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多分析物生物过程监测工作流程,通过在线近红外光谱法对产黄青霉发酵进行演示。

Workflow for multi-analyte bioprocess monitoring demonstrated on inline NIR spectroscopy of P. chrysogenum fermentation.

机构信息

RECENDT - Research Center for Non-Destructive Testing GmbH, Altenberger Straße 69, 4040, Linz, Austria.

Institute of Chemical Engineering, University of Vienna, Am Getreidemarkt 9/166, 1060, Vienna, Austria.

出版信息

Anal Bioanal Chem. 2017 Jan;409(3):797-805. doi: 10.1007/s00216-016-9918-9. Epub 2016 Sep 17.

DOI:10.1007/s00216-016-9918-9
PMID:27640207
Abstract

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. Graphical abstract Flowchart illustrating the workflow for feasibility studies and implementation of models for inline monitoring of Ammonia, Biomass, Phenoxyacetic acid and Penicillin.

摘要

傅里叶变换近红外(FT-NIR)光谱结合多元分析在生物过程中已经应用了几十年。然而,该领域发表的论文都是特定案例,并没有专注于为社区提供通用的实验工作流程,特别是对于多分析物过程的标准设计实验(DoE)可能需要大量的测量。本文提出了一种在多分析物发酵过程中进行 FT-NIR 光谱仪可行性研究和在线实施的工作流程。该工作流程应用于产晶青霉素发酵过程中,其中关键分析物之间的化学结构和生长趋势相似,以及通气和生长真菌使得任务具有挑战性:首先,使用 FT-NIR 离线测量纯分析物,并使用主成分分析进行聚类。为了研究获得的聚类的可分离性,应用了基于加标法的设计实验方法。使用离线和在线数据对可分离分析物进行多元建模,然后比较不同模型的性质。最后,通过异常值诊断来设置模型输出的约束条件。结果表明,生物量、青霉素(PEN)、苯氧乙酸(POX)、氨和生物量可以通过预测的均方根误差分别为 2.62g/L、0.34g/L、0.51g/L 和 18.3mM 来分离。

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