Faassen Saskia M, Hitzmann Bernd
Process Analytics and Cereal Science, Institute of Food Science and Biotechnology, University Hohenheim, Garbenstraße 23, 70599 Stuttgart, Germany.
Sensors (Basel). 2015 Apr 30;15(5):10271-91. doi: 10.3390/s150510271.
On-line sensors for the detection of crucial process parameters are desirable for the monitoring, control and automation of processes in the biotechnology, food and pharma industry. Fluorescence spectroscopy as a highly developed and non-invasive technique that enables the on-line measurements of substrate and product concentrations or the identification of characteristic process states. During a cultivation process significant changes occur in the fluorescence spectra. By means of chemometric modeling, prediction models can be calculated and applied for process supervision and control to provide increased quality and the productivity of bioprocesses. A range of applications for different microorganisms and analytes has been proposed during the last years. This contribution provides an overview of different analysis methods for the measured fluorescence spectra and the model-building chemometric methods used for various microbial cultivations. Most of these processes are observed using the BioView® Sensor, thanks to its robustness and insensitivity to adverse process conditions. Beyond that, the PLS-method is the most frequently used chemometric method for the calculation of process models and prediction of process variables.
用于检测关键工艺参数的在线传感器对于生物技术、食品和制药行业的过程监测、控制和自动化来说是很有必要的。荧光光谱法是一种高度发达的非侵入性技术,能够在线测量底物和产物浓度或识别特征工艺状态。在培养过程中,荧光光谱会发生显著变化。通过化学计量学建模,可以计算预测模型并将其应用于过程监控,以提高生物过程的质量和生产率。在过去几年中,已经提出了一系列针对不同微生物和分析物的应用。本文介绍了用于测量荧光光谱的不同分析方法以及用于各种微生物培养的模型构建化学计量学方法。由于其坚固性和对不利工艺条件不敏感,这些过程大多使用BioView®传感器进行监测。除此之外,偏最小二乘法(PLS方法)是计算过程模型和预测过程变量时最常用的化学计量学方法。