Jian Ding , Bo Wang , Qingyuan Liu , Wenbiao Hou , Jun Cai , Cheng Lu
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引用次数: 0
Abstract
Bacillus licheniformis is widely utilized in disease prevention and environmental remediation. Spore quantity is a critical factor in determining the quality of microbiological agents containing vegetative cells. To improve the understanding of Bacillus licheniformis BF-002 strain culture, a hybrid model integrating traditional dynamic modeling and recurrent neural network was developed. This model enabled the optimization of carbon/nitrogen source feeding rates, pH, temperature and agitation speed using genetic algorithms. Carbon and nitrogen source consumption in the optimal duplicate batches showed no significant difference compared to the control batch. However, the spore quantity in the broth increased by 16.2% and 35.2% in the respective duplicate batches. Overall, the hybrid model outperformed the traditional dynamic model in accurately tracking the cultivation dynamics of Bacillus licheniformis, leading to increased spore production when used for optimizing cultivation conditions.
期刊介绍:
Bioresource Technology publishes original articles, review articles, case studies, and short communications covering the fundamentals, applications, and management of bioresource technology. The journal seeks to advance and disseminate knowledge across various areas related to biomass, biological waste treatment, bioenergy, biotransformations, bioresource systems analysis, and associated conversion or production technologies.
Topics include:
• Biofuels: liquid and gaseous biofuels production, modeling and economics
• Bioprocesses and bioproducts: biocatalysis and fermentations
• Biomass and feedstocks utilization: bioconversion of agro-industrial residues
• Environmental protection: biological waste treatment
• Thermochemical conversion of biomass: combustion, pyrolysis, gasification, catalysis.