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.

中文翻译：

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神经网络模型在微生物发酵中的应用综述


高性能菌株的开发和菌株筛选技术的不断突破也对下游发酵优化和放大提出了挑战。因此，利用神经网络模型来优化发酵过程，以实现提高产量或降低成本的目标，并将人工智能技术与发酵过程的特殊性结合使用。在神经网络模型的帮助下，高性能菌株的产量提高和发酵过程的放大将得到加速。本文为任何对最先进的微生物发酵过程感兴趣的人提供了有用的评论，因为它全面回顾了神经网络模型在预测发酵产量、优化发酵过程和监测发酵过程方面的应用。