Novel strategy for the calorimetry-based control of fed-batch cultivations of saccharomyces cerevisiae

Typical controllers for fed-batch cultivations are based on the estimation and control of the specific growth rate in real time. Biocalorimetry allows one to measure a heat signal proportional to the substrate consumed by cells. The derivative of this heat signal is usually used to evaluate the specific growth rate, introducing noise to the resulting estimate. To avoid this, this study investigated a novel controller based directly on the heat signal. Time trajectories of the heat signal setpoint were modelled for different specific growth rates, and the controller was set to follow this dynamic setpoint. The developed controller successfully followed the setpoint during aerobic cultivations of Saccharomyces cerevisiae, preventing the Crabtree effect by maintaining low glucose concentrations. With this new method, fed-batch cultivations of S. cerevisiae could be reliably controlled at specific growth rates between 0.075 h−1 and 0.20 h−1, with average root mean square errors of 15 ± 3%

Cole-Cole, linear and multivariate modeling of capacitance data for on-line monitoring of biomass

This work evaluates three techniques of calibrating capacitance (dielectric) spectrometers used for on-line monitoring of biomass: modeling of cell properties using the theoretical Cole-Cole equation, linear regression of dual-frequency capacitance measurements on biomass concentration, and multivariate (PLS) modeling of scanning dielectric spectra. The performance and robustness of each technique is assessed during a sequence of validation batches in two experimental settings of differing signal noise. In more noisy conditions, the Cole-Cole model had significantly higher biomass concentration prediction errors than the linear and multivariate models. The PLS model was the most robust in handling signal noise. In less noisy conditions, the three models performed similarly. Estimates of the mean cell size were done additionally using the Cole-Cole and PLS models, the latter technique giving more satisfactory result

The Use of Virtual Calibrations to Facilitate Understanding of Factor Analysis

Tutorial published on: http://www.chemometrics.se/File/VirtualCalibrations.pd

Materials science at Swiss universities of applied sciences

Copyright ©Swiss Chemical Society: CHIMIA, Volume 73, Numbers 7-8, August 2019, pp. 645-655(11)In the Swiss Universities of Applied Sciences, several research institutes are involved in Materials Science, with different approaches and applications fields. A few examples of recent projects from different groups of the University of Applied Sciences and Arts Western Switzerland (HES-SO), the Zurich University of Applied Sciences (ZHAW) and the University of Applied Sciences and Arts Northwestern Switzerland (FHNW) are given

Continuous monitoring of shelf lives of materials by application of data loggers with implemented kinetic parameters

The evaluation of the shelf life of, for example, food, pharmaceutical materials, polymers, and energetic materials at room or daily climate fluctuation temperatures requires kinetic analysis in temperature ranges which are as similar as possible to those at which the products will be stored or transported in. A comparison of the results of the evaluation of the shelf life of a propellant and a vaccine calculated by advanced kinetics and simplified 0th and 1st order kinetic models is presented. The obtained simulations show that the application of simplified kinetics or the commonly used mean kinetic temperature approach may result in an imprecise estimation of the shelf life. The implementation of the kinetic parameters obtained fromadvanced kinetic analyses into programmable data loggers allows the continuous online evaluation and display on a smartphone of the current extent of the deterioration of materials. The proposed approach is universal and can be used for any goods, any methods of shelf life determination, and any type of data loggers. Presented in this study, the continuous evaluation of the shelf life of perishable goods based on the Internet of Things (IoT) paradigm helps in the optimal storage/shipment and results in a significant decrease of waste

Optimization of broke recirculation in a newsprint mill

Problem statement and motivation -- Model -- Introduction and process description -- Simulation development -- Simulation validation -- Optimization of the broke recirculation strategy -- Problem statement and description -- Current operating strategies -- Objective function developpement -- Solution approach -- Case study

Robust model development and enhancement techniques for improved on-line spectroscopic monitoring of bioprocesses

The recent phenomenal growth of the field of biotechnology has contributed to a mounting pressure to improve process efficiency and productivity and to increase the quality and safety of end-products. This demand gave rise to the discipline of on-line bioprocess monitoring encompassing tools that provide a live analytical window into the process and create extensive opportunities for process development, control and optimization. Among these tools, on-line spectroscopy has surfaced as one of the prominent techniques of monitoring the concentration of process metabolites and biomass. Unfortunately, one of the major obstacles currently impeding the industrial spread of the technology is the chronic lack of robustness and long-term stability of spectrometers in on-line monitoring conditions. The work presented in this dissertation aims to explore various ways of improving the reliability of spectroscopic bioprocess monitoring instruments without interfering with their real-time functionality. A Fourier-transform mid-infrared (FTIR) and a dielectric (capacitance) spectrometer are used as the model instruments in a series of experiments involving the cultivation of yeasts. A general review of methods that help maintain the on-line reliability of bioprocess spectrometers is presented first. A clear distinction is made between techniques that involve retrospective reprocessing of the obtained predictions using off-line measurements, and methods that perform the signal or calibration model correction in real-time. A case study, included in the review, demonstrates the effectiveness of some of the latter techniques in correcting mid-IR spectral drift comparable in magnitude of absorbance to a pure component spectrum of glucose at 10 g/l. It is shown that the drift can be significantly reduced using techniques such as spectrum derivation, spectral anchoring and Orthogonal Signal Correction (OSC). Proposed next is a technique to generate on-line reference standards for the FTIR without the need of sampling. The method involves the periodic injection of small amounts of the monitored metabolites into the culture medium. The corresponding measured differences in the spectra are used as reference measurements for recalibrating the model in real-time based on the technique of Dynamic Orthogonal Projection (DOP). Applying this approach leads to a decrease, ranging from 25 to 50 %, in the standard error of prediction of metabolite concentrations. The following study compares three distinct methods of calibrating a dielectric spectrometer: fitting capacitance data to the theoretical Cole-Cole equation, correlating capacitance measurements linearly to biomass concentration and the modeling of scanning capacitance spectra using multivariate (PLS) analysis. The performance and robustness of each calibration technique is assessed during a sequence of validation batches in two experimental settings differing in the level of signal noise. The linear and PLS models outperform the Cole-Cole model in terms of biomass concentration prediction error, particularly in the more noisy conditions. The PLS model proves to be the most robust in rejecting the signal variability. Estimates of the mean cell size are additionally done using the Cole-Cole and PLS models, the latter technique giving more precise results. Finally, in a study involving the simultaneous use of the FTIR and capacitance spectrometers, data reconciliation is shown to improve the on-line prediction of process analytes and biomass. The concentrations predicted by both spectrometers are reconciled in real-time based on mass and elemental balances involving off-gas analysis and measurements of base addition. A statistical test is used to confirm the integrity of the balances before the reconciliation. The technique leads to a significant reduction in the standard error of prediction for all the components involved

Control of specific growth rate in fed-batch bioprocesses: novel controller design for improved noise management

Accurate control of the specific growth rate (µ) of microorganisms is dependent on the ability to quantify the evolution of biomass reliably in real time. Biomass concentration can be monitored online using various tools and methods, but the obtained signal is often very noisy and unstable, leading to inaccuracies in the estimation of μ. Furthermore, controlling the growth rate is challenging as the process evolves nonlinearly and is subject to unpredictable disturbances originating from the culture’s metabolism. In this work, a novel feedforward-feedback controller logic is presented to counter the problem of noise and oscillations in the control variable and to address the exponential growth dynamics more effectively. The controller was tested on fed-batch cultures of Kluyveromyces marxianus, during which μ was estimated in real time from online biomass concentration measurements obtained with dielectric spectroscopy. It is shown that the specific growth rate can be maintained at different setpoint values with an average root mean square control error of 23 ± 6%

Control of specific growth rate in fed-batch bioprocesses ::novel controller design for improved noise management

Accurate control of the specific growth rate (µ) of microorganisms is dependent on the ability to quantify the evolution of biomass reliably in real time. Biomass concentration can be monitored online using various tools and methods, but the obtained signal is often very noisy and unstable, leading to inaccuracies in the estimation of μ. Furthermore, controlling the growth rate is challenging as the process evolves nonlinearly and is subject to unpredictable disturbances originating from the culture’s metabolism. In this work, a novel feedforward-feedback controller logic is presented to counter the problem of noise and oscillations in the control variable and to address the exponential growth dynamics more effectively. The controller was tested on fed-batch cultures of Kluyveromyces marxianus, during which μ was estimated in real time from online biomass concentration measurements obtained with dielectric spectroscopy. It is shown that the specific growth rate can be maintained at different setpoint values with an average root mean square control error of 23 ± 6

Preventing Overflow Metabolism in Crabtree-Positive Microorganisms through On-Line Monitoring and Control of Fed-Batch Fermentations

At specific growth rates above a particular critical value, Crabtree-positive microorganisms exceed their respiratory capacity and enter diauxic growth metabolism. Excess substrate is converted reductively to an overflow metabolite, resulting in decreased biomass yield and productivity. To prevent this scenario, the cells can be cultivated in a fed-batch mode at a growth rate maintained below the critical value, µcrit. This approach entails two major challenges: accurately estimating the current specific growth rate and controlling it successfully over the course of the fermentation. In this work, the specific growth rate of S. cerevisiae and E. coli was estimated from enhanced on-line biomass concentration measurements obtained with dielectric spectroscopy and turbidity. A feedforward-feedback control scheme was implemented to maintain the specific growth rate at a setpoint below µcrit, while on-line FTIR measurements provided the early detection of the overflow metabolites. The proposed approach is in line with the principles of Bioprocess Analytical Technology (BioPAT), and provides a means to increase the productivity of Crabtree-positive microorganisms