Predictive Modeling of Sequential Fermentation for Sustainable Date Vinegar Production From Unripe Kharak Dates

This study optimizes sequential fermentation and predictive modeling for sustainable, high-quality vinegar production from unripe Kharak dates, an underutilized byproduct. Acetic acid bacteria (AAB) were isolated from Tehran and Gorgan samples (Iran), identified as Acetobacter pasteurianus, A. aceti, and A. tropicalis via morphological, biochemical, and PCR methods. Alcoholic fermentation was done by Saccharomyces cerevisiae at 20%, 30%, and 40% date syrup concentrations, followed by acetic fermentation with AAB. Optimal yeast growth and alcohol yield occurred at 20%, while A. pasteurianus showed robust performance across all levels, with 30% date syrup concentration yielding the best balance of growth, acidity (2.3% w/v), and pH stability. Gaussian, Gompertz, Rational, Sinusoidal Fit, and Logistic models effectively described microbial dynamics. This work enhances byproduct valorization and supports scalable, dietary-friendly vinegar production.