Workflow for multi-analyte bioprocess monitoring demonstrated on inline NIR spectroscopy of P. chrysogenum fermentation
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- 作者：Pekka Luoma ; Aydin Golabgir ; Markus Brandstetter…
- 关键词：Near ; infrared ; Spectroscopy ; P. chrysogenum ; Inline ; Process analysis ; DoE
- 刊名：Analytical and Bioanalytical Chemistry
- 出版年：2017
- 出版时间：January 2017
- 年：2017
- 卷：409
- 期：3
- 页码：797-805
- 全文大小：
- 刊物类别：Chemistry and Materials Science
- 刊物主题：Analytical Chemistry; Biochemistry, general; Laboratory Medicine; Characterization and Evaluation of Materials; Food Science; Monitoring/Environmental Analysis;
- 出版者：Springer Berlin Heidelberg
- ISSN：1618-2650
- 卷排序：409
文摘
Fourier transform near-infrared (FT-NIR) spectroscopy combined with multivariate analysis has been applied in bioprocesses for a couple of decades. Nevertheless the papers published in this field are case-specific and do not focus on providing the community generic workflows to conduct experiments, especially as a standard Design of Experiment (DoE) for a multi-analyte process might require overwhelming amount of measurements. In this paper, a workflow for feasibility studies and inline implementation of FT-NIR spectrometer in multi-analyte fermentation processes is presented. The workflow is applied to Penicillium crysogenum fermentation, where the similarities in chemical structures and growth trends between the key analytes together with the aeration and growing fungi make the task challenging: first, the pure analytes are measured off-line with FT-NIR and clustered using principal component analysis. To study the separability of the gained clusters, a DoE approach by spiking is applied. The multivariate modelling of the separable analytes is conducted using the off-line and inline data followed by a comparison of the properties of the different models. Finally, the model output constraints are set by means of outlier diagnostics. As a result, biomass, penicillin (PEN), phenoxyacetic acid (POX), ammonia and biomass were shown to be separable with root mean square error of predictions of 2.62 g/l, 0.34 g/l, 0.51 g/l and 18.3 mM, respectively.