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Processing watermelon waste using
 Saccharomyces cerevisiae
 yeast and the fermentation method for bioethanol production

Bioethanol is a source of energy for the future when petroleum is going to finish. The aim of this study is to assess bioethanol production from watermelon waste using Saccharomyces cerevisiae (S. cerevisiae) yeast and fermentation method. The test was replicated three times in 35 hr at three different fermenter agitator speeds and three levels of yeast. The results showed that about 35.5 g of bioethanol was obtained from each kilogram of watermelon. Investigating different variables shows that the fermenter agitator speed of 120 rpm and the yeast amount of 5 g could lead to the best yield in the process of fermenting watermelon waste for the purpose of producing bioethanol. The results of the evaluating the artificial neural network (ANN) model and adaptive neuro‐fuzzy inference system (ANFIS) in predicting bioethanol production from watermelon waste with the highest coefficient of determination (R²) were 0.9895 and 0.9993, respectively. These results indicate that ANNs and ANFIS are effective in predicting bioethanol production from watermelon waste. PRACTICAL APPLICATIONS: Advanced, green, clean, and sustainable processing technologies to reduce watermelon waste. Fermentation of agricultural waste in the shortest time (30 hr). Investigating important factors in waste fermentation process. The performance of ANN and ANFIS network in predicting bioethanol production.