The present study adopted a response surface methodology (RSM) approach validated by artificial neural network (ANN) models to optimise the production of a bitter gourd-grape beverage. Aset of statistically pre-designed experiments were conducted, and the RSM optimisation model fitted to the obtained data, yielding adequately fit models for the monitored control variables R² values for alcohol (0.79), pH (0.89), and total soluble solids (TSS) (0.89). Further validation of the RSM model fit using ANN showed relatively high accuracies of 0.98, 0.88, and 0.82 for alcohol, pH, and TSS, respectively, suggesting satisfactory predictability and adequacy of the models. A clear effect of the optimised conditions, namely fermentation time at (72 h), fermentation temperature (32.50 and 45.11 °C), and starter culture concentration (3.00 v/v) on the total titratable acidity (TTA), was observed with an R² value of (0.40) and RSM model fit using ANN overall accuracy of (0.56). However, higher TTA values were observed for samples fermented for 72 h at starter culture concentrations above 3 mL. The level of 35% bitter gourd juice was optimised in this study and was considered desirable because the goal was to make a low-alcohol beverage.

Bitter gourd beverages are well acclaimed for their health benefits, which have propelled their consumption. The beverages are prepared through a fermentation process, which is one of the oldest means of preserving and enhancing the flavour of many foods. Optimized conditions for the fermentation of a bitter gourd–grape beverage were investigated in our previous study. In the present study, a statistical comparison (one-way analysis of variance (ANOVA), Tukey’s honestly significant difference (HSD) test and an independent t-test)) of grape juice, bitter gourd juice and the fermented bitter gourd–grape beverage (with and without enzymes) was carried out to find significant differences among the products. Alcohol was found to be consistent for the four products with p > 0.05, whereas significant differences (p ≤ 0.05) in the pH, antioxidant activity (ferric reducing antioxidant assay (FRAP), 2,2-diphenyl-1-picrylhydrazyl (DPPH) and 2,2-azinobis (3-ethyl-benzothiazoline-6-sulfonic acid) (ABTS)), total titratable acidity (TTA), total soluble solids (TSS), total flavonoid content (TFC) and total phenolic content (TPC) were observed. The fermented bitter gourd–grape beverage (FBGGB) with enzymes had the highest antidiabetic potential content (27.07). The data obtained demonstrate that fermentation indeed enhances the biochemical function of vegetables (in this case, bitter gourd) and could thus be considered for the commercial processing of bitter gourd.