Enhanced production of acetic acid through bioprocess optimization employing response surface methodology and artificial neural network.

[Display omitted] • Isolation of acetic acid-producing bacteria from fruit waste and cow dung. • Estimation of Acetic acid production by biological method for waste valorization. • Experimentation of Acetic acid production on different parameters. • Optimization of acetic acid yield by RSM and ANN models. In this study, acetic acid bacteria (AAB) are isolated from fruit waste and cow dung on the basis of acetic acid production potential. The AAB were identified based on halo-zones produced in the Glucose-Yeast extract-Calcium carbonate (GYC media) agar plates. In the current study, maximum acetic acid yield is reported to be 4.88 g/100 ml from the bacterial strain isolated from apple waste. With the help of RSM (Response surface methodology) tool, glucose and ethanol concentration and incubation period, as independent variable showed the significant effect of glucose concentration and incubation period and their interaction on the AA yield. A hypothetical model of artificial neural network (ANN) was also used to compare the predicted value from RSM. Acetic acid production through the biological route can be the sustainable and clean approach to utilizing food waste in circular economy approach [ABSTRACT FROM AUTHOR]