title: Time-dependent fermentation control strategies for enhancing synthesis of marine bacteriocin 1701 using artificial neural network and genetic algorithm.
abstract: The artificial neural network (ANN) and genetic algorithm (GA) were combined to optimize the fermentation process for enhancing production of marine bacteriocin 1701 in a 5-L-stirred-tank. Fermentation time, pH value, dissolved oxygen level, temperature and turbidity were used to construct a "5-10-1" ANN topology to identify the nonlinear relationship between fermentation parameters and the antibiotic effects (shown as in inhibition diameters) of bacteriocin 1701. The predicted values by the trained ANN model were coincided with the observed ones (the coefficient of R(2) was greater than 0.95). As the fermentation time was brought in as one of the ANN input nodes, fermentation parameters could be optimized by stages through GA, and an optimal fermentation process control trajectory was created. The production of marine bacteriocin 1701 was significantly improved by 26% under the guidance of fermentation control trajectory that was optimized by using of combined ANN-GA method.
authors.affiliation: State Key Laboratory of Biocontrol, School of Life Sciences, Sun Yat-sen University, Guangzhou 510275, PR China.
authors.forename: Jiansheng
authors.initials: J
authors.lastname: Peng
authors.forename: Fanmei
authors.initials: F
authors.lastname: Meng
authors.forename: Yuncan
authors.initials: Y
authors.lastname: Ai
mesh_terms: D000465:Algorithms; D000704:Analysis of Variance; D001430:Bacteriocins / Q000096:biosynthesis* / Q000191:economics; D019149:Bioreactors / Q000382:microbiology; D001709:Biotechnology / Q000379:methods*; D005285:Fermentation; D016571:Neural Networks, Computer; D010100:Oxygen / Q000378:metabolism; D015203:Reproducibility of Results; D013997:Time Factors
chemical_list: D001430:Bacteriocins; C585056:bacteriocin 1701, Brevibacterium casei; D010100:Oxygen