Optimizing fermentation condition and shelf life study of black wheat rawa idli using artificial neural network-enhanced response surface methodology

Abstract

Black wheat, a nutrient-rich and underutilized pigmented wheat variety, offers significant health benefits when incorporated into plant-based foods. This study aimed to optimize the fermentation parameters for black wheat rawa idli (BWI) over a period of 2–6 h temperatures ranging from 20 to 45 °C. Key parameters, including batter volume, pH, titratable acidity, and density, were evaluated. Multi-objective optimization was performed using response surface methodology (RSM) and an artificial neural network coupled (ANN). The ANN demonstrated superior prediction accuracy (R² = 0.98, MSE = 0.11) compared to RSM (R² = 0.93, MSE = 0.31). Optimal fermentation conditions were identified as 32.5 °C for 4 h with 1.37 % inoculation. Scanning electron microscopy revealed a loss of structural integrity in starch granules, improved texture and enhanced antioxidant potential. The shelf life of the BWI mix stored at 25 °C in low-density polyethylene packaging was 75 days without nitrogen flushing and extended to 120 days with nitrogen flushing. These findings indicate that BWI possesses enhanced functional qualities, making it a promising and healthier dietary option. The optimization of fermentation parameters and shelf-life assessment provides valuable insights for the development of the healthier alternative to traditional rawa idli.