BioPAT Laboratory, Department of Biosciences and Bioengineering, Indian Institute of Technology Guwahati, Assam, 781039, India.
World J Microbiol Biotechnol. 2024 May 9;40(6):196. doi: 10.1007/s11274-024-03993-1.
During the epoch of sustainable development, leveraging cellular systems for production of diverse chemicals via fermentation has garnered attention. Industrial fermentation, extending beyond strain efficiency and optimal conditions, necessitates a profound understanding of microorganism growth characteristics. Specific growth rate (SGR) is designated as a key variable due to its influence on cellular physiology, product synthesis rates and end-product quality. Despite its significance, the lack of real-time measurements and robust control systems hampers SGR control strategy implementation. The narrative in this contribution delves into the challenges associated with the SGR control and presents perspectives on various control strategies, integration of soft-sensors for real-time measurement and control of SGR. The discussion highlights practical and simple SGR control schemes, suggesting their seamless integration into industrial fermenters. Recommendations provided aim to propose new algorithms accommodating mechanistic and data-driven modelling for enhanced progress in industrial fermentation in the context of sustainable bioprocessing.
在可持续发展的时代，利用细胞系统通过发酵生产各种化学品引起了关注。工业发酵不仅需要提高菌株效率和优化条件，还需要深入了解微生物的生长特性。比生长速率（specific growth rate，SGR）是一个关键变量，因为它会影响细胞生理学、产物合成率和最终产物质量。尽管比生长速率很重要，但缺乏实时测量和强大的控制系统限制了比生长速率控制策略的实施。本文讨论了比生长速率控制所面临的挑战，并介绍了各种控制策略、用于实时测量和控制比生长速率的软传感器的集成。讨论强调了实用且简单的比生长速率控制方案，并建议将其无缝集成到工业发酵罐中。提出的建议旨在提出新的算法，以适应基于机理和数据驱动的建模，以在可持续生物加工的背景下促进工业发酵的发展。
