Accounting for transient changes in bioprocess conditions for robust process monitoring and improved control of microalgal processes

Microalgal biotechnology and the production of microalgae-derived products are promising technologies in the industrial transformation to create a more circular and biobased economy with net zero carbon footprint.

For the production of microalgae, many process conditions have to be controlled according to specific environmental requirements by the microalgal strain of interest. These requirements include for example the control of process acidity and temperature to be maintained in identical range to the biological niche of the microorganism in nature. Aside from these more general process conditions, it is necessary to supply the microalgal cells with enough nutrients and energy to maintain their vitality and growth. Typically, energy supply of algae is achieved by illumination and consequent harvesting of light energy by the photosynthetic apparatus of the algae. The growth processes of microalgae cultures and multiplication of cells over time has the consequence that more nutrients and energy are required to maintain the culture and provide conditions for growth. As it is not possible to infinitely augment the supply of energy and nutrients proportionally to the increasing number of cells, this ultimately leads to process conditions of limited growth, where one or more factors are less available per cell and thereby limit the speed of cell growth. Such shifts from growth assuring into limiting conditions often trigger the cells to not only grow slower but also undergo changes in cell internal processes and in their morphology. Some of these changes are due to evolutional traits of microalgae and can be seen as a microalgal skill set that can actively be exploited. By helping microalgae in adjusting to their constantly changing natural environments which are governed by daily and seasonal fluctuations in light, temperature, and nutrient levels, these response mechanisms give algae their versatility and robustness.

Figure 1. Batch cultivation of Nannochloropsis oceanica.

In many cases these mechanisms are employed intentionally in industrial productions. This way, by actively changing certain process conditions, one can force the algae cultures into metabolic states where the production of a byproduct of interest is enhanced. However, not all such changes in cell properties seen in microalgae are a consequence of internal reaction mechanisms: transient cell alterations might also be a result of the degradation of vital microalgal components and consequently cell death. For these reasons, the task of process monitoring is of major importance to the design of industrially feasible microalgal productions.

High levels of control which are demanded in industry raise the urge for monitoring techniques that supply operators constantly and reliably with information on all important process parameters at a fast rate and with minimal time delays between measurement and control action. Accuracy and reliability of measurements for general biological quantities must not be susceptive to changes in cell state, as cells might change their properties without changes to their overall quantity. At the same time, the monitoring systems should also detect fluctuations in cell properties in order to identify whether metabolic shifts occur and to distinguish between intentionally exploited mechanisms and unwanted processes happening such as culture deaths.

These ambiguous requirements to monitoring growing cell cultures cannot be satisfied by analyzing and describing the process through one single measurement technique only. For instance, the analysis of dry weight concentrations, which is a commonly employed method to describe developments of bioprocesses, does give a good estimate about the total biomass being produced. However, this measure does not differentiate whether an increase in biomass happened because of cell division and growth or due to the enrichment of cells with byproducts like carbohydrates that expand them in size and mass without further cell division.

The assessment of biological growth through elemental mass balancing and design of biomass and bioproduct predictors by a software sensor-based approach are promising approaches for the design of metabolic state sensitive monitoring of microalgal processes.

While elemental mass balancing, which is based on laws of mass conservation, allows to describe biomass enhancements as a general measure of quantities, it enables to certain degrees the differentiation of biomass into characteristic groups. The increased productivity of such classes of molecules can simultaneously be detected and described through changes in the ratios between different elemental conversion rates. The estimation of built products and byproducts is subsequently done based on stoichiometric model assumptions of growth and respiration.

Soft sensing approaches have the advantage of using multiple parameters from obtained sensor networks data for estimation of parameters. Thereby they allow not only prediction of otherwise unmeasurable factors to the process but also they can be designed to account for changing process conditions, rendering them robust parameter estimators.

In this project we develop software sensors to monitor elemental conversion rates during microalgae growth. By employing elemental mass balancing approaches to these conversion rates, we aim to simultaneously estimate biomass evolution and biomass differentiation on-line and reduce disrupting effects of changing cell properties and process conditions. The focus of this project is set to oxygen, carbon dioxide and nitrogen as these compounds account for a mass fraction of ~90% of microalgal biomass.

Nitrogen is one of the essential macronutrients for balanced growth of microalgae. Its uptake rates are closely tied to accumulation of other byproducts such as lipids and carbohydrates in microalgae. Optimal microalgal biomass and lipid production therefore will require strategies with precise control of nitrogen levels to meet the optimal trade-off between promoting microalgal growth and enhancing lipid productivity. Current strategies of measuring nitrogen uptake require the collection of samples and time-demanding sample processing and analysis, making them unsuitable for automized process control.

Figure 2. On-line elemental mass balancing employs multiple conversion rates to determine process states and development of microalgal growth processes.

The investigated approach for soft sensing nitrogen uptake rates in microalgae relies on interaction of charged nitrogen species such as nitrate and ammonium and the overall charge balance of process medium. The uptake of the two molecular nitrogen species changes the equilibrium of charge balance and can thereby cause protonation or deprotonation of culture medium, which can be seen by shifting pH values during growth and nitrogen uptake processes. These shifts might be corrected by a pH dependent strategy of nitrogen supply in form of acids or bases to simultaneously tackle protonation and deprotonation of the process.

by Henrik Geltner