Sustainable valorization of Pleurotus pulmonarius via green dual-enzyme technology: Novel optimization for functional protein hydrolysates

This research established a sustainable dual-enzyme hydrolysis method for generating nutrient-dense hydrolysates from grey oyster mushrooms <i>(Pleurotus pulmonarius),</i> a native resource of Vietnam. Process optimization integrated a quadratic regression model using response surface methodology (RSM) and an artificial neural network combined with a genetic algorithm (ANN-GA). The objective was to enhance nitrogen recovery, amino acids, peptides, glutamic acid, and lysine, while minimizing NH₃ formation. ANN-GA demonstrated superior predictive accuracy compared to RSM, with RMSE values of 1-2 % versus 2-5 %. In contrast, RSM offered precise quantitative insights regarding the effects of factors. The optimal conditions (50.9 °C, 6.45 h, pH 6.12) resulted in a nitrogen recovery of 27.23 %, with 6.926 g/100 g of amino acids, 11.41 g/100 g of peptides, 6.398 g/100 g of glutamic acid, 0.0845 g/100 g of lysine, and 0.0089 g/100 g of NH₃. Levels of essential amino acids were comparable to or higher than those documented in previous studies. The sustainability of the method not only reduces waste and benefits farmers but also provides a practical route to producing mushroom-based functional food and seasoning ingredients due to their high amino acid and peptide content.