RSM and ANN with Bioactivity Evaluation

Polyphenols have gained significant attention in recent decades due to their protective role against cancer, diabetes, obesity, osteoporosis, neurodegenerative, and cardiovascular diseases. This study explored the influence of radiation time, microwave power, and sample-to-solvent ratio on the microwave-assisted extraction of polyphenols from Pithecellobium dulce fruit peels. Extraction efficiency, antioxidant activity, and anti-cholesterol activity were optimised using both response surface methodology (RSM) and artificial neural networks combined with a genetic algorithm (ANN-GA). The ANN-GA model exhibited higher predictive accuracy (R2 = 0.9805–0.9813) and lower statistical error compared to quadratic RSM models (R2 = 0.9566–0.9767). Under optimised conditions, ANN-GA yielded 244.35 mg/g total polyphenols, 92.51% antioxidant activity, and 73.96% anti-cholesterol activity, outperforming RSM (242.35 mg/g, 92.18%, and 73.26%, respectively). These findings demonstrate the scientific novelty of ANN-GA as a more robust and reliable tool than RSM for process optimisation. Moreover, the study highlights the practical application of utilizing P. dulce fruit peels as a low-cost, natural source of health-promoting bioactives. Importantly, this work presents a broader impact by providing a sustainable strategy for waste valorisation into nutraceutical and pharmaceutical products.