文献类型：期刊文献

英文题名：Real-time and on-line parallel detection of key fermentation process parameters by near-infrared spectroscopy in different environments

作者：Chen, Yang[1]; Chen, Lingli[1]; Guo, Meijin[1]; Li, Xu[1]; Liu, Jinsong[2]; Liu, Xiaofeng[2]; Chen, Zhongbing[3]; Tian, Xiaojun[2]; Zheng, Haoyue[2]; Tian, Xiwei[4]; Chu, Ju[1]; Zhuang, Yingping[5]

机构：[1] State Key Laboratory of Bioreactor Engineering, East China University of Science and Technology, China; [2] SDIC Biotech Investment Co. Ltd., Beijing, 100000, China; [3] Zhejiang Biok Co.Ltd, Zhongguan Industrial Park, China; [4] East China University of Science and Technology, China; [5] State Key Laboratory of Bioreactor Engineering, East China University of Science and Technology, Frontiers Science Center for Materiobiology and Dynamic Chemistry, East China University of Science and Technology, Shanghai, 200237, China

年份：2021

外文期刊名：Research Square

收录：EI(收录号：20220187173)

语种：英文

外文关键词：Fermentation - Infrared devices - Lactic acid - Least squares approximations - Mean square error - Process control - Sodium - Substrates

摘要：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 and sodium gluconate 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 R2 is greater than 0.90, exhibiting a good linear relationship. The root mean square error shows that the model has high credibility. This research provides a basis for the application of NIR spectroscopy in complex fermentation systems. ? 2021, CC BY.