Optimization and comparison of ℽ-aminobutyric acid (GABA) production by LAB in soymilk using RSM and ANN models

Abstract Background ℽ-Aminobutyric acid (GABA) is a non-proteinaceous amino acid. In the mammalian nervous system, GABA functions as an inhibitory neurotransmitter. The present study focused on screening and optimization of ℽ-aminobutyric yield by lactic bacteria using soymilk basal media. Lactobacillus fermentum ( Lb. ) was isolated from sourdough. qualitative confirmation production observed detecting colored spots thin layer chromatography plate (TLC) comparing it with standard spot. confirmed its molecular mass spectrophotometry analysis (MS analysis). Single variable experiments were conducted for various physical nutritional parameters, determined content produced , viable bacterial count, pH fermented medium. Experimental data authenticated response surface method (RSM) artificial neural network (ANN) model. Results results demonstrated that through single experiments, cells increased in containing one percent glucose, monosodium glutamate (MSG), inoculum volume incubated at 37 °C, 48 h 5. According to RSM results, interaction highest concentration MSG (1.5%) mid glucose (1.156%) yielded maximum (5.54 g/L). experimental good agreement two models. models showed less error percentage than ANN Conclusion This indicates best substrate growth compared synthetic can be explored further food pharmaceutical industries development functional foods therapeutic purposes.