Dabros Michal, Amrhein Michael, Bonvin Dominique, Marison Ian W, von Stockar Urs
Laboratory of Chemical and Biological Engineering, Institute of Chemical Sciences and Engineering, Ecole Polytechnique Fédérale de Lausanne, CH-1015 Lausanne, Switzerland.
Biotechnol Prog. 2009 Mar-Apr;25(2):578-88. doi: 10.1002/btpr.143.
Real-time data reconciliation of concentration estimates of process analytes and biomass in microbial fermentations is investigated. A Fourier-transform mid-infrared spectrometer predicting the concentrations of process metabolites is used in parallel with a dielectric spectrometer predicting the biomass concentration during a batch fermentation of the yeast Saccharomyces cerevisiae. Calibration models developed off-line for both spectrometers suffer from poor predictive capability due to instrumental and process drifts unseen during calibration. To address this problem, the predicted metabolite and biomass concentrations, along with off-gas analysis and base addition measurements, are reconciled in real-time based on the closure of mass and elemental balances. A statistical test is used to confirm the integrity of the balances, and a non-negativity constraint is used to guide the data reconciliation algorithm toward positive concentrations. It is verified experimentally that the proposed approach reduces the standard error of prediction without the need for additional off-line analysis.
本文研究了微生物发酵过程中过程分析物和生物质浓度估计的实时数据校正。在酿酒酵母的分批发酵过程中，使用一台预测过程代谢物浓度的傅里叶变换中红外光谱仪与一台预测生物质浓度的介电光谱仪并行工作。由于在校准过程中未观察到仪器和过程漂移，为两台光谱仪离线开发的校准模型预测能力较差。为了解决这个问题，基于质量和元素平衡的封闭性，对预测的代谢物和生物质浓度以及废气分析和碱添加测量进行实时校正。使用统计检验来确认平衡的完整性，并使用非负约束来指导数据校正算法朝着正浓度方向进行。实验验证了所提出的方法在无需额外离线分析的情况下降低了预测的标准误差。
