Jia-Cong Huang , Qi Guo , Xu-Hong Li, Tian-Qiong Shi
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引用次数: 0
Abstract
The development of high-performance strains and the continuous breakthrough of strain screening technology also pose challenges to downstream fermentation optimization and scale-up. Therefore, neural network models are utilized to optimize the fermentation process to meet the goals of boosting yield or lowering cost, with the use of artificial intelligence technology in conjunction with the peculiarities of the fermentation process. High-performance strains’ yield rise and fermentation process amplification will be sped up with the aid of neural network models. This paper offers a helpful review for anyone interested in state-of-the-art microbial fermentation processes, as it thoroughly reviews the application of neural network models in predicting fermentation yield, optimizing the fermentation process, and monitoring the fermentation process.
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.