A kinetic model of heterotrophic and mixotrophic cultivation of the potential biofuel organism microalgae Chlorella sorokiniana

Prospective technical and technological insights into microalgae production using aquaculture wastewater effluents

Microalgae biomass is a promising resource addressing climate change and play a role in energy transition for generating biofuels. Due to their ability to produce higher yield per year, biofuels obtained from microalgae are considered 3rd generation-advanced biofuels. The industrial production of microalgae mitigates the effects of CO2 emissions and can be used for wastewater bioremediation since most effluents are rich in nutrients. Using wastewater as growth media for microalgae promotes the principles of circular economy and nutrient recovery. The aquaculture wastewater effluent contains high levels of nitrogenous compounds, as well as phosphates and dissolved organic carbon. The current review aims to identify, centralize, and provide extensive information on the decisive technological and technical factors involved in the growth process of different microalgae species in aquaculture wastewater. The study focuses on technological growth performance indicators, as well as specific control strategies applied to achieve pH control, since it has been highlighted to be one of the most important growth-related cofactors. A bibliometric framework was developed to identify future trends in integrated microalgae production. The scientific literature analysis highlighted the great potential of aquaculture wastewater effluents to be used as growth media for microalgae biomass production, due to superior performance in lipid and carbohydrate productivity. Most control strategies developed for microalgae production systems found in the literature aim at controlling the pH in the bioreactor by injecting CO2, while few other papers consider manipulating the dissolved oxygen. The need for higher-level control arises to not only track pH or DO references but also to maximize the treatment efficiency of the bioreactor.

The growth and nutrient removal properties of heterotrophic microalgae Chlorella sorokiniana in simulated wastewater containing volatile fatty acids

To reduce the high cost of organic carbon sources in waste resource utilization in the cultivation of microalgae, volatile fatty acids (VFAs) derived from activated sludge were used as the sole carbon source to culture Chlorella sorokiniana under the heterotrophic cultivation. The addition of VFAs in the heterotrophic condition enhanced the total nitrogen (TN) and phosphorus (TP) removal of C. sorokiniana, which proved the advantageous microalgae in using VFAs in the heterotrophic culture after screening in the previous study. To discover the possible mechanism of nitrogen and phosphorus adsorption in heterotrophic conditions by microalgae, the effect of different ratios of VFAs (acetic acid (AA): propionic acid (PA): butyric acid (BA)) on the nutrient removal and growth properties of C. sorokiniana was studied. In the 8:1:1 group, the highest efficiency (77.19%) of VFAs assimilation, the highest biomass (0.80 g L-1) and lipid content (31.35%) were achieved, with the highest TN and TP removal efficiencies of 97.44 % and 91.02 %, respectively. Moreover, an aerobic denitrifying bacterium, Pseudomonas, was determined to be the dominant genus under this heterotrophic condition. This suggested that besides nitrate uptake and utilization by C. sorokiniana under the heterotrophy, the conduct of the denitrification process was also the main reason for obtaining high nitrogen removal efficiency.

Comparative assessment of microalgal growth kinetic models based on light intensity and biomass concentration

The comprehensive evaluation and validation of mathematical models for microalgal growth dynamics are essential for improving cultivation efficiency and optimising photobioreactor design. A considerable gap in comprehending the relation between microalgal growth, light intensity and biomass concentration arises since many studies focus solely on associating one of these factors. This paper compares microalgal growth kinetic models, specifically focusing on the combined impact of light intensity and biomass concentration. Considering a dataset (experimental results and literature values) concerning Chlorella vulgaris, nine kinetic models were assessed. Bannister and Grima models presented the best fitting performance to experimental data (RMSE ≤ 0.050 d-1; R2≥0.804; d2≥0.943). Cultivation conditions conducting photoinhibition were identified in some kinetic models. After testing these models on independent datasets, Bannister and Grima models presented superior predictive performance (RMSE = 0.022-0.023 d-1; R2 = 0.878-0.884; d2: 0.976-0.975). The models provide valuable tools for predicting microalgal growth and optimising operational parameters, reducing the need for time-consuming and costly experiments.

The growth and lipid accumulation of Scenedesmus quadricauda under nitrogen starvation stress during xylose mixotrophic/heterotrophic cultivation

In order to conquer the block of high cost and low yields which limit to realize the commercialization of microalgal biodiesel, the mixotrophic and heterotrophic cultivation of Scenedesmus quadricauda FACHB-1297 fed on xylose was separately studied employing six forms of media: phosphorus sufficient, phosphorus restricted, and phosphorus starvation were combined with nitrogen sufficient and nitrogen starvation conditions. The maximum lipid content (about 41% of dry weight) was obtained on the 5th day (heterotrophic cultivation) and 8th day (mixotrophic cultivation) under the nitrogen starved and phosphorus sufficient (N0&P) conditions, which was about twofold in comparison to the final lipid content on the sufficient nitrogen condition (control). Under mixotrophic and heterotrophic modes, the highest lipid production was achieved in the N0&P trial, with the value of 274.96 mg/L and 193.77 mg/L, respectively. Xylose utilization rate of 30-96% under heterotrophic modes was apparently higher than that of 20-50% in mixotrophic modes. In contrast, phosphorus uptake rate of 100% under mixotrophic cultivation was significantly more than that of 60-90% in heterotrophic cultivation. Furthermore, under the condition of heterotrophic cultivation using xylose as a carbon source, the phosphorus had a positive impact on microalgae cell synthesis and the lipid content enhanced with the augmentation in phosphorus concentrations. We suggested that sufficient phosphorus should be supplied for obtaining higher microalgal lipid production in the lack of nitrogen under xylose heterotrophic/mixotrophic condition. This was a highly effective way to obtain efficient microalgae lipid production.

A reliable multi-nutrient model for the rapid production of high-density microalgal biomass over a broad spectrum of mixotrophic conditions

The superior microalgal biomass productivities obtained under mixotrophic conditions have been widely demonstrated. However, to attain the full potential of the method, optimal conditions for biomass production and resource utilization need to be determined and successfully exploited throughout the process operation. Detailed kinetic mathematical models have often proved most efficient tools for predicting process behavior and governing its overall operation. This paper presents an extensive study for obtaining a highly reliable model for mixotrophic production of microalgae covering a wide set and range of nutritional conditions (10-fold the concentration range of Bold's Basal Medium) and biomass yields up to 6.68 g.L^-1 after only 6 days. The final reduced model includes a total of five state variables and nine parameters: model calibration resulted in very small 95% confidence intervals and relative errors below 5% for all parameters. Model validation showed high reliability with R² correlation values between 0.77 and 0.99.

Pyrolysis-GCMS of Spirulina platensis: Evaluation of biomasses cultivated under autotrophic and mixotrophic conditions

Microalgae are autotrophs and CO2 fixers with great potential to produce biofuels in a sustainable way, however the high cost of biomass production is a challenge. Mixotrophic growth of microalgae has been presented as a great alternative to achieve economic sustainability. Thus, the present work reports the energetic characterization of S. platensis biomasses cultivated under autotrophic (A) and mixotrophic conditions using cheese whey waste at different concentrations, 2.5 (M2.5), 5.0 (M5) and 10.0% (M10), in order to analyze the potential production of valuable chemicals and bio-oil by TGA/DTG and Py-GC/MS. The biochemical compositions of the studied biomasses were different due to the influence of different culture mediums. As the whey concentration increased, there was an increase in the carbohydrate content and a decrease in the protein content, which influenced the elemental composition, calorific value, TGA and volatile compounds evaluated by Py-GC/MS at 450°C, 550°C and 650°C. Sample M10 had lower protein content and formed a smaller amount of nitrogenates compounds by pyrolysis at all temperatures evaluated. There was a reduction of 43.8% (450º), 45.6% (550ºC) and 23.8% (650ºC) in the formation of nitrogenates compounds in relation to sample A. Moreover, the temperature also showed a considerable effect in the formation of volatile compounds. The highest yields of nitrogenates compounds, phenols and aromatic and non-aromatic hydrocarbons were observed at 650ºC. The oxygenated, and N and O containing compounds decreased as the temperature increased. Hydrocarbons such as toluene, heptadecane and heneicosane were produced by S.platensis pyrolysis, which makes this biomass attractive for production of high quality bio-oil and valuable chemicals. Therefore, the results showed that it is possible to decrease the formation of nitrogen compounds via manipulation of growth conditions and temperature.

Optimization and Scale-Up of Fermentation Processes Driven by Models

In the era of sustainable development, the use of cell factories to produce various compounds by fermentation has attracted extensive attention; however, industrial fermentation requires not only efficient production strains, but also suitable extracellular conditions and medium components, as well as scaling-up. In this regard, the use of biological models has received much attention, and this review will provide guidance for the rapid selection of biological models. This paper first introduces two mechanistic modeling methods, kinetic modeling and constraint-based modeling (CBM), and generalizes their applications in practice. Next, we review data-driven modeling based on machine learning (ML), and highlight the application scope of different learning algorithms. The combined use of ML and CBM for constructing hybrid models is further discussed. At the end, we also discuss the recent strategies for predicting bioreactor scale-up and culture behavior through a combination of biological models and computational fluid dynamics (CFD) models.