Comparison of different estimation techniques for biomass concentration in large scale yeast fermentation

A Hybrid Model Simulating Multi-Stage Continuous Fermentation of Saccharomyces cerevisiae

The performance of industrial strains has gradually improved with the rapid development of synthetic biotechnology. The production efficiency of traditional batch and fed-batch culture is limited and product quality varies since both are dynamic processes, whereas multi-stage continuous culture can maximise the production efficiency of specific fermentation processes and achieve consistent product quality. However, each single-stage fermentation under multi-stage continuous fermentation requires accurate steady-state control, and a model with adequate accuracy is required for designing and controlling a multi-stage continuous fermentation process. At present, there are few reports on kinetic models for the control of multi-stage continuous fermentation. In this work, we constructed a hybrid model for Saccharomyces cerevisiae multi-stage continuous culture, taking both oxygen limitation and Crabtree effect. The accuracy of the model was ∼80%, the advantages and limitations of the model are discussed and a potential improvement strategy is proposed.

Exploring the impact of magnetic fields on biomass production efficiency under aerobic and anaerobic batch fermentation of Saccharomyces cerevisiae

In this work, the effect of moderate electromagnetic fields (2.5, 10, and 15 mT) was studied using an immersed coil inserted directly into a bioreactor on batch cultivation of yeast under both aerobic and anaerobic conditions. Throughout the cultivation, parameters, including CO2 levels, O2 saturation, nitrogen consumption, glucose uptake, ethanol production, and yeast growth (using OD 600 measurements at 1-h intervals), were analysed. The results showed that 10 and 15 mT magnetic fields not only statistically significantly boosted and sped up biomass production (by 38-70%), but also accelerated overall metabolism, accelerating glucose, oxygen, and nitrogen consumption, by 1-2 h. The carbon balance analysis revealed an acceleration in ethanol and glycerol production, albeit with final concentrations by 22-28% lower, with a more pronounced effect in aerobic cultivation. These findings suggest that magnetic fields shift the metabolic balance toward biomass formation rather than ethanol production, showcasing their potential to modulate yeast metabolism. Considering coil heating, opting for the 10 mT magnetic field is preferable due to its lower heat generation. In these terms, we propose that magnetic field can be used as novel tool to increase biomass yield and accelerate yeast metabolism.

Estimation of Chlamydomonas reinhardtii biomass concentration from chord length distribution data

A novel method to estimate the concentration of Chlamydomonas reinhardtii biomass was developed. The method employs the chord length distribution information gathered by means of a focused beam reflectance probe immersed in the culture sample and processes the data through a feedforward multilayer perceptron. The multilayer perceptron architecture was systematically optimised through the application of a simulated annealing algorithm. The method developed can predict the concentration of microalgae with acceptable accuracy and, with further development, it could be implemented online to monitor the aggregation status and biomass concentration of microalgal cultures.

Event triggered state estimation techniques for power systems with integrated variable energy resources

For many decades, state estimation (SE) has been a critical technology for energy management systems utilized by power system operators. Over time, it has become a mature technology that provides an accurate representation of system state under fairly stable and well understood system operation. The integration of variable energy resources (VERs) such as wind and solar generation, however, introduces new fast frequency dynamics and uncertainties into the system. Furthermore, such renewable energy is often integrated into the distribution system thus requiring real-time monitoring all the way to the periphery of the power grid topology and not just the (central) transmission system. The conventional solution is two fold: solve the SE problem (1) at a faster rate in accordance with the newly added VER dynamics and (2) for the entire power grid topology including the transmission and distribution systems. Such an approach results in exponentially growing problem sets which need to be solver at faster rates. This work seeks to address these two simultaneous requirements and builds upon two recent SE methods which incorporate event-triggering such that the state estimator is only called in the case of considerable novelty in the evolution of the system state. The first method incorporates only event-triggering while the second adds the concept of tracking. Both SE methods are demonstrated on the standard IEEE 14-bus system and the results are observed for a specific bus for two difference scenarios: (1) a spike in the wind power injection and (2) ramp events with higher variability. Relative to traditional state estimation, the numerical case studies showed that the proposed methods can result in computational time reductions of 90%. These results were supported by a theoretical discussion of the computational complexity of three SE techniques. The work concludes that the proposed SE techniques demonstrate practical improvements to the computational complexity of classical state estimation. In such a way, state estimation can continue to support the necessary control actions to mitigate the imbalances resulting from the uncertainties in renewables.

Improved synchronous light scattering method for measuring baker's yeast biomass using thickened suspensions

Measuring yeast biomass is important in the processes of microbial fermentations. It has been demonstrated that synchronous light scattering (SLS) signals could be applied for the quantification of model bioparticles such as Saccharomyces cerevisiae. In this study, an improved synchronous light scattering method was developed for yeast biomass estimation. The settlement of yeast cells during SLS signals measuring process was studied, and hydrolysis anionic polyacrylamide was added into yeast suspensions to increase the stability of the cells in liquid environment. By simultaneously scanning both the excitation and emission monochromators of a common spectrofluorometer with same starting excitation and emission wavelength (namely, ∆λ = 0), the SLS intensity was found to be proportional to the yeast concentration in the range from 0 to 4.9 × 10(6) cell/mL (R (2) = 0.9907), the detection limit is 8.1 × 10(3) cell/mL. The developed method exhibited good stability and sensitivity in the recovery test and growth curve drawing process, demonstrating the potential of the method in practical application of biomass estimation.