Fluorescence Techniques for Bioprocess Monitoring

Anton, Fabienne; Lindemann, Carsten; Hitzmann, Bernd; Reardon, Kenneth F.; Scheper, Thomas

doi:10.1002/9780470054581.eib632

Cited by 2 publications

(6 citation statements)

References 24 publications

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“…Indeed, fluorescence spectra contain valuable information concerning cells and process variables (e.g., biomass and cell density). Thus, fluorescence spectroscopy combined with chemometric tools offers deeper insight into biological processes resulting in easier bioprocess monitoring, optimization, and control [75]. In fact, multivariate statistical methods are needed because, similar to other spectroscopic methods, fluorescence spectra recorded during a fermentation process result in a high data volume, and so chemometric methods are usually needed [e.g., PCA, PLS regression, and artificial neural networks (ANN)] [37].…”

Section: Fluorescence Spectroscopymentioning

confidence: 99%

Online Analysis for Industrial Bioprocesses

Veloso

Ferreira

2017

Current Developments in Biotechnology and Bioengineering

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implementation as well as any other monitoring and control strategy depends on: (1) the availability of robust, reliable, low-cost, easy-to-use online/at-line sensors; (2) a complete understanding of the variability inherent in the bioprocess and introduced by the raw materials; and (3) the availability of sufficient time to develop a process that is amenable to the application of any online monitoring or control procedure during manufacturing [5]. However, it may be difficult to implement monitoring and control strategies because they require the use of experimental design tools, which for some industries such as biopharmaceuticals implies a high-cost, time-consuming procedure.On the other hand, several studies showed the advantages of developing mathematical models for the design, optimization, and bioprocess control. However, the vast majority of industrial processes are still controlled and optimized without the explicit use of these models. Nevertheless, the development of mathematical models that can describe bioprocesses has become essential because it is usually cheaper to model a system and simulate its operating conditions than to perform laboratory experiments. In some cases, apart from the economic point of view, there are other practical reasons, such as safety and ethical questions that make experimentation impracticable in real systems [6,7].Mathematical modeling, monitoring, and the real-time control of bioprocesses is a major challenge for biotechnologists and control engineers, leaving them the task of creating communication platforms among themselves and the industry so that the novel techniques that are developed can be used on an industrial level.The development of modeling strategies, real-time monitoring, control, and optimization is necessary to guarantee operational reproducibility, quality control, and run-torun consistency for both developmental and scale-up purposes [8].However, the significant uncertainty of the models' structure and parameters, and the nonlinear and dynamic nature of these systems make bioprocesses modeling, monitoring, and control a difficult and challenging task. Also, implementation of the most suitable type of automated analysis is a main difficulty.Automated analysis can be performed in two ways: by using a measurement probe inside the reactor, avoiding the need for sampling; or by automated sampling and subsequent sample analysis. The main drawback to the first approach is the scarcity or even lack of inexpensive and robust probes able to allow direct and in-line measurements of state variables. For the latter, expensive, time-consuming, and mostly offline methodologies (e.g., chromatography, electrophoresis, and mass spectrometry) are usually applied that required highly skilled technicians. Nevertheless, although it is rarely available, timely process information about fermentation biomass, substrates, intermediates, products, and nutrients is required to make effective control decisions [9,10]. For instance, in a bioprocess it is crucial to keep cells alive ...

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Section: Fluorescence Spectroscopymentioning

confidence: 99%

Online Analysis for Industrial Bioprocesses

Veloso

Ferreira

2017

Current Developments in Biotechnology and Bioengineering

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“…Often, this does not allow for fast and real-time decisions to monitor and control the process. Some efforts have been conducted to find alternative analytical techniques that allow for in situ and online monitoring and control of the process, like pH, temperature, and dissolved oxygen . They should avoid the use of chemical reagents and waste production, allowing instantaneous data acquisition without time delay and achieving higher efficiency, productivity, and optimization.…”

Section: Introductionmentioning

confidence: 99%

“…Some efforts have been conducted to find alternative analytical techniques that allow for in situ and online monitoring and control of the process, like pH, temperature, and dissolved oxygen. 3 They should avoid the use of chemical reagents and waste production, allowing instantaneous data acquisition without time delay and achieving higher efficiency, productivity, and optimization. The development of those innovative analytical tools increases the possibility of an early detection of deviations from the expected process.…”

Section: ■ Introductionmentioning

confidence: 99%

“…The development of those innovative analytical tools increases the possibility of an early detection of deviations from the expected process. 3,4 Fluorescence spectroscopy emerged as a highly promising tool for in situ and online monitoring of biological systems through the use of an optical fiber probe. 5 As the probe can be interfaced in the system, there is no risk of contamination nor sample consumption, making the technique non-invasive and non-destructive.…”

Section: ■ Introductionmentioning

confidence: 99%

“…They should avoid the use of chemical reagents and waste production, allowing instantaneous data acquisition without time delay and achieving higher efficiency, productivity, and optimization. The development of those innovative analytical tools increases the possibility of an early detection of deviations from the expected process. , …”

Section: Introductionmentioning

confidence: 99%

See 2 more Smart Citations

Acidogenic Fermentation of Brewers’ Spent Grain Monitored through Two-Dimensional Fluorescence Spectroscopy

Guarda

Costa

Gil

et al. 2023

ACS Sustainable Chem. Eng.

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Biological systems are commonly controlled and monitored through offline and time-consuming tools, which often impairs an effective and real-time response to counteract system disturbances. The feasibility of using two-dimensional (2D) fluorescence spectroscopy as a non-invasive, non-destructive, and real-time procedure to monitor the acidogenic fermentation of brewer’s spent grain (BSG) in a granular sludge reactor was evaluated. For that, the effect of pH fluctuations on the system response was used as a model to ascertain the 2D fluorescence spectroscopy applicability to monitor the process performance, namely, to predict the fermentation products (FP) and the soluble protein (SProt) concentrations in the effluent stream through mathematical analysis. The pH fluctuations over the course of the reactor’s operation altered the granules’ microbiome composition, leading to different effluent FP profiles. Fluorescence excitation–emission matrices (EEMs) were used with projection to latent structures (PLS) modeling to predict the FP and SProt concentrations in the effluent with average errors below 0.75 and 0.43 g L–1, respectively. Both models were able to capture the tendency of the data even when the accuracy of prediction was not so high. The combined approach of using 2D fluorescence spectroscopy and mathematical analysis seemed promising for real-time monitoring of the acidogenic fermentation of complex substrates.

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Fluorescence Techniques for Bioprocess Monitoring

Cited by 2 publications

References 24 publications

Online Analysis for Industrial Bioprocesses

Online Analysis for Industrial Bioprocesses

Acidogenic Fermentation of Brewers’ Spent Grain Monitored through Two-Dimensional Fluorescence Spectroscopy

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