Dynamic coupling of photoacclimation and photoinhibition in a model of microalgae growth

Improving microalgae growth modeling of outdoor cultivation with light history data using machine learning models: A comparative study

Accurate prediction of microalgae growth is crucial for understanding the impacts of light dynamics and optimizing production. Although various mathematical models have been proposed, only a few of them have been validated in outdoor cultivation. This study aims to investigate the use of machine learning algorithms in microalgae growth modeling. Outdoor cultivation data of Phaeodactylum tricornutum in flat-panel airlift photobioreactors for 50 days were used to compare the performance of Long Short-Term Memory (LSTM) and Support Vector Regression (SVR) with traditional models, namely Monod and Haldane. The results indicate that the machine learning models outperform the traditional models due to their ability to utilize light history as input. Moreover, the LSTM model shows an excellent ability to describe the light acclimation effect. Last, two potential applications of these models are demonstrated: 1) use as a biomass soft sensor and 2) development of an optimal harvest strategy for outdoor cultivation.

Theoretical growth rate of microalgae under high/low-flashing light

Dynamic light regimes strongly impact microalgal photosynthesis efficiency. Finding the optimal way to supply light is then a tricky problem, especially when the growth rate is inhibited by overexposition to light and, at the same time, there is a lack of light in the deepest part of the culture. In this paper, we use the Han model to study the theoretical microalgal growth rate by applying periodically two different light intensities. Two approaches are considered depending on the period of the light pattern. For a large light period, we demonstrate that the average photosynthetic rate can be improved under some conditions. Moreover, we can also enhance the growth rate at steady state as given by the PI-curve. Although, these conditions change through the depth of a bioreactor. This theoretical improvement in the range of 10-15% is due to a recovery of photoinhibited cells during the high irradiance phase. We give a minimal value of the duty cycle for which the optimal irradiance is perceived by the algae culture under flashing light regime.

Long-term assessment of the nutrient recovery capacity and biomass productivity of Scenedesmus almeriensis in raceway reactors using unprocessed urban wastewater

The present work aims to assess the treatment of unprocessed urban wastewater using the microalga Scenedesmus almeriensis. Two 12 m³ raceway reactors, one supplemented by wastewater and the second by chemical fertilizer, operating outdoors in a semi-continuous mode, were used for eight months. Results suggested that S. almeriensis can be produced in wastewater without affecting the photosynthetic apparatus reaching a productivity of 13 g·m^-2·day^-1 on average in both the systems. Furthermore, the nutrient content in terms of nitrogen, phosphorous and chemical oxygen demand of the wastewater was reduced under the European limitations during most of the period, with an average removal rate of 2.2, 0.2 and 3.0 g·m^-2·day^-1 respectively. Therefore, raceways demonstrated a high potential for microalgal production and successful biotreatment, proving robust and reliable. Finally, the effect of environmental conditions on biomass productivity of the clean system was evaluated in a model with high accuracy (R² = 0.9, p = 0.0002).

Modeling and Simulation of Photobioreactors with Computational Fluid Dynamics—A Comprehensive Review

Computational Fluid Dynamics (CFD) have been frequently applied to model the growth conditions in photobioreactors, which are affected in a complex way by multiple, interacting physical processes. We review common photobioreactor types and discuss the processes occurring therein as well as how these processes have been considered in previous CFD models. The analysis reveals that CFD models of photobioreactors do often not consider state-of-the-art modeling approaches. As a comprehensive photobioreactor model consists of several sub-models, we review the most relevant models for the simulation of fluid flows, light propagation, heat and mass transfer and growth kinetics as well as state-of-the-art models for turbulence and interphase forces, revealing their strength and deficiencies. In addition, we review the population balance equation, breakage and coalescence models and discretization methods since the predicted bubble size distribution critically depends on them. This comprehensive overview of the available models provides a unique toolbox for generating CFD models of photobioreactors. Directions future research should take are also discussed, mainly consisting of an extensive experimental validation of the single models for specific photobioreactor geometries, as well as more complete and sophisticated integrated models by virtue of the constant increase of the computational capacity.

Synergistic effect of growth conditions and organic carbon sources for improving biomass production and biodiesel quality by the microalga Choricystis minor var. minor

In the search for microalgae species with potential for biodiesel production, Choricystis minor var. minor has been seen as a promising source of biomass due to its high lipid content and the satisfactory characteristics of its fatty acid methyl esters (FAMEs). For this reason, the objective of this study was to investigate the synergistic effect of growth conditions and organic carbon sources on cultivation of this microalga. To do so, experimental cultivations were conducted in photoautotrophic, heterotrophic and mixotrophic metabolisms using glucose, fructose, glycerol or sucrose - in growth conditions that use organic carbon. Thus, growth parameters of the cultures were evaluated and at the end of the cultivations, FAMEs yield and profile were determined by gas chromatography, the efficiency of carbon conversion into biomass was evaluated and a microbial analysis was conducted. Regarding growth conditions, the findings have confirmed that, regardless of the organic carbon source used, the heterotrophic and mixotrophic metabolisms can present advantages over the photoautotrophic one. In addition, biomass production was higher with the use of glucose than with other organic carbon sources, regardless of growth condition (heterotrophic or mixotrophic). Moreover, cultivations with the addition of CO₂ have converted carbon into biomass less efficiently. On the other hand, photoautotrophic cultures presented the lowest bacterial load. In comparison to photoautotrophic and mixotrophic, heterotrophic cultures have led to lower FAMEs content and higher yields of unsaturated fatty acids. The most satisfactory FAMEs profile for biodiesel production was obtained with mixotrophic growth using fructose.

The promise of dawn: Microalgae photoacclimation as an optimal control problem of resource allocation

Photosynthetic microorganisms are known to adjust their photosynthetic capacity according to light intensity. This so-called photoacclimation process is thought to maximize growth at equilibrium, but its dynamics under varying conditions remains less understood. To tackle this problem, microalgae growth and photoacclimation are represented by a (coarse-grained) resource allocation model. Using optimal control theory (the Pontryagin maximum principle) and numerical simulations, we determine the optimal strategy of resource allocation to maximize microalgal growth rate over a time horizon. We show that, after a transient, the optimal trajectory approaches the optimal steady state, a behavior known as the turnpike property. Then, a bi-level optimization problem is solved numerically to estimate model parameters from experimental data. The fitted trajectory represents well a Dunaliella tertiolecta culture facing a light down-shift. Finally, we study photoacclimation dynamics under day/night cycle. In the optimal trajectory, the synthesis of the photosynthetic apparatus surprisingly starts a few hours before dawn. This anticipatory behavior has actually been observed both in the laboratory and in the field. This shows the algal predictive capacity and the interest of our method which predicts this phenomenon.

Models of microalgal cultivation for added-value products - A review

Microalgae are considered a promising feedstock for biorefineries given that their chemical composition - rich in carbohydrate and lipid - can be directed towards the co-production of various value-added fuels and chemicals. Production of microalgal biomass for biorefinery purposes requires the identification and establishment of optimal cultivation systems, a crucial yet complicated task due to the numerous factors (e.g. media composition, light, temperature) that simultaneously regulate biomass growth and intracellular composition. Modelling these biological processes, taking into account a single or multiple growth-limiting factors, offers a valuable tool to simulate, design and optimise the dynamics of microalgae cultivation. This review provides an overview of existing models developed to describe microalgal growth processes at the macroscopic scale (also termed black-box models) and discusses their formulation in detail. The black-box kinetic modelling frameworks are compiled into single-factor (6 formulations) and multiple-factor (32 formulations - further divided into non-interactive, additive, and interactive) growth kinetic models, as reported in more than 80 studies, for the prediction of biomass growth as a function of major operational factors such as media composition (e.g. nutrient concentration) and environmental factors (e.g. transient light and temperature). In addition, the review focuses on those models that further account for the production dynamics of two microalgal intracellular products with renowned potential as biorefinery substrates: carbohydrate and lipid molecules. Models of microalgal cultivation dynamics offer a robust engineering tool to understand the natural yet complex responses of microalgae to their growing environment and can help - if used appropriately - to optimise microalgae cultivation and increase the economic viability and sustainability of microalgal systems.

Microalgae: A Promising Source of Valuable Bioproducts

Microalgae are a group of autotrophic microorganisms that live in marine, freshwater and soil ecosystems and produce organic substances in the process of photosynthesis. Due to their high metabolic flexibility, adaptation to various cultivation conditions as well as the possibility of rapid growth, the number of studies on their use as a source of biologically valuable products is growing rapidly. Currently, integrated technologies for the cultivation of microalgae aiming to isolate various biologically active substances from biomass to increase the profitability of algae production are being sought. To implement this kind of development, the high productivity of industrial cultivation systems must be accompanied by the ability to control the biosynthesis of biologically valuable compounds in conditions of intensive culture growth. The review considers the main factors (temperature, pH, component composition, etc.) that affect the biomass growth process and the biologically active substance synthesis in microalgae. The advantages and disadvantages of existing cultivation methods are outlined. An analysis of various methods for the isolation and overproduction of the main biologically active substances of microalgae (proteins, lipids, polysaccharides, pigments and vitamins) is presented and new technologies and approaches aimed at using microalgae as promising ingredients in value-added products are considered.

Biomass accumulation-influencing factors in microalgae farms

ABSTRACT Due to the emergence of large microalgae farms and increased competition in this sector, the search for higher productivity is common. One way to achieve this goal in microalgae production is to optimize the factors that influence their growth during the cultivation stage to increase the accumulation of bio-compounds of interest. In this stage, the factors that most influence are: nutrition, gas diffusion, light intensity and quality and, finally, stirring, which directly affects all other factors. Thus, a review and an evaluation of the influence and importance of stirring were performed in the present study. The nutrients that most influence biomass accumulation are carbon, nitrogen and phosphorus, but their proportion is directly related to the proposed objective for microalgae. In the diffusion of gases, it is essential to supply adequate CO2 for the growth of microalgae, and flue gases can be used. Also, it is necessary to ensure proper removal of photosynthetic O2, which could inhibit microalgae metabolism and slow their growth rate. It is important to provide the appropriate light intensity for photosynthesis, but excess may cause photoinhibition in cultivation. Stirring is of paramount importance to ensure nutrient distribution in the medium, gas diffusion (incorporation of CO2 and removal of O2) and adequate exposure of microalgae to light, reducing the effects of photoinhibition and self-shading.

Three-dimensional numerical simulation of light penetration in an optimized flow field composed of microalgae cells, carbon dioxide bubbles and culture medium

In order to evaluate light penetration and its influence on microalgae growth in a raceway pond with alternatively permutated conic baffles (RWP-APCB), 3D numerical simulation of light penetration was performed using computational fluid dynamics in an optimized flow field composed of microalgae cells, CO₂ bubbles and culture medium. Results showed that light intensity in the culture medium attenuated faster in accordance with solution depth, with increased microalgae cell concentration, increased bubble volume fraction and decreased CO₂ bubble diameter. Light zone fraction (i.e. ratio of light zone length to solution depth) increased with promoted incident irradiation. It was found that around 75% of microalgae cells were distributed in light zone and non-photochemical quenching coefficient of microalgae decreased by 32% in RWP-APCB. This resulted in a 16% increase of the Chlorella pyrenoidosa biomass growth rate, to 0.36 g/L/d.

Microalgal kinetics - a guideline for photobioreactor design and process development

Kinetics generally describes bio‐(chemical) reaction rates in dependence on substrate concentrations. Kinetics for microalgae is often adapted from heterotrophs and lacks mechanistic foundation, e.g. for light harvesting. Using and understanding kinetic equations as the representation of intracellular mechanisms is essential for reasonable comparisons and simulations of growth behavior. Summarizing growth kinetics in one equation does not yield reliable models. Piecewise linear or rational functions may mimic photosynthesis irradiance response curves, but fail to represent the mechanisms. Our modeling approach for photoautotrophic growth comprises physical and kinetic modules with mechanistic foundation extracted from the literature. Splitting the light submodel into the modules for light distribution, light absorption, and photosynthetic sugar production with independent parameters allows the transfer of kinetics between different reactor designs. The consecutive anabolism depends among others on nutrient concentrations. The nutrient uptake kinetics largely impacts carbon partitioning in the reviewed stoichiometry range of cellular constituents. Consecutive metabolic steps mask each other and demand a maximum value understandable as the minimum principle of growth. These fundamental modules need to be clearly distinguished, but may be modified or extended based on process conditions and progress in research. First, discussion of kinetics helps to understand the physiological situation, for which ranges of parameter values are given. Second, kinetics should be used for photobioreactor design, but also for gassing and nutrient optimization. Numerous examples are given for both aspects. Finally, measuring kinetics more comprehensively and precisely will help in improved process development.

Microalgae and cyanobacteria modeling in water resource recovery facilities: A critical review

Microalgal and cyanobacterial resource recovery systems could significantly advance nutrient recovery from wastewater by achieving effluent nitrogen (N) and phosphorus (P) levels below the current limit of technology. The successful implementation of phytoplankton, however, requires the formulation of process models that balance fidelity and simplicity to accurately simulate dynamic performance in response to environmental conditions. This work synthesizes the range of model structures that have been leveraged for algae and cyanobacteria modeling and core model features that are required to enable reliable process modeling in the context of water resource recovery facilities. Results from an extensive literature review of over 300 published phytoplankton models are presented, with particular attention to similarities with and differences from existing strategies to model chemotrophic wastewater treatment processes (e.g., via the Activated Sludge Models, ASMs). Building on published process models, the core requirements of a model structure for algal and cyanobacterial processes are presented, including detailed recommendations for the prediction of growth (under phototrophic, heterotrophic, and mixotrophic conditions), nutrient uptake, carbon uptake and storage, and respiration.

How do microalgae perceive light in a high-rate pond? Towards more realistic Lagrangian experiments

Hydrodynamics in a high-rate production reactor for microalgae cultivation affects the light history perceived by cells. The interplay between cell movement and medium turbidity leads to a complex light pattern, whose forcing effects on photosynthesis and photoacclimation dynamics are non-trivial. Hydrodynamics of high density algal ponds mixed by a paddle wheel has been studied recently, although the focus has never been on describing its impact on photosynthetic growth efficiency. In this multidisciplinary downscaling study, we first reconstructed single cell trajectories in an open raceway using an original hydrodynamical model offering a powerful discretization of the Navier-Stokes equations tailored to systems with free surfaces. The trajectory of a particular cell was selected and the associated high-frequency light pattern was computed. This light pattern was then experimentally reproduced in an Arduino-driven computer controlled cultivation system with a low density Dunaliella salina culture. The effect on growth and pigment content was recorded for various frequencies of the light pattern, by setting different paddle wheel velocities. Results show that the frequency of this realistic signal plays a decisive role in the dynamics of photosynthesis, thus revealing an unexpected photosynthetic response compared to that recorded under the on/off signals usually used in the literature. Indeed, the light received by a single cell contains signals from low to high frequencies that nonlinearly interact with the photosynthesis process and differentially stimulate the various time scales associated with photoacclimation and energy dissipation. This study highlights the need for experiments with more realistic light stimuli to better understand microalgal growth at high cell densities. An experimental protocol is also proposed, with simple, yet more realistic, step functions for light fluctuations.

High-Fidelity Modelling Methodology of Light-Limited Photosynthetic Production in Microalgae

Reliable quantitative description of light-limited growth in microalgae is key to improving the design and operation of industrial production systems. This article shows how the capability to predict photosynthetic processes can benefit from a synergy between mathematical modelling and lab-scale experiments using systematic design of experiment techniques. A model of chlorophyll fluorescence developed by the authors [Nikolaou et al., J Biotechnol 194:91-99, 2015] is used as starting point, whereby the representation of non-photochemical-quenching (NPQ) process is refined for biological consistency. This model spans multiple time scales ranging from milliseconds to hours, thus calling for a combination of various experimental techniques in order to arrive at a sufficiently rich data set and determine statistically meaningful estimates for the model parameters. The methodology is demonstrated for the microalga Nannochloropsis gaditana by combining pulse amplitude modulation (PAM) fluorescence, photosynthesis rate and antenna size measurements. The results show that the calibrated model is capable of accurate quantitative predictions under a wide range of transient light conditions. Moreover, this work provides an experimental validation of the link between fluorescence and photosynthesis-irradiance (PI) curves which had been theoricized.