Browsing by Subject "On-line process monitoring"

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    Development of an on-line process monitoring for yeast cultivations via 2D-fluorescence spectroscopy
    (2019) Assawajaruwan, Supasuda; Hitzmann, Bernd
    An optimum process is required in the field of food, pharmaceutical and biotechnological industry with the ultimate goal of achieving high productivity and high-quality products. In order to achieve this goal, there are many different parameters to be realized and controlled, e.g., physical, chemical and biological aspects of microbial bioprocesses. Microbial cultivations are a very complex process, therefore, reliable and efficient tools are required to receive as much real-time information for an on-line monitoring as possible, so that the processes can be controlled in time. The primary objective of this research was to apply a two-dimensional (2D) fluorescence spectroscopy to monitor glucose, ethanol and biomass concentrations of yeast cultivations. The measurement of one spectrum has 120 fluorescence intensity variables of excitation and emission wavelength combinations (WLCs) without consideration of the scattered light. To investigate which WLCs carry important and relevant information regarding the analyte concentrations, the three wavelength selection methods were implemented: a method based on loadings, variable importance in projection (VIP) and ant colony optimization. The five selected WLCs from each method for a particular analyte were evaluated by multiple linear regression (MLR) models. The selected WLCs, which showed the best predictive performance of the MLR models, were relevant to the analyte concentrations. Regarding the results of the MLR models, the most significant WLCs contained seven different excitation and emission wavelengths. They can be combined to have 38 WLCs for one spectrum based on the principle of fluorescence. They were in the area of NADH, tryptophan, pyridoxine, riboflavin and FAD/FMN. The 38 WLCs were used to predict the glucose, ethanol and biomass concentrations via partial least squares (PLS) regression. The best prediction from the PLS models with 38 WLCs had the percentage of root mean square error of prediction (pRMSEP) in the range of 3.1-6.3 %, which was not significantly different from the PLS models with the 120 variables. Therefore, the specific fluorescence sensor for yeast cultivations could be built with less filters, which would make it a low-cost device. The following plan of the research goal was to investigate the attribute of fluorophores inside cells in real time using a 2D fluorescence spectrometer. The considered intracellular fluorophores, such as NADH, tryptophan, pyridoxine, riboflavin and FAD/FMN were observed during the yeast cultivations under three different conditions: batch, fed-batch with the glucose pulse during a glucose growth phase (GP) and fed-batch with the glucose pulse during an ethanol growth phase (EP) after a diauxic shift. With the help of principal component analysis, the different states of the yeast cultivations, particularly the glucose pulse during EP, can be recognized and identified from the on-line fluorescence spectra. On the other hand, the change of the fluorescence spectra in the fed-batch process with the glucose pulse during GP was not recognizable. Remarkably, the intensities of the fluorophores due to the glucose pulse during EP did not change in the same direction. The fluorescence intensities of NADH and riboflavin increased, but the intensity of tryptophan, pyridoxine and FAD/FMN decreased. The conversion between tryptophan and NADH intensities was quantified as a proportional factor. It was calculated from the ratio of the area of NADH and tryptophan fluorescence intensity after the glucose addition until depletion. The proportional factor was independent on various glucose concentrations with the coefficient of determination, R2 = 0.999. The correlative intensity changes of these fluorophores demonstrate a metabolic switch from ethanol to glucose growth phase. Based on the previous experiments, a closed-loop control has been implemented for yeast cultivations. 2D fluorescence spectroscopy was applied for an on-line monitoring and control of yeast cultivations to attain pure oxidative metabolism. A glucose concentration is an important factor in a fed-batch process of Saccharomyces cerevisiae. Therefore, it has to be controlled under a critical concentration to avoid overflow metabolism and to gain high productivity of biomass. The characteristic of the NADH intensity can effectively identify the metabolic switch between oxidative and oxidoreductive states. Consequently, the feed rates were regulated using the NADH intensity as a metabolic signal. With this closed-loop control of the glucose concentration, a biomass yield was obtained at 0.5 gbiomass/gglucose. Additionally, ethanol production could be avoided during the controlled feeding phase. The fluorescence sensor with the signal of the NADH intensity has potential to control a glucose concentration under the critical value in real time. The experiments carried out show that 2D fluorescence spectroscopy has great potential in on-line monitoring and process control of the yeast cultivations. Consequently, it is promising to build up a compact and economical fluorescence sensor with the specific wavelengths using light-emitting diodes and photodiodes. The sensor would be a cost-effective and miniaturized device for routine analysis, which could be advantageous to real-time bioprocess monitoring.
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    Generic chemometric models for metabolite concentration prediction based on Raman spectra
    (2022) Yousefi-Darani, Abdolrahim; Paquet-Durand, Olivier; von Wrochem, Almut; Classen, Jens; Tränkle, Jens; Mertens, Mario; Snelders, Jeroen; Chotteau, Veronique; Mäkinen, Meeri; Handl, Alina; Kadisch, Marvin; Lang, Dietmar; Dumas, Patrick; Hitzmann, Bernd
    Chemometric models for on-line process monitoring have become well established in pharmaceutical bioprocesses. The main drawback is the required calibration effort and the inflexibility regarding system or process changes. So, a recalibration is necessary whenever the process or the setup changes even slightly. With a large and diverse Raman dataset, however, it was possible to generate generic partial least squares regression models to reliably predict the concentrations of important metabolic compounds, such as glucose-, lactate-, and glutamine-indifferent CHO cell cultivations. The data for calibration were collected from various cell cultures from different sites in different companies using different Raman spectrophotometers. In testing, the developed “generic” models were capable of predicting the concentrations of said compounds from a dilution series in FMX-8 mod medium, as well as from an independent CHO cell culture. These spectra were taken with a completely different setup and with different Raman spectrometers, demonstrating the model flexibility. The prediction errors for the tests were mostly in an acceptable range (<10% relative error). This demonstrates that, under the right circumstances and by choosing the calibration data carefully, it is possible to create generic and reliable chemometric models that are transferrable from one process to another without recalibration.