Yang Chen, Lingli Chen, Meijin Guo, Xu Li, Jinsong Liu, Xiaofeng Liu, Zhongbing Chen, Xiaojun Tian, Haoyue Zheng, Xiwei Tian, Ju Chu, Yingping Zhuang
State Key Laboratory of Bioreactor Engineering, East China University of Science and Technology, 130 Meilong Road, P.O. box 329, Shanghai, 200237, People's Republic of China.
SDIC Biotech Investment Co. Ltd, Beijing, 100000, China.
Bioresour Bioprocess. 2021 Oct 5;8(1):96. doi: 10.1186/s40643-021-00452-9.
The fermentation process is dynamically changing, and the metabolic status can be grasped through real-time monitoring of environmental parameters. In this study, a real-time and on-line monitoring experiment platform for substrates and products detection was developed based on non-contact type near-infrared (NIR) spectroscopy technology. The prediction models for monitoring the fermentation process of lactic acid, sophorolipids (SLs) and sodium gluconate (SG) were established based on partial least-squares regression and internal cross-validation methods. Through fermentation verification, the accuracy and precision of the NIR model for the complex fermentation environments, different rheological properties (uniform system and multi-phase inhomogeneous system) and different parameter types (substrate, product and nutrients) have good applicability, and R was greater than 0.98, exhibiting a good linear relationship. The root mean square error of prediction shows that the model has high credibility. Through the control of appropriate glucose concentration in SG fermentation as well as glucose and oil concentrations SLs fermentation by NIR model, the titers of SG and SLs were increased to 11.8% and 26.8%, respectively. Although high cost of NIR spectrometer is a key issue for its wide application in an industrial scale. This work provides a basis for the application of NIR spectroscopy in complex fermentation systems.
发酵过程是动态变化的,通过对环境参数的实时监测可以掌握代谢状态。在本研究中,基于非接触式近红外(NIR)光谱技术开发了一个用于底物和产物检测的实时在线监测实验平台。基于偏最小二乘回归和内部交叉验证方法,建立了监测乳酸、槐糖脂(SLs)和葡萄糖酸钠(SG)发酵过程的预测模型。通过发酵验证,NIR模型对于复杂发酵环境、不同流变特性(均匀体系和多相非均匀体系)以及不同参数类型(底物、产物和营养物质)具有良好的适用性,相关系数R大于0.98,呈现出良好的线性关系。预测均方根误差表明该模型具有较高的可信度。通过NIR模型控制SG发酵中合适的葡萄糖浓度以及SLs发酵中葡萄糖和油的浓度,SG和SLs的效价分别提高到了11.8%和26.8%。尽管NIR光谱仪成本高昂是其在工业规模上广泛应用的一个关键问题。这项工作为NIR光谱在复杂发酵系统中的应用提供了依据。