A mechanistic model of photosynthesis in microalgae

Real-Time Sensor Data Profile-Based Deep Learning Method Applied to Open Raceway Pond Microalgal Productivity Prediction

Microalgal biotechnology holds the potential for renewable biofuels, bioproducts, and carbon capture applications due to unparalleled photosynthetic efficiency and diversity. Outdoor open raceway pond (ORP) cultivation enables utilization of sunlight and atmospheric carbon dioxide to drive microalgal biomass synthesis for production of bioproducts including biofuels; however, environmental conditions are highly dynamic and fluctuate both diurnally and seasonally, making ORP productivity prediction challenging without time-intensive physical measurements and location-specific calibrations. Here, for the first time, we present an image-based deep learning method for the prediction of ORP productivity. Our method is based on parameter profile plot images of sensor parameters, including pH, dissolved oxygen, temperature, photosynthetically active radiation, and total dissolved solids. These parameters can be remotely monitored without physical interaction with ORPs. We apply the model to data we generated during the Unified Field Studies of the Algae Testbed Public-Private-Partnership (ATP3 UFS), the largest publicly available ORP data set to date, which includes millions of sensor records and 598 productivities from 32 ORPs operated in 5 states in the United States. We demonstrate that this approach significantly outperforms an average value based traditional machine learning method (R2 = 0.77 ≫ R2 = 0.39) without considering bioprocess parameters (e.g., biomass density, hydraulic retention time, and nutrient concentrations). We then evaluate the sensitivity of image and monitoring data resolutions and input parameter variations. Our results demonstrate ORP productivity can be effectively predicted from remote monitoring data, providing an inexpensive tool for microalgal production and operational forecasting.

Exploring the Physiological Multiplicity of Native Microalgae from the Ecuadorian Highland, Italian Lowland and Indoor Locations in Response to UV-B

The differential effects of UV-B on the inhibition or activation of protective mechanisms to maintain cells photosynthetically active were investigated in native microalgae. Four strains were used, including two Chlorella sorokiniana strains, F4 and LG1, isolated from a Mediterranean inland swamp and a recycled cigarette butt's substrate, respectively, and two isolates from an Ecuadorian highland lake related to Pectinodesmus pectinatus (PEC) and Ettlia pseudoalveolaris (ETI). Monocultures were exposed to acute UV-B (1.7 W m^-2) over 18 h under controlled conditions. UV-B-untreated microalgae were used as the control. Comparative physiological responses, including photosynthetic pigments, non-enzymatic antioxidants, and chlorophyll a fluorescence, were evaluated at specific time points. Results showed that UV-B significantly compromised all the physiological parameters in F4, thereby resulting in the most UV-B-sensitive strain. Contrarily, UV-B exposure did not lead to changes in the PEC physiological traits, resulting in the best UV-B-resistant strain. This could be attributed to the acclimation to high light habitat, where maintaining a constitutive phenotype (at the photosynthetic level) is strategically advantageous. Differently, LG1 and ETI at 12 h of UV-B exposure showed different UV-B responses, which is probably related to acclimation, where in LG1, the pigments were recovered, and the antioxidants were still functioning, while in ETI, the accumulation of pigments and antioxidants was increased to avoid further photodamage. Consequently, the prolonged exposure in LG1 and ETI resulted in species-specific metabolic regulation (e.g., non-enzymatic antioxidants) in order to constrain full photoinhibition under acute UV-B.

CultureLED: A 3D printer-based LED illumination cultivation system for multi-well culture plates

Microalgae are a source of high value products such as pigments, lipids and carbohydrates. Microalgae cultivation techniques have evolved and improved, but a vast amount of research is still needed to achieve a better understanding of these microorganisms. Due to this, there is a growing need for affordable, flexible, and easy to control research systems and protocols. 3D printing revolutionized design and manufacturing as it became widely available to the mass market, allowing the creation of novel forms, enabling mass customization, and supporting low-volume, distributed production. The emergence of open-source designs combined with 3D printing applications have the potential to replace and outperform standard designs and methods. This protocol describes CultureLED, a well plated cell culture system that can be mounted on an orbital shaker or positioned on a shelf. It is an open hardware design, based on low-cost commercial off-the-shelf components. It was designed for optimized production cost, simplicity, low power consumption, design flexibility, and controllable light conditions. The CultureLED utilizes light-emitting diodes and it can be used for cultivation of small sized organisms or microorganisms with different light requirements and as such, has a wide range of applications.

Mathematical Modeling to Estimate Photosynthesis: A State of the Art

Photosynthesis is a process that indicates the productivity of crops. The estimation of this variable can be achieved through methods based on mathematical models. Mathematical models are usually classified as empirical, mechanistic, and hybrid. To mathematically model photosynthesis, it is essential to know: the input/output variables and their units; the modeling to be used based on its classification (empirical, mechanistic, or hybrid); existing measurement methods and their invasiveness; the validation shapes and the plant species required for experimentation. Until now, a collection of such information in a single reference has not been found in the literature, so the objective of this manuscript is to analyze the most relevant mathematical models for the photosynthesis estimation and discuss their formulation, complexity, validation, number of samples, units of the input/output variables, and invasiveness in the estimation method. According to the state of the art reviewed here, 67% of the photosynthesis measurement models are mechanistic, 13% are empirical and 20% hybrid. These models estimate gross photosynthesis, net photosynthesis, photosynthesis rate, biomass, or carbon assimilation. Therefore, this review provides an update on the state of research and mathematical modeling of photosynthesis.

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.

Lutein production by microalgae using corn starch wastewater pretreated with rapid enzymatic hydrolysis

The main purpose of this study was to explore the pretreatment process of corn starch wastewater (CSW) and engineered microalgae cultivation strategy to improve the nutrient recovery from wastewater and the yield of microalgae lutein. One-stage enzymatic hydrolysis utilizing α-amylase and glucoamylase simultaneously was established to efficiently harvest a maximum concentration of reducing sugar content of 7.26 g/L from CSW in 50 min. Lutein yield of 10.96 mg/L was obtained under 24 h continuous illumination with 2200 Lux light intensity. Furthermore, a cyclic feeding cultivation strategy was developed to improve lutein accumulation and COD removal up to 25.9 mg/L and 50.7%, respectively, after three cultivation cycles. Lutein yield of 14.86 mg/L and COD removal efficiency of 73.2% was achieved with further implementation in actual wastewater. This work provided a new perspective in developing the potential of cultivating microalgae with corn starch wastewater to produce high-value lutein.

Palm Oil Mill Effluent for Lipid Production by the Diatom Thalassiosira pseudonana

Biomass and lipid production by the marine centric diatom Thalassiosira pseudonana were characterized in media based on palm oil mill effluent (POME) as a source of key nutrients. The optimal medium comprised 20% by volume POME, 80 µM Na2SiO3, and 35 g NaCl L−1 in water at pH ~7.7. In 15-day batch cultures (16:8 h/h light–dark cycle; 200 µmol photons m−2 s−1, 26 ± 1 °C) bubbled continuously with air mixed with CO2 (2.5% by vol), the peak concentration of dry biomass was 869 ± 14 mg L−1 corresponding to a productivity of ~58 mg L−1 day−1. The neutral lipid content of the biomass was 46.2 ± 1.1% by dry weight. The main components of the esterified lipids were palmitoleic acid methyl ester (31.6% w/w) and myristic acid methyl ester (16.8% w/w). The final biomass concentration and the lipid content were affected by the light–dark cycle. Continuous (24 h light) illumination at the above-specified irradiance reduced biomass productivity to ~54 mg L−1 day−1 and lipid content to 38.1%.

Productivity analysis in tubular photobioreactors using a dynamic photosynthesis model coupled to computational fluid dynamics particle tracking

Tubular photobioreactors (TPBRs) are closed devices used for the mass culture of microalgae. TPBRs are supposed to be well-mixed, but the influence of their specific fluid dynamics in photosynthesis efficiency has never been studied in detail. Here, we use Computational Fluid Dynamics (CFD) coupled to a dynamic photosynthesis model to analyze the efficiency of the photosynthetic response in the loop of TPBRs of different sizes (14, 24, 44, 64, and 84 mm) and circulation velocities (0.4 to 1 m s^-1). The results show that only the smallest diameters cause enough radial mixing for a photosynthesis-enhancing light regime (integration factor Γ = 0.199 for D = 14 mm and v = 1 m s^-1) while high circulation velocities in larger diameters (up to 1 m s^-1) increase operating costs but do not enhance photosynthetic productivity. It is also shown the relevance of the characteristic frequency of the strain (β), which is crucial for high productivity.

Removal of nitrate and phosphate from simulated agricultural runoff water by Chlorella vulgaris

Microalgae such Chlorella vulgaris can effectively absorb nitrate and phosphate from contaminated water. This work characterized nitrate and phosphate removal from simulated agricultural runoff using C. vulgaris. Statistically designed experiments were used to model the following responses: (1) algal growth; (2) nitrate removal; (3) phosphate removal; (4) protein in the algal biomass; (5) chlorophyll content of the biomass; (6) the biomass phenolics content; and (7) the free radical scavenging antioxidant activity of the biomass. These response were modelled for the following key experimental factors: initial nitrate concentration in the simulated runoff (1080-3240 mg L^-1, as NaNO₃), initial phosphate concentration (20-60 mg L^-1, as K₂HPO₄), photoperiod (8-24 h of light/day) and culture duration (5-15 days). The validated models were used to identify the factor levels to maximize the various responses. Nitrate removal was maximized at 85.6% when initial nitrate and phosphate concentrations were 2322 mg L^-1 and 38 mg L^-1 (N:P atom ratio ≈ 125:1), respectively, with a 17.2 h daily photoperiod in a 13-day culture. Phosphate removal was maximized at 95% when the initial nitrate and phosphate concentrations were 1402 mg L^-1 and 56.7 mg L^-1 (N:P ≈ 51:1), respectively, with a 15.7 h daily photoperiod in a 14.7-day culture. At least ~14 h of a daily photoperiod and a ~11-day culture period were required to maximize all the studied responses. C. vulgaris is edible and may be used as animal feed. Nutritional aspects of the biomass were characterized. Biomass with more than 24% protein could be produced. Under the best conditions, the chlorophyll (potential food colorants) content of the biomass was 8.5% and the maximum level of total phenolics (antioxidants) in the biomass was nearly 13 mg gallic acid equivalent g^-1.

Analysis of productivity in raceway photobioreactor using computational fluid dynamics particle tracking coupled to a dynamic photosynthesis model

Raceway photobioreactors (RWPs) are the most common and affordable device for the mass culture of microalgae but due to geometry and the requirement of low input power, its photosynthetic performance is low. The fluid dynamics of RWPs have been studied for information such as energy dissipation and shear rate, CFD has never been used to analyze photosynthesis efficiency by coupling dynamic photosynthesis models with microalgae trajectories. In this work, we investigate by CFD simulation the effect of circulation velocities between 0.2 and 0.8 m s-1in a 0.15 m-1 deep RWPs under standard outdoor conditions to shows that in all circumstances the RWP from the point o view of photosynthesis operates as a perfectly segregated device (no mixing) and that the average growth rate is the result of the integration of the local growth rates at different depths (integration factor Γ = 0).

Model-Based Prediction of Perceived Light Flashing in Recirculated Inclined Wavy-Bottomed Photobioreactors

Microalgae biomass production rate in short light-path photobioreactors potentially can be improved by mixing-induced flashing light regimes. A cascade photobioreactor features a thin liquid layer flowing down a sloping, wavy-bottomed surface where liquid flow exhibits peculiar local recirculation hydrodynamics, potentially conducive to an ordered flashing light regime. This article presents a model-based analysis of the frequency distribution of perceived irradiance in said wavy-bottomed photobioreactor. The model combines a Lagrangian description of the motion of individual cells, in turn derived from the hydrodynamic parameters of the photobioreactor extracted from an experimentally validated Computational Fluid Dynamic model, with a simplified description of the irradiance field across the culture thickness, down to the spectral analysis of perceived irradiance. The main finding of the work is that the wavy bottomed photobioreactor provides a ‘robust’ spectral excitation to the circulating microalgae up to 3 Hz frequency, while in flat panels and bubble columns excitation decays evenly at a 24 db/octave rate. This analysis paves the way to improving the light flashing performance of the wavy-bottomed photobioreactor with respect to geometry (cavity size and installation inclination) and operation (flow rate).

A new approach for calculating microalgae culture growth based on an inhibitory effect of the surrounding biomass

Ever since the potential of algae in biotechnology was recognized, models describing the growth of algae inside photobioreactors have been proposed. These models are the basis for the optimization of process conditions and reactor designs. Over the last few decades, models became more and more elaborate with the increase of computational capacity. Thus far, these models have been based on light attenuation due to the absorption and scattering effects of the biomass. This manuscript presents a new way of predicting the apparent growth inside photobioreactors using simple models for enzymatic kinetics to describe the reaction between photons and the photosynthetic unit. The proposed model utilizes an inhibition kinetic formula based on the surrounding biomass to describe the average growth rate of a culture, which is determined by the local light intensities inside the reactor. The result is a mixed-inhibition scheme with multiple inhibition sites. The parameters of the new kinetic equation are replaced by empirical regression functions to correlate their dependency on incident light intensity and reactor size. The calibrations of the parameters and the regression functions are based on the numerical solutions of the growth rate computed with a classical Type II model. As a final verification, we apply the new equation in predicting the growth behavior of three phototrophic organisms in reactors of three different sizes.

Indirect regulation of temperature in raceway reactors by optimal management of culture depth

Temperature and irradiance are the two most relevant factors determining the performance of microalgae cultures in open raceway reactors. Moreover, inadequate temperature strongly reduces the biomass productivity in these systems even if enough sunlight is available. Controlling the temperature in large open raceway reactors is considered unaffordable because of the large amount of energy required. This study presents an indirect method for temperature regulation in microalgae raceway reactors by optimizing the culture depth. First, the effect of the culture depth on the raceway temperature is analyzed for different seasons of the year. Afterward, a simulation study is presented where the proposed control approach is compared to the normal operation mode with constant volume in the reactor. This study is also extended to industrial scale. Relevant improvements on the temperature factor and biomass production are presented. The developed knowledge allows the improvement of the performance in open raceway reactors up to 12% without involving additional energy and costs, being a suitable solution for large industrial reactors that until now have no options for controlling the temperature.

A new model to analyze the temperature effect on the microalgae performance at large scale raceway reactors

In this study a simplified temperature model for raceway reactors is developed, allowing to determine the temperature of the microalgae culture as a function of reactor design and environmental conditions. The model considers the major phenomena taking place in raceway reactors, especially heat absorption by radiation and heat losses by evaporation among others. The characteristic parameters of the model have been calibrated using genetic algorithms, next being validated with a long set of more than 50 days covering different weather conditions. It is worth to highlight the use of the developed model as a tool to analyze the influence of the temperature on the performance of microalgae cultures at large scale. As example, the annual variation of the performance of up to five different microalgae strains has been determined by computing the temperature index, thus the normalized value of performance of whatever microalgae at the real temperature with respect to that achievable at optimal temperature can be established. Results confirm that only strains tolerant to wide ranges of temperature can be efficiently produced all the year around in large scale outdoor raceway reactors without additional temperature control systems.

Enhanced biomass productivity of microalgae Nannochloropsis sp. in an airlift photobioreactor using low-frequency flashing light with blue LED

Microalgae Nannochloropsis sp. is a widely recognized renewable biodiesel feedstock. The ability of this microalgae to absorb CO2 constitutes an added value toward reducing global warming. However, the process of optimizing its growth still involves many challenges. Photoinhibition, which takes places during microalgae cultivation when using continuous lighting, constitutes an unresolved problem. Therefore, the optimum light/dark cycle method is considered necessary. The experiments were conducted using a designed, tubular airlift photobioreactor and blue, energy-saving, light-emitting diode (LED) lights for the purpose of internal illumination. We observed that a 45:15 min (light:dark) cycle increased the production of Nannochloropsis sp. biomass significantly, with a cell density, wet weight, and lipid content of 17 × 106 cell/ml, 7.11 g, and 10.1% dry weight, respectively. By using the blue LED lights, our designed, airlift photobioreactor increased cell growth by 70% compared to the growth of Nannochloropsis sp. in nature and produced 61 times higher lipid content compared to Nannochloropsis sp. that is exposed to natural light.

Effect of Light Intensity and Quality on Growth Rate and Composition of Chlorella vulgaris

In this research, the effect of solar irradiance on Chlorella vulgaris cultivated in open bioreactors under greenhouse conditions was investigated, as well as of ratio of light intensity in the 420–520 nm range to light in the 580–680 nm range (I_420–520/I_580–680) and of artificial irradiation provided by red and white LED lamps in a closed flat plate laboratory bioreactor on the growth rate and composition. The increase in solar irradiance led to faster growth rates (μ_exp) of C. vulgaris under both environmental conditions studied in the greenhouse (in June up to 0.33 d⁻¹ and in September up to 0.29 d⁻¹) and higher lipid content in microalgal biomass (in June up to 25.6% and in September up to 24.7%). In the experiments conducted in the closed bioreactor, as the ratio I_420–520/I_580–680 increased, the specific growth rate and the biomass, protein and lipid productivities increased as well. Additionally, the increase in light intensity with red and white LED lamps resulted in faster growth rates (the μ_exp increased up to 0.36 d⁻¹) and higher lipid content (up to 22.2%), while the protein, fiber, ash and moisture content remained relatively constant. Overall, the trend in biomass, lipid, and protein productivities as a function of light intensity was similar in the two systems (greenhouse and bioreactor).

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.

The potential of quantitative models to improve microalgae photosynthetic efficiency

The massive increase in carbon dioxide concentration in the atmosphere driven by human activities is causing huge negative consequences and new sustainable sources of energy, food and materials are highly needed. Algae are unicellular photosynthetic microorganisms that can provide a highly strategic contribution to this challenge as alternative source of biomass to complement crops cultivation. Algae industrial cultures are commonly limited by light availability, and biomass accumulation is strongly dependent on their photon-to-biomass conversion efficiency. Investigation of algae photosynthetic metabolism is thus strategic for the generation of more efficient strains with higher productivity. Algae are cultivated at industrial scale in conditions highly different from the natural niches they adapted to and strains development efforts must fully consider the seminal influence on productivity of regulatory mechanism of photosynthesis as well as of cultivation parameters like cells concentration, light distribution in the culture, mixing, nutrients and carbon dioxide availability. In this review we will focus in particular on how mathematical models can account for the complex influence of all environmental parameters and can be exploited for development of improved algae strains.

A critical review on designs and applications of microalgae-based photobioreactors for pollutants treatment

The development of the photobioreactors (PBs) is recently noticeable as cutting-edge technology while the correlation of PBs' engineered elements such as modellings, configurations, biomass yields, operating conditions and pollutants removal efficiency still remains complex and unclear. A systematic understanding of PBs is therefore essential. This critical review study is to: (1) describe the modelling approaches and differentiate the outcomes; (2) review and update the novel technical issues of PBs' types; (3) study microalgae growth and control determined by PBs types with comparison made; (4) progress and compare the efficiencies of contaminants removal given by PBs' types and (5) identify the future perspectives of PBs. It is found that Monod model's shortcoming in internal substrate utilization is well fixed by modified Droop model. The corroborated data also remarks an array of PBs' types consisting of flat plate, column, tubular, soft-frame and hybrid configuration in which soft-frame and hybrid are the latest versions with higher flexibility, performance and smaller foot-print. Flat plate PBs is observed with biomass yield being 5 to 20 times higher than other PBs types while soft-frame and membrane PBs can also remove pharmaceutical and personal care products (PPCPs) up to 100%. Looking at an opportunity for PBs in sustainable development, the flat plate PBs are applicable in PB-based architectures and infrastructures indicating an encouraging revenue-raising potential.

New horizons in culture and valorization of red microalgae

Research on marine microalgae has been abundantly published and patented these last years leading to the production and/or the characterization of some biomolecules such as pigments, proteins, enzymes, biofuels, polyunsaturated fatty acids, enzymes and hydrocolloids. This literature focusing on metabolic pathways, structural characterization of biomolecules, taxonomy, optimization of culture conditions, biorefinery and downstream process is often optimistic considering the valorization of these biocompounds. However, the accumulation of knowledge associated with the development of processes and technologies for biomass production and its treatment has sometimes led to success in the commercial arena. In the history of the microalgae market, red marine microalgae are well positioned particularly for applications in the field of high value pigment and hydrocolloid productions. This review aims to establish the state of the art of the diversity of red marine microalgae, the advances in characterization of their metabolites and the developments of bioprocesses to produce this biomass.

Exergy efficiency of light conversion into biomass in the macroalga Ulva sp. (Chlorophyta) cultivated under the pulsed light in a photobioreactor

Marine macroalgae are a potential feedstock for biorefineries that can reduce dependence on fossil fuels and contribute to bioeconomy. New knowledge and technologies for efficient conversion of solar energy into macroalgae biomass are needed to increase biomass yields and energy conversion efficiency. In this work, we show that the green macroalgae from Ulva sp. can grow under the pulsed light in a photobioreactor with higher exergy conversion efficiency in comparison to cultivation under constant light with the same intensity. In the tested frequencies, 1-40 Hz and duty cycles (DC) 1-100%, DC has a stronger impact on the growth rate than frequency. The efficiency of light transformation into biomass increased with decreasing DC. Pulsating with DC 20% led to 60% of the biomass chemical energy yield for the respective constant light (DC 100%). Models of Ulva sp. growth rate and exergy conversion efficiency as a function of pulsating light parameters were developed. These results open new directions to enhance solar to chemical energy conversion through macroalgae by controlling the light distribution in the macroalgal biomass.

A penalty on photosynthetic growth in fluctuating light

Fluctuating light is the norm for photosynthetic organisms, with a wide range of frequencies (0.00001 to 10 Hz) owing to diurnal cycles, cloud cover, canopy shifting and mixing; with broad implications for climate change, agriculture and bioproduct production. Photosynthetic growth in fluctuating light is generally considered to improve with increasing fluctuation frequency. Here we demonstrate that the regulation of photosynthesis imposes a penalty on growth in fluctuating light for frequencies in the range of 0.01 to 0.1 Hz (organisms studied: Synechococcus elongatus and Chlamydomonas reinhardtii). We provide a comprehensive sweep of frequencies and duty cycles. In addition, we develop a 2^nd order model that identifies the source of the penalty to be the regulation of the Calvin cycle – present at all frequencies but compensated at high frequencies by slow kinetics of RuBisCO.

Reaction engineering analysis of Scenedesmus ovalternus in a flat-plate gas-lift photobioreactor

Microalgal strains of the genus Scenedesmus are a promising resource for commercial biotechnological applications. The temperature-, pH- and light-dependent growth of Scenedesmus ovalternus has been investigated on a laboratory scale. Best batch process performance was obtained at 30°C, pH 8.0 and an incident photon flux density of 1300μmolphotonsm^-2s^-1 using a flat-plate gas-lift photobioreactor. Highest growth rate (0.11h^-1) and space-time yield (1.7±0.1g_CDWL^-1d^-1) were observed when applying these reaction conditions. Biomass concentrations of up to 7.5±0.1g_CDWL^-1 were achieved within six days (25.0±0.5g_CDWm^-2d^-1). The light-dependent growth kinetics of S. ovalternus was identified using Schuster's light transfer model and Andrews' light inhibition model (K_S=545μmolphotonsm^-2s^-1; K_I=2744μmolphotonsm^-2s^-1; μ_max=0.21h^-1). The optimal mean integral photon flux density for growth of S. ovalternus was estimated to be 1223μmolphotonsm^-2s^-1.

Comprehensive computational model for combining fluid hydrodynamics, light transport and biomass growth in a Taylor vortex algal photobioreactor: Lagrangian approach

A comprehensive quantitative model incorporating the effects of fluid flow patterns, light distribution, and algal growth kinetics on biomass growth rate is developed in order to predict the performance of a Taylor vortex algal photobioreactor for culturing Chlorella vulgaris. A commonly used Lagrangian strategy for coupling the various factors influencing algal growth was employed whereby results from computational fluid dynamics and radiation transport simulations were used to compute numerous microorganism light exposure histories, and this information in turn was used to estimate the global biomass specific growth rate. The simulations provide good quantitative agreement with experimental data and correctly predict the trend in reactor performance as a key reactor operating parameter is varied (inner cylinder rotation speed). However, biomass growth curves are consistently over-predicted and potential causes for these over-predictions and drawbacks of the Lagrangian approach are addressed.

Toward Multiscale Models of Cyanobacterial Growth: A Modular Approach

Oxygenic photosynthesis dominates global primary productivity ever since its evolution more than three billion years ago. While many aspects of phototrophic growth are well understood, it remains a considerable challenge to elucidate the manifold dependencies and interconnections between the diverse cellular processes that together facilitate the synthesis of new cells. Phototrophic growth involves the coordinated action of several layers of cellular functioning, ranging from the photosynthetic light reactions and the electron transport chain, to carbon-concentrating mechanisms and the assimilation of inorganic carbon. It requires the synthesis of new building blocks by cellular metabolism, protection against excessive light, as well as diurnal regulation by a circadian clock and the orchestration of gene expression and cell division. Computational modeling allows us to quantitatively describe these cellular functions and processes relevant for phototrophic growth. As yet, however, computational models are mostly confined to the inner workings of individual cellular processes, rather than describing the manifold interactions between them in the context of a living cell. Using cyanobacteria as model organisms, this contribution seeks to summarize existing computational models that are relevant to describe phototrophic growth and seeks to outline their interactions and dependencies. Our ultimate aim is to understand cellular functioning and growth as the outcome of a coordinated operation of diverse yet interconnected cellular processes.

Low light intensity and nitrogen starvation modulate the chlorophyll content of Scenedesmus dimorphus

AIMS

Chlorophyll is a photosynthetic pigment found in plants and algal organisms and is a bioproduct with human health benefits and a great potential for use in the food industry. The chlorophyll content in microalgae strains varies in response to environmental factors. In this work, we assessed the effect of nitrogen depletion and low light intensity on the chlorophyll content of the Scenedesmus dimorphus microalga.

METHODS AND RESULTS

The growth of S. dimorphus under low light intensity led to a reduction in cell growth and volume as well as increased cellular chlorophyll content. Nitrogen starvation led to a reduction in cell growth and the chlorophyll content, changes in the yield and productivity of chlorophylls a and b. Transmission electron microscopy was used to investigate the ultrastructural changes in the S. dimorphus exposed to nitrogen and light deficiency.

CONCLUSIONS

In contrast to nitrogen depletion, low light availability was an effective mean for increasing the total chlorophyll content of green microalga S. dimorphus.

SIGNIFICANCE AND IMPACT OF THE STUDY

The findings acquired in this work are of great biotechnological importance to extend knowledge of choosing the right culture condition to stimulate the effectiveness of microalgae strains for chlorophyll production purposes.

Mitigation of carbon dioxide by oleaginous microalgae for lipids and pigments production: Effect of light illumination and carbon dioxide feeding strategies

Oleaginous microalgae Nannochloropsis sp. was selected as potential strain for CO2 mitigation into lipids and pigments. The synergistic effects of light intensity and photoperiod were evaluated to provide the adequate light energy for this strain. The saturation light intensity was 60μmol·photon·m(-2)s(-1). With full illumination, the biomass obtained was 0.850±0.16g·L(-1) with a lipid content of 44.7±1.2%. The pigments content increased with increasing light energy supply. Three main operating factors including initial cell concentration, CO2 content and gas flow rate were optimized through Response Surface Methodology. The feedings with low CO2 content at high gas flow rate gave the maximum biomass but with low lipid content. After optimization, the biomass and lipid production were increased up to 1.30±0.103g·L(-1) and 0.515±0.010g·L(-1), respectively. The CO2 fixation rate was as high as 0.729±0.04g·L(-1)d(-1). The fatty acids of Nannochloropsis sp. lipids were mainly C16-C18 indicating its potential use as biodiesel feedstocks.

Scenedesmus dimorphus biofilm: Photoefficiency and biomass production under intermittent lighting

This study investigated the effect of intermittent lighting on the growth performances of a Scenedesmus dimorphus biofilm. Flashing light effect (FLE) is common in traditional suspended cultures of microalgae; yet, publications about this phenomenon, in the context of biofilm cultivation, are scarce. In this work we demonstrate that, thanks to intermittent illumination, it is possible for attached cultivations to fulfill FLE, improve photoefficiency and productivity as well as providing protection from photoinhibition using much lower flashing light frequencies than those usually required with suspended cultures. Medium frequency intermittent lighting (0.1 Hz) guaranteed excellent light integration resulting in 9.13 g m⁻² d⁻¹ biomass productivity, which was 8.9% higher than with continuous lighting. Results showed that a light fraction value of 0.5 always improved photoefficiency values as related to continuous light with a 118.8% maximum increase.

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.

Carbonate Precipitation through Microbial Activities in Natural Environment, and Their Potential in Biotechnology: A Review

Calcium carbonate represents a large portion of carbon reservoir and is used commercially for a variety of applications. Microbial carbonate precipitation, a by-product of microbial activities, plays an important metal coprecipitation and cementation role in natural systems. This natural process occurring in various geological settings can be mimicked and used for a number of biotechnologies, such as metal remediation, carbon sequestration, enhanced oil recovery, and construction restoration. In this study, different metabolic activities leading to calcium carbonate precipitation, their native environment, and potential applications and challenges are reviewed.

Modelling of oxygen-evolving-complex ionization dynamics for energy-efficient production of microalgal biomass, pigment and lipid with carbon capture: an engineering vision for a biorefinery

Development of an algal growth kinetics model, incorporating oxygen-evolving-complex ionization dynamics, for sustainable production of algal biomass, lipid, and chlorophyll (with associated carbon dioxide capture) in an algal biorefinery.