Optimization of acetic acid fermentation condition of Acetobacter A3 based on orthogonal design coupled with artificial neural networks model

A bacterium strain A3 producing acetic acid was isolated from the traditional brewing process of Gansu vinegar. The optimization method based on orthogonal design coupled with artificial neural networks model (ANN) was employed to select fermentation conditions for increasing the yield of acetic acid. The combinations of factor and level in the orthogonal design were used as the input variables, and the content of acid as the output for building the ANN model. The sixteen tests data were used as BP architecture training samples, and two other test results (No.17 and No.18) were used to examine the generalization capability of the model. Finally, the established ANN was applied to the optimization of fermentation conditions. The results showed that the optimized fermentation conditions for acetic acid production of this Acetobacter A3 were found to be 4.2% (v/v) alcohol, 30℃, pH6.4 and 8d fermentation time. Under the conditions, the content of acetic acid was superior to orthogonal test, increasing to 4.3086g/100mL.