Use of image analysis tool for the development of light distribution pattern inside the photobioreactor for the algal cultivation

Application of regression and artificial neural network analysis of Red-Green-Blue image components in prediction of chlorophyll content in microalgae

This study presented a novel methodology to predict microalgae chlorophyll content from colour models using linear regression and artificial neural network. The analysis was performed using SPSS software. Type of extractant solvents and image indexes were used as the input data for the artificial neural network calculation. The findings revealed that the regression model was highly significant, with high R² of 0.58 and RSME of 3.16, making it a useful tool for predicting the chlorophyll concentration. Simultaneously, artificial neural network model with R² of 0.66 and low RMSE of 2.36 proved to be more accurate than regression model. The model which fitted to the experimental data indicated that acetone was a suitable extraction solvent. In comparison to the cyan-magenta-yellow-black model in image analysis, the red-greenblue model offered a better correlation. In short, the estimation of chlorophyll concentration using prediction models are rapid, more efficient, and less expensive.

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.

Machine learning-informed and synthetic biology-enabled semi-continuous algal cultivation to unleash renewable fuel productivity

Algal biofuel is regarded as one of the ultimate solutions for renewable energy, but its commercialization is hindered by growth limitations caused by mutual shading and high harvest costs. We overcome these challenges by advancing machine learning to inform the design of a semi-continuous algal cultivation (SAC) to sustain optimal cell growth and minimize mutual shading. An aggregation-based sedimentation (ABS) strategy is then designed to achieve low-cost biomass harvesting and economical SAC. The ABS is achieved by engineering a fast-growing strain, Synechococcus elongatus UTEX 2973, to produce limonene, which increases cyanobacterial cell surface hydrophobicity and enables efficient cell aggregation and sedimentation. SAC unleashes cyanobacterial growth potential with 0.1 g/L/hour biomass productivity and 0.2 mg/L/hour limonene productivity over a sustained period in photobioreactors. Scaling-up the SAC with an outdoor pond system achieves a biomass yield of 43.3 g/m²/day, bringing the minimum biomass selling price down to approximately $281 per ton.

Growth limitation caused by mutual shading and the high harvest cost hamper algal biofuel production. Here, the authors overcome these two problems by designing a semi-continuous algal cultivation system and an aggregation-based sedimentation strategy to achieve high levels production of biomass and limonene.

Antioxidant and anti-proliferative properties of extracts from heterotrophic cultures of Galdieria sulphuraria

This study explores the possibility to use the extremophilic microalga Galdieria sulphuraria (strain 064) as a source of natural biomolecules with beneficial and protective effects on human health. Galdieria was cultivated in heterotrophy conditions and cells extracts for their antioxidant and anti-proliferative properties were tested. Galdieria extracts showed high antioxidant power tested through ABTS assay and revealed high glutathione and phycocyanin contents. Based on Annexin-V FITC/propidium iodide and MTT analysis, algae extracts inhibited the proliferation of human adenocarcinoma A549 cells (51.2% inhibition) through the induction of apoptosis without cell cycle arrest. Besides, cytotoxicity and cytometry assays showed a positive pro-apoptotic mechanism. On these bases, we suggest that G. sulphuraria from heterotrophic culture, for its therapeutic potential, could be considered a good candidate for further studies with the aim to isolate bioactive anti-cancer molecules.

Light intensity as major factor to maximize biomass and lipid productivity of Ettlia sp. in CO2-controlled photoautotrophic chemostat

The optimal culture conditions are critical factors for high microalgal biomass and lipid productivity. To optimize the photoautotrophic culture conditions, combination of the pH (regulated by CO₂ supply), dilution rate, and light intensity was systematically investigated for Ettlia sp. YC001 cultivation in a chemostat during 143days. The biomass productivity increased with the increase in dilution rate and light intensity, but decreased with increasing pH. The average lipid content was 19.8% and statistically non-variable among the tested conditions. The highest biomass and lipid productivities were 1.48gL^-1d^-1 and 291.4mgL^-1d^-1 with a pH of 6.5, dilution rate of 0.78d^-1, and light intensity of 1500μmolphotonsm^-2s^-1. With a sufficient supply of CO₂ and nutrients, the light intensity was the main determinant of the photosynthetic rate. Therefore, the surface-to-volume ratio of a photobioreactor should enable efficient light distribution to enhance microalgal growth.

Hydrogen production by Rhodobacter sphaeroides DSM 158 under intense irradiation

To identify optimal hydrogen production conditions using growing cultures of Rhodobacter sphaeroides DSM 158 the effects of varying the reactor's volumetric power input (0.01-1.4kWm(-3)) and irradiation intensity (5-2500Wm(-2)) were investigated in batch and continuous production modes. Irradiation intensity had a greater effect on hydrogen production than volumetric power input. Hydrogen production and photofermentative biomass formation were maximized by irradiation at 2250Wm(-2) with a volumetric power input of 0.55kWm(-3). The bacterial dry weight (2.64gL(-1)) and rate of hydrogen production (195mLL(-1)h(-1)) achieved under these conditions were greater than any that have previously been reported for batch-mode hydrogen production by R. sphaeroides. Continuous mode experiments (D=0.1h(-1)) yielded a bacterial dry weight, hydrogen production rate, productivity and hydrogen yield of 2.35±0.18gL(-1), 165±6.2mLL(-1)h(-1), 3.96LL(-1)d(-1) and 36.6%, respectively.

Cell growth kinetics of Chlorella sorokiniana and nutritional values of its biomass

The present study investigates the effects of different physico-chemical parameters for the growth of Chlorella sorokiniana and subsequently determination of nutritional values of its biomass. Most suitable temperature, light intensity, pH, and acetic acid concentration were 30°C, 100 μmol m(-2)s(-1), pH 7.5, and 34.8mM, respectively for the growth of this microorganism. Arrhenius growth activation energy, Ea was calculated as 7.08 kJ mol(-1). Monod kinetics constants: maximum specific growth rate (μ max) and substrate (acetic acid) affinity coefficient (Ks) were determined as 0.1 ± 0.01 h(-1) and 76 ± 8 mg L(-1), respectively. Stoichiometric analysis revealed the capture of 1.83 g CO2 and release of 1.9 g O2 for 1g algal biomass synthesis. Algal biomass of C. sorokiniana was found rich in protein and several important minerals such as Mg, Ca, and Fe. Astaxanthin and β-carotene were extracted and quantified using high performance liquid chromatography.

Physicochemical parameters optimization, and purification of phycobiliproteins from the isolated Nostoc sp

The present study investigated the effects of several physicochemical parameters on the improvement of phycobiliproteins (especially phycocyanin) synthesis in a newly isolated species of Nostoc sp. Standard BG11₀ medium was modified to enhance the biomass productivity in different photobioreactors. The initial pH of 8, light intensity of 40 μmol m(-2)s(-1), temperature of 35 °C, diurnal cycle of 16:8 h (light:dark regime), 75.48 μM Na₂CO₃ and 17.65 mM NaNO₃ were found most suitable for the phycobiliproteins synthesis. Cyanobacteria exhibited chromatic adaptation, causing overexpression of phycocyanin in red and phycoerythrin in green light. The maximum phycobiliproteins yield of 0.13 gg(-1) dry cell weight was obtained in green light. Phycocyanin was further purified using thin layer chromatography (TLC), anion exchange chromatography and SDS-PAGE (denaturing gel) electrophoresis.

A novel flat plate algal bioreactor with horizontal baffles: structural optimization and cultivation performance

A novel flat plate photobioreactor with horizontal baffles was developed. The effects of aeration intensity and aeration site were investigated using computational fluid dynamics. The effects of baffle structural parameters, including the ratio of clearance between the baffle and the bioreactor wall (d) to bioreactor width (D) and the ratio of distance between two adjacent baffles (h) to D on the flow and mixing performance were assessed. A good light/dark cycle and strong, uniform mixing performance were created at d/D=0.5 and h/D=1 when the aeration site was located at the bottom center. The cultivation performance was assessed by culturing Chlorella vulgaris 31. The maximum biomass productivity in the optimized bioreactor was 1.88 times than that of a traditional bioreactor without baffles. For a light path length of 80 mm, the optimized baffles offer a large economical advantage in improving algal productivity and reduce growth condition difference.

Hollow glass microspheres for temperature and irradiance control in photobioreactors

The addition of hollow glass microspheres (HGM) to polymers to change thermal insulation and mechanical properties is widely used. In this study HGM were tested as a new construction material for photobioreactors to control irradiance and broth temperature in microalgae cultivation. The heat isolation properties of HGMs of three different densities were tested in a polymer matrix. The transmittance (5-50%) and the thermal conductivity (182.05-190.73 W/mK) of the HGM composite material were analyzed. The results were tested in a model to predict the broth temperature and the growth rate as a function of temperature and irradiance. The addition of 1.3 and 0.6 vol.% of HGM lead to an increase in the growth rate of up to 37% and a reduction in the broth temperature up to 9°C. The mechanical resistance of the composites tested is similar to the polymer matrix.