Extraction of chlorophylls and carotenoids from dry and wet biomass of isolated Chlorella Thermophila: Optimization of process parameters and modelling by artificial neural network

Cohesive phycoremediation of pyrene by freshwater microalgae Selenastrum sp. and biodiesel production and its assessment

In this study, the freshwater microalgae Selenastrum sp. was assessed for the effective degradation of pyrene and simultaneous production of biodiesel from pyrene-tolerant biomass. The growth of algae was determined based on the cell dry weight, cell density, chlorophyll content, and biomass productivity under different pyrene concentrations. Further, lipids from pyrene tolerant culture were converted into biodiesel by acid-catalyzed transesterification, which was characterized for the total fatty acid profile by gas chromatography. Increased pyrene concentration revealed less biomass yield and productivity after 20 days of treatment, indicating potent pyrene biodegradation by Selenastrum sp. Biomass yield was unaffected till the 20 mg/L pyrene. A 95% of pyrene bioremediation was observed at 20 days of culturing. Lipid accumulation of 22.14%, as evident from the estimation of the total lipid content, indicated a marginal increase in corroborating pyrene stress in the culture. Fatty acid methyl esters yield of 63.06% (% per 100 g lipids) was noticed from the pyrene tolerant culture. Moreover, fatty acid profile analysis of biodiesel produced under 10 mg/L and 20 mg/L pyrene condition showed escalated levels of desirable fatty acids in Selenastrum sp., compared to the control. Further, Selenastrum sp. and other freshwater microalgae are catalogued for sustainable development goals attainment by 2030, as per the UNSDG (United Nations Sustainable Development Goals) agenda. Critical applications for the Selenastrum sp. in bioremediation of pyrene, along with biodiesel production, are enumerated for sustainable and renewable energy production and resource management.

Effect of microalgae and bacteria inoculation on the startup of bioreactors for paper pulp wastewater and biofuel production

The use of microalgae and bacteria as a strategy for the startup of bioreactors for the treatment of industrial wastewater can be a sustainable and economically viable alternative. This technology model provides satisfactory results in the nitrification and denitrification process for nitrogen removal, organic matter removal, biomass growth, sedimentation, and byproducts recovery for added-value product production. The objective of this work was to evaluate the performance of microalgae and bacteria in their symbiotic process when used in the treatment of paper pulp industry wastewater. The experiment, lasting fourteen days, utilized four bioreactors with varying concentrations in mgVSS/L of microalgae to bacteria ratio (R1-100:100, R2-100:300, R3-100:500, R4-300:100) in the startup process. Regarding the sludge volumetric index (SVI), the results show that the R1 and R2 reactors developed SVI30/SVI10 biomass in the range of 85.57 ± 7.33% and 84.72 ± 8.19%, respectively. The lipid content in the biomass of reactors R1, R2, R3 e R4 was 13%, 7%, 19%, and 22%, respectively. This high oil content at the end of the batch, may be related to the nutritional stress that the species underwent during this feeding regime. In terms of chlorophyll, the bioreactor with an initial inoculation of 100:100 showed better symbiotic growth of microalgae and bacteria, allowing exponential growth of microalgae. The total chlorophyll value for this bioreactor was 801.46 ± 196.96 μg/L. Biological removal of nitrogen from wastewater from the paper pulp industry is a challenge due to the characteristics of the effluent, but the four reactors operated in a single batch obtained good nitrogen removal. Ammonia nitrogen removal performances were 91.55 ± 9.99%, 72.13 ± 19.18%, 64.04 ± 21.34%, and 86.15 ± 30.10% in R1, R2, R3, and R4, respectively.

A review on machine learning approaches for microalgae cultivation systems

Microalgae plays a crucial role in biomass production within aquatic environments and are increasingly recognized for their potential in generating biofuels, biomaterials, bioactive compounds, and bio-based chemicals. This growing significance is driven by the need to address imminent global challenges such as food and fuel shortages. Enhancing the value chain of bio-based products necessitates the implementation of an advanced screening and monitoring system. This system is crucial for tailoring and optimizing the cultivation conditions, ensuring the lucrative and efficient production of the final desired product. This, in turn, underscores the necessity for robust predictive models to accurately emulate algae growth in different conditions during the initial cultivation phase and simulate their subsequent processing in the downstream stage. In pursuit of these objectives, diverse mechanistic and machine learning-based methods have been independently employed to model and optimize microalgae processes. This review article thoroughly examines the techniques delineated in the literature for modeling, predicting, and monitoring microalgal biomass across various applications such as bioenergy, pharmaceuticals, and the food industry. While highlighting the merits and limitations of each method, we delve into the realm of newly emerging hybrid approaches and conduct an exhaustive survey of this evolving methodology. The challenges currently impeding the practical implementation of hybrid techniques are explored, and drawing inspiration from successful applications in other machine-learning-assisted fields, we review various plausible solutions to overcome these obstacles.

Characterization of halotolerant microalga isolated from waterlogged habitats: Deciphering the biochemical profiling and unraveling the molecular identity

The primary objective of this study was to comprehensively explore the biochemical profile of the novel halotolerant microalgae strain, biogas laboratory scenedesmus (BGLRS), previously isolated from waterlogged regions in the southwest zone of Punjab, India. To achieve this, three distinct drying methods viz. freeze-drying, oven-drying, and shade-drying were employed and biochemical composition and antioxidant analyses on the microalgal biomass were conducted. Utilizing advanced analytical techniques, including high-performance liquid chromatography (HPLC), inductively coupled plasma-atomic emission spectroscopy (ICP-AES), and gas chromatography-mass spectroscopy (GC-MS) on freeze-dried biomass, its carbohydrate profile, micronutrient composition, and presence of bioactive compounds with potential therapeutic and nutraceutical significance were sought to unravel. Among the drying methods evaluated, freeze-drying exhibited the most promising experimental results, prompting its selection for further investigation. Notably, ICP-AES unveiled elevated concentrations of essential elements such as calcium, iron, magnesium, and phosphorus in BGLRS, with negligible traces of heavy metals, underscoring its safety for human consumption. GC-MS analysis further divulged the existence of numerous biologically active compounds, indicating potential applications in medical and nutraceutical fields. Through molecular identification using sequencing of the internal transcribed spacer (ITS) region, a close taxonomic resemblance between BGLRS and Scenedesmus sp. MKB was established, solidifying its unique position within the microalgal taxonomy. The deposition of ITS sequences into the NCBI GenBank, obtaining accession number MN796425, attests to the rigor and transparency of this research. Overall, these findings strongly suggest that microalgae BGLRS possesses high-quality biochemical attributes of significant therapeutic and nutraceutical importance.

Microalgal biorefineries: Advancement in machine learning tools for sustainable biofuel production and value-added products recovery

The microalgae can be converted into biofuels, biochemicals, and bioactive compounds in a biorefinery. Recently, designing and executing more viable and sustainable biofuel production from microalgal biomass is one of the vital challenges in the development of biorefinery. Scalable cultivation of microalgae is mandatory for commercializing and industrializing the biorefinery. The intrinsic complication in cultivation of microalgae is the physiological and operational factors that renders challenging impact to enable a smooth and profitable operation. However, this aim can only be successful via a simulation prospect. Machine learning tools provides advanced approaches for evaluating, predicting, and controlling uncertainties in microalgal biorefinery for sustainable biofuel production. The present review provides a critical evaluation of the most progressing machine learning tools that validate a potential to be employed in microalgal biorefinery. These tools are highly potential for their extensive evaluation on microalgal screening and classification. However, the application of these tools for optimization of microalgal biomass cultivation in industries in order to increase the biomass production, is still in its initial stages. Integrated hybrid machine learning tools can aid the industries to function efficiently with least resources. Some of the challenges, and perspectives of machine learning tools are discussed. Besides, future prospects are also emphasized. Though, most of the research reports on machine learning tools are not appropriate to gather generalized information, standard protocols and strategies must be developed to design generalized machine learning tools. On a whole, this review offers a perspective information about digitalized microalgal exploitation in a microalgal biorefinery.

Effects of CO2 concentration and time on algal biomass film, NO3-N concentration, and pH in the membrane bioreactor: Simulation-based ANN, RSM and NSGA-II

The practice of aquaculture is associated with the generation of a substantial quantity of effluent. Microalgae must effectively assimilate nitrogen and phosphorus from their surrounding environment for growth. This study modeled the algal biomass film, NO3-N concentration, and pH in the membrane bioreactor using the response surface methodology (RSM) and an artificial neural network (ANN). Furthermore, it was suggested that the optimal condition for each parameter be determined. The results of ANN modeling showed that ANN with a structure of 5-3 and employing the transfer functions tansig-logsig demonstrated the highest level of accuracy. This was evidenced by the obtained values of coefficient (R2) = 0.998, R = 0.999, mean squared error (MAE) = 0.0856, and mean square error (MSE) = 0.143. The ANN model, characterized by a 5-5 structure and employing the tansig-logsig transfer function, demonstrates superior accuracy when predicting the concentration of NO3-N and pH. This is evidenced by the high values of R2 (0.996), R (0.998), MAE (0.00162), and MSE (0.0262). The RSM was afterward employed to maximize the performance of algal film biomass, pH levels, and NO3-N concentrations. The optimal conditions for the algal biomass film were a concentration of 2.884 mg/L and a duration of 6.589 days. Similarly, the most favorable conditions for the NO3-N concentration and pH were 2.984 mg/L and 6.787 days, respectively. Therefore, this research uses non-dominated sorting genetic algorithm II (NSGA II) to find the optimal NO3-N concentration, algal biomass film, and pH for product or process quality. The region has the greatest alkaline pH and lowest NO3-N content.

The Effect of Ethephon on Ethylene and Chlorophyll in Zoysia japonica Leaves

Zoysia japonica (Zoysia japonica Steud.) is a kind of warm-season turfgrass with many excellent characteristics. However, the shorter green period and longer dormancy caused by cold stress in late autumn and winter are the most limiting factors affecting its application. A previous transcriptome analysis revealed that ethephon regulated genes in chlorophyll metabolism in Zoysia japonica under cold stress. Further experimental data are necessary to understand the effect and underlying mechanism of ethephon in regulating the cold tolerance of Zoysia japonica. The aim of this study was to evaluate the effects of ethephon by measuring the enzyme activity, intermediates content, and gene expression related to ethylene biosynthesis, signaling, and chlorophyll metabolism. In addition, the ethylene production rate, chlorophyll content, and chlorophyll a/b ratio were analyzed. The results showed that ethephon application in a proper concentration inhibited endogenous ethylene biosynthesis, but eventually promoted the ethylene production rate due to its ethylene-releasing nature. Ethephon could promote chlorophyll content and improve plant growth in Zoysia japonica under cold-stressed conditions. In conclusion, ethephon plays a positive role in releasing ethylene and maintaining the chlorophyll content in Zoysia japonica both under non-stressed and cold-stressed conditions.

Chemical Composition of Wild Collected and Cultivated Edible Plants (Sonchus oleraceus L. and Sonchus tenerrimus L.)

The present work investigates the nutritional and bioactive composition, as well as the organoleptic and sensory properties, of S. oleraceus and S. tenerrimus, two wild plant species traditionally used in the gastronomy of the Mediterranean area. Additionally, the effect of cultivation on leaf composition was assessed to explore their potential for large-scale production and commercialization from the point of view of possible losses or gains in quality. Both species were characterized as a good source of bioactive compounds, such as vitamins, pro-vitamins and carotenoids, with health-promoting and antioxidant properties that are highly appreciated. The sensory profile revealed a good general acceptance of S. oleraceus and S. tenerrimus, indicating that they could be included in the diet. Although the cultivation of S. oleraceus resulted in a decrease in the concentration of phenolic compounds when compared to wild-harvested plants, the opposite occurred for vitamin C. In S. tenerrimus, cultivation also increased the concentration of other compounds with important nutritional and healthy properties, such as sugars, organic acids and β-carotene. The results of the composition, organoleptic and sensory properties of S. oleraceus and S. tenerrimus support the idea of their potential to be used as edible leafy vegetables and as promising assets for functional foods.

Appraising the phycoremediation potential of cyanobacterial strains Phormidium and Oscillatoria for nutrient removal from textile wastewater (TWW) and synchronized biodiesel production from TWW-tolerant biomass

In this study, phycoremediation of textile wastewater (TWW) by freshwater cyanobacterial strains such as sp., Oscillatoria sp. F01 and Oscillatoria sp. F02 was evaluated, and lipids were simultaneously extracted from biomass for biodiesel production. Onset of the study, Phormidium sp. and Oscillatoria sp. F01 has better growth rates, increased biomass production, high chlorophyll content, and efficient nutrient utilization in TWW compared to Oscillatoria sp. F02. Phormidium sp. showed 1.41 g/L dry weight, followed by Oscillatoria sp. F01 with 1.39 g/L and Oscillatoria sp. F02 with 1.02 g/L biomass. Both strains demonstrated their capability to elevate the pH level while reducing TDS and eliminating/reducing several nutrients such as nitrates, nitrites, phosphates, sulphates, sulphides, chlorides, calcium, sodium, and magnesium. Further, the total lipids extracted from the TWW-grown Phormidium sp., Oscillatoria sp. F01 and Oscillatoria sp. F02 was estimated to be 8.20, 13.70 and 11.20 %, respectively, on day 21, which was higher than the lipid content obtained from control cultures. Further, biodiesel produced from the lipids of all strains showed higher levels of C12:0, C16:0, C16:1, C18:1, C18:2, and C18:3 among all the fatty acids. Therefore, they can potentially offer a valuable source of lipids and diverse fatty acids for high-quality biodiesel production. This integrated system not only offers a solution for TWW treatment but also provides a feedstock for renewable fuel production simultaneously.

Bridging artificial intelligence and fucoxanthin for the recovery and quantification from microalgae

Fucoxanthin is a carotenoid that possesses various beneficial medicinal properties for human well-being. However, the current extraction technologies and quantification techniques are still lacking in terms of cost validation, high energy consumption, long extraction time, and low yield production. To date, artificial intelligence (AI) models can assist and improvise the bottleneck of fucoxanthin extraction and quantification process by establishing new technologies and processes which involve big data, digitalization, and automation for efficiency fucoxanthin production. This review highlights the application of AI models such as artificial neural network (ANN) and adaptive neuro fuzzy inference system (ANFIS), capable of learning patterns and relationships from large datasets, capturing non-linearity, and predicting optimal conditions that significantly impact the fucoxanthin extraction yield. On top of that, combining metaheuristic algorithm such as genetic algorithm (GA) can further improve the parameter space and discovery of optimal conditions of ANN and ANFIS models, which results in high R2 accuracy ranging from 98.28% to 99.60% after optimization. Besides, AI models such as support vector machine (SVM), convolutional neural networks (CNNs), and ANN have been leveraged for the quantification of fucoxanthin, either computer vision based on color space of images or regression analysis based on statistical data. The findings are reliable when modeling for the concentration of pigments with high R2 accuracy ranging from 66.0% - 99.2%. This review paper has reviewed the feasibility and potential of AI for the extraction and quantification purposes, which can reduce the cost, accelerate the fucoxanthin yields, and development of fucoxanthin-based products.

Bubble column photobioreactor (BCPR) for cultivating microalgae and microalgal consortium (Co-CC) with additional CO2 supply for enhancing biomass, lipid, and preferable fatty acids production

The present study has designed and developed a 5 L bubble column photobioreactor (BCPR) to investigate two microalgal strains Chlorella sp. S-01, Chlorella sp. S-02 and their consortium Co-CC (Chlorella sp. S-01 + Chlorella sp. S-02) at 0.03, 5, and 10% CO2 supply for biomass and lipid production. The dry cell weight of Chlorella sp. S-01, Chlorella sp. S-02 and Co-CC were, respectively about 1.41, 1.32, and 1.39 g/L on the 20th day without CO2 supply, while it was 1.76, 1.61, and 1.87 g/L, respectively at 10% CO2 supply and similarly, chlorophyll-a content was higher in 10% CO2 supplied condition over control. Interestingly, Co-CC grown at all the CO2 concentrations showed similar lipid content between 19.30 and 1F9.41%. As an integrated refinery approach, de-oiled biomass of Co-CC was subjected to carbohydrates and protein estimation and found that 46.2% and 30.80% in 10% CO2 supply condition in BCPR. Lipid extracted from the Co-CC grown under 0.03, 5, and 10% CO2 supply in 5L BCPR was converted to biodiesel, and the biodiesel yield was estimated to be 62.78%. Further, the fatty acid profile of Co-CC grown at 10% CO2 showed higher levels of C16:0, C16:1, C18:1, and monounsaturated fatty acids contents over other CO2 supplied conditions. Biodiesel of Co-CC showed favourable fuel properties such as density, higher heating value, oxidative stability, CFPP, viscosity, degree of unsaturation, saponification value, and cetane number, which were also in accordance with ASTM, and EN, biodiesel standards.

Microalgal upgrading of the fermentative biohydrogen produced from Bacillus coagulans via non-pretreated plant biomass

BACKGROUND

Hydrogen is a promising source of alternative energy. Fermentative production is more feasible because of its high hydrogen generation rate, simple operating conditions, and utilization of various organic wastes as substrates. The most significant constraint for biohydrogen production is supplying it at a low cost with fewer impurities.

RESULTS

Leaf biomass of Calotropis procera was used as a feedstock for a dark fermentative production of hydrogen by Bacillus coagulans AH1 (MN923076). The optimum operation conditions for biohydrogen production were 5.0% substrate concentrationand pH 9.0, at 35 °C. In which the biohydrogen yield was 3.231 mmol H2/g dry biomass without any pretreatments of the biomass. A freshwater microalga Oscillatroia sp was used for upgrading of the produced biohydrogen. It sequestrated 97 and 99% % of CO2 from the gas mixture when it was cultivated in BG11 and BG11-N media, respectively After upgrading process, the residual microalgal cells exhibited 0.21mg/mL of biomass yield,high content of chlorophyll-a (4.8 µg/mL) and carotenoid (11.1 µg/mL). In addition to Oscillatroia sp residual biomass showed a lipid yield (7.5-8.7%) on the tested media.

CONCLUSION

Bacillus coagulans AH1 is a promising tool for biohydrogen production avoiding the drawbacks of biomass pretreatment. Oscillatroia sp is encouraged as a potent tool for upgrading and purification of biohydrogen. These findings led to the development of a multiproduct biorefinery with zero waste that is more economically sustainable.

Enhancement for the synthesis of bio-energy molecules (carbohydrates and lipids) in Desmodesmus subspicatus: experiments and optimization techniques

Microalgae are regarded as renewable resources of energy, foods and high-valued compounds using a biorefinery approach. In the present study, we explored isolated microalgae (Desmodesmus subspicatus) for the production of bio-energy molecules (carbohydrate and lipid). Optimizations of media (BG-11) components have been made using the Taguchi orthogonal array (TOA) technique to maximize biomass, carbohydrate and lipid production. Optimized results showed that biomass, carbohydrates and lipid productivity increased by 1.3 times at optimal combinations of media components than standard BG-11 media. Further, the influence of various carbon and nitrogen sources as nutritional supplement with optimum media composition under different light intensities was investigated for productivity of carbohydrate and lipid. Results demonstrated that 1.5 times higher productivity of carbohydrate and lipids were achieved in the presence optimum BG-11 under a broad range of light intensities (84-504 µmol m-2 s-1). Among different nitrogen sources, glycine was found to give higher productivity (1.5 times) followed by urea. Use of the cellulose as a carbon source in the media significantly increases biomass (2.4 times), carbohydrates (2.3 times) and lipids (2.3 times) productivity. Investigations revealed that cultivating Desmodesmus subspicatus under optimum culture conditions has the potential for large-scale bio-ethanol and bio-diesel production.

Natural Carotenoids: Recent Advances on Separation from Microbial Biomass and Methods of Analysis

Biotechnologically produced carotenoids occupy an important place in the scientific research. Owing to their role as natural pigments and their high antioxidant properties, microbial carotenoids have been proposed as alternatives to their synthetic counterparts. To this end, many studies are focusing on their efficient and sustainable production from renewable substrates. Besides the development of an efficient upstream process, their separation and purification as well as their analysis from the microbial biomass confers another important aspect. Currently, the use of organic solvents constitutes the main extraction process; however, environmental concerns along with potential toxicity towards human health necessitate the employment of "greener" techniques. Hence, many research groups are focusing on applying emerging technologies such as ultrasounds, microwaves, ionic liquids or eutectic solvents for the separation of carotenoids from microbial cells. This review aims to summarize the progress on both the biotechnological production of carotenoids and the methods for their effective extraction. In the framework of circular economy and sustainability, the focus is given on green recovery methods targeting high-value applications such as novel functional foods and pharmaceuticals. Finally, methods for carotenoids identification and quantification are also discussed in order to create a roadmap for successful carotenoids analysis.

Chlorophylls as Natural Bioactive Compounds Existing in Food By-Products: A Critical Review

Chlorophylls are a group of naturally occurring pigments that are responsible for the green color in plants. This pigment group could have numerous health benefits due to its high antioxidant activity, including anti-inflammatory, anti-cancer, and anti-obesity properties. Many food by-products contain a high level of chlorophyll content. These by-products are discarded and considered environmental pollutants if not used as a source of bioactive compounds. The recovery of chlorophylls from food by-products is an interesting approach for increasing the sustainability of food production. This paper provides insight into the properties of chlorophylls and the effect of different treatments on their stability, and then reviews the latest research on the extraction of chlorophylls from a sustainable perspective.

Optimization of the culture of Chlorella sorokiniana PA.91 by RSM: effect of temperature, light intensity, and MgAC-NPs

The unique physicochemical properties of magnesium amino clay nanoparticles (MgAC-NPs) tends to be beneficial in the application as a co-additive in treating microalgae. Also, MgAC-NPs can create oxidative stress in the environment, concurrently elective control bacteria in mixotrophic culture, and stimulate CO₂ biofixation. The condition of the cultivation of newly isolated strains, Chlorella sorokiniana PA.91, was optimized for the first time for MgAC-NPs at various temperatures and light intensities in the culture medium of municipal wastewater (MWW) by central composite design in the response surface methodology (RSM-CCD). This study examined synthesized MgAC-NP with their FE-SEM, EDX, XRD, and FT-IR characteristics. The synthesized MgAC-NPs were naturally stable, cubic shaped, and within the size range of 30-60 nm. The optimization results show that at culture conditions of 20 °C, 37 μmol m^-2 s^-1, and 0.05 g L^-1, microalga MgAC-NPs have the best growth productivity and biomass performance. Maximum dry biomass weight (55.41%), specific growth rate (30.26%), chlorophyll (81.26%), and carotenoids (35.71%) were achieved under the optimized condition. Experimental results displayed that C.S. PA.91 has a high capacity for lipid extraction (1.36 g L^-1) and significant lipid efficiency (45.1%). Also, in 0.2 and 0.05 g L^-1 of the MgAC-NPs, COD removal efficiency 91.1% and 81.34% from C.S. PA.91 showed, respectively. These results showed the potential of C.S. PA.91-MgAC-NPs for nutrient removal in wastewater treatment plants and their quality as sources of biodiesel.

Development of an HPLC-PDA Method for the Determination of Capsanthin, Zeaxanthin, Lutein, β-Cryptoxanthin and β-Carotene Simultaneously in Chili Peppers and Products

For the better standardization and widespread application of the determination method of carotenoids in both chili peppers and their products, this work reports for the first time the simultaneous determination of five main carotenoids, including capsanthin, zeaxanthin, lutein, β-cryptoxanthin and β-carotene in chili peppers and their products, with optimized extraction and the high-performance liquid chromatography (HPLC) method. All parameters in the methodological evaluation were found to be in good stability, recovery and accuracy compliance with the reference values; the R coefficients for the calibration curves were more than 0.998; and the LODs and LOQs varied from 0.020 to 0.063 and from 0.067 to 0.209 mg/L, respectively. The characterization of five carotenoids in chili peppers and their products passed all the required validation criteria. The method was applied in the determination of carotenoids in nine fresh chili peppers and seven chili pepper products.

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.

Emerging trends in the pretreatment of microalgal biomass and recovery of value-added products: A review

Microalgae are a promising source of raw material (i.e., proteins, carbohydrates, lipids, pigments, and micronutrients) for various value-added products and act as a carbon sink for atmospheric CO₂. The rigidity of the microalgal cell wall makes it difficult to extract different cellular components for its applications, including biofuel production, food and feed supplements, and pharmaceuticals. To improve the recovery of products from microalgae, pretreatment strategies such as biological, physical, chemical, and combined methods have been explored to improve whole-cell disruption and product recovery efficiency. However, the diversity and uniqueness of the microalgal cell wall make the pretreatment process more species-specific and limit its large-scale application. Therefore, advancing the currently available technologies is required from an economic, technological, and environmental perspective. Thus, this paper provides a state-of-art review of the current trends, challenges, and prospects of sustainable microalgal pretreatment technologies from a microalgae-based biorefinery concept.

Effect of Electrofiltration on the Dewatering Kinetics of Arthrospira platensis and Biocompound Recovery

Arthrospira platensis (A. platensis) is a microalga with a wide range of commercial uses. One of the main concerns that needs to be addressed in microalgae biorefineries is the costs associated with the harvesting and concentration steps. Filtration has been shown to be an effective technique for concentrating microalgae and recent studies have attempted to enhance membrane filtration by applying an external electric field to the filtration cell. This study consisted of assessing the use of electrically assisted filtration (electrofiltration) at 60 A/m2 and 1 bar for the dewatering of A. platensis, as well as the effect of pretreating the microalgae with ultrasounds (US) on the filtration process. Untreated A. platensis exhibited better filtration kinetics than US-treated A. platensis, and electrofiltration was found to increase the cake dryness. More protein and pigments were present in the US-treated microalgae solution compared to the untreated microalgae, which led to the presence of higher concentrations of protein and pigments in the filtrate streams after pressure filtration at 1 bar without the application of an external electric field. Electrofiltration was found to consume less energy compared to traditional drying techniques used for A. platensis. However, electrofiltration degrades the biocompounds present in the filtrate and cake due to pH changes and other electrophoresis phenomena, which shows the need to optimize the process in future work.

Strategy Development for Microalgae Spirulina platensis Biomass Cultivation in a Bubble Photobioreactor to Promote High Carbohydrate Content

As a counter to climate change, energy crises, and global warming, microalgal biomass has gained a lot of interest as a sustainable and environmentally favorable biofuel feedstock. Microalgal carbohydrate is considered one of the promising feedstocks for biofuel produced via the bioconversion route under a biorefinery system. However, the present culture technique, which uses a commercial medium, has poor biomass and carbohydrate productivity, creating a bottleneck for long-term microalgal-carbohydrate-based biofuel generation. This current investigation aims toward the simultaneous increase in biomass and carbohydrate accumulation of Spirulina platensis by formulating an optimal growth condition under different concentrations of nitrogen and phosphorous in flasks and a bubble photobioreactor. For this purpose, the lack of nitrogen (NaNO3) and phosphorous (K2HPO4) in the culture medium resulted in an enhanced Spirulina platensis biomass and total carbohydrate 0.93 ± 0.00 g/L and 74.44% (w/w), respectively. This research is a significant step in defining culture conditions that might be used to tune the carbohydrate content of Spirulina.

Bioprospecting of marine microalgae from Kaohsiung Seacoast for lutein and lipid production

A bioprospecting study was conducted from Seawater samples collected at Kaohsiung Seacoast, Taiwan. The current research was aimed to isolate potential lutein-producing strain, evaluate and optimize the best cultivation mode, lutein accumulation stage, lutein-extraction method, and condition to recover maximum lutein (main product) and lipid (byproduct). Biorefinery is the latest approach worldwide to extract multi-products for cost-effectiveness. Selected isolate among several isolates, identified as Chlorella sorokiniana Kh12 and exploited under biorefinery concept for lutein and lipid extraction. Kh12 cultivated under mixotrophy: 2X-(HT)-9k yielded maximum biomass (3.46 g L^-1) and lutein (13.69 mg g^-1) which is among the higher yields reported so far. Among various tested solvents, methanol was the best extractor. Bead milling was most effective to disrupt algal cell walls, seven minutes of milling was best for maximum lutein (7.56 mg g^-1) extraction. Kh12 could be a promising candidate for commercial lutein and lipid co-production based on the outcome.

Enhancement of growth and biomolecules (carbohydrates, proteins, and chlorophylls) of isolated Chlorella thermophila using optimization tools

The production of multiple products from microalgae is essential for economic sustainability and the knowledge of optimum cultivation conditions for high growth and biomolecule synthesis of a microalgal strain is the prerequisite for its commercial production. In this work, optimization of nutrient concentrations for the cultivation of isolated Chlorella thermophila was performed by manipulating nine nutrients with the objectives of maximization of growth, carbohydrate, protein, and chlorophyll contents. Experiments were designed and effects of the parameters were studied using Taguchi orthogonal array (TOA). Experimental results of TOA were used for modeling artificial neural networks (ANN) followed by the optimization using genetic algorithm (GA) to find global optimal solutions. Results showed an increase of 36, 88, 36, and 88% for growth, carbohydrates, proteins, and chlorophylls, respectively, at optimal combinations of parameters given by TOA. Results obtained through the ANN-GA optimization were 9, 10, and 3% more compared to the TOA for biomass, carbohydrates, and chlorophylls, respectively with experimental verification. Nitrates and bicarbonate were found to play the most pivotal role in biomass and biomolecule synthesis of the isolated microalgal strain. Results of the current investigation can be used in the industrial scale-up for the production of multiple products using the biorefinery approach.

Evaluation of Nutraceutical Properties of Eleven Microalgal Strains Isolated from Different Freshwater Aquatic Environments: Perspectives for Their Application as Nutraceuticals

The increasing global population and the simultaneous growing attention to natural, sustainable, and healthier products are driving the food industry towards research on alternative food sources. In this scenario, microalgae are gaining worldwide attention as "functional feedstocks" for foods, feeds, supplements, and nutraceutical formulations, being a source of high-value metabolites including polyphenols and other antioxidant compounds. In this work, eleven microalgal strains from freshwater environments were evaluated for their nutraceutical properties, focusing on photosynthetic pigments, total polyphenols, and flavonoid content, as well as in vitro antioxidant activities. Data helped to select those strains showing the most promising features for simultaneous massive growth and bioactive compound production. Results highlighted that the microalgae have variable values for both biochemical parameters and antioxidant activities, mainly depending on the solvents and applied treatment rather than on the isolation sources or the phylogenetic attribution. According to our results, the putative best candidates for massive cultivation under laboratory conditions for the simultaneous extraction of different molecules with nutraceutical potential are strains F1 (Scenedesmaceae), F3 (Chlamydomonas debariana), R1 (Chlorella sorokiniana), and C2 (Chlorella-like).

Photosynthesis and pigment production: elucidation of the interactive effects of nutrients and light on Chlamydomonas reinhardtii

Chlamydomonas reinhardtii produces a variety of compounds that can be beneficial to human and animal health. Among these compounds, application of photosynthetic pigments, such as chlorophylls and carotenoids, has gained considerable interest in numerous industries. A better understanding on the interactive effects of essential nutrients and light on microalgal physiology and pigment production would be beneficial in improving cultivation strategies. Therefore, this study evaluated biomass, carotenoid and chlorophyll yield and the following fluorescence parameters: quantum yield in PS II [Y(II)] and electron transport rate (ETR) using response surface methodology (RSM). The F_v/F_m, Y(NO) and Y(NPQ) were also monitored; however, no significant relationship was observed. From the investigation it was apparent that nitrogen and carbon; as well as the interactive effects of (nitrogen and carbon) and (carbon and light irradiance) were significant factors. The model predicted the optimum conditions for maximum carotenoids (8.15 ± 0.389 mg g^-1) were 08.7 mol l^-1 of nitrogen, 0.2 mol l^-1 and 50 μmol photon m^-2 s^-1 of light irradiance. While maximum chlorophyll (33.6 ± 0.854 mg g^-1) required a higher nitrogen (11.21 mol l^-1). The photosynthetic parameters [Y(II), ETR] was correlated with the primary pigments and biomass production. Increased photosynthetic activity was associated with high carbon and light. The Y(II)and ETR of PSII under these conditions were 0.2 and ~ 14, respectively. This approach was accurate in developing the model, optimizing factors and analysing interaction effects. This study served to provide a better understanding on the interactions between factors influencing pigment biosynthesis and photosynthetic performance of Chlamydomonas reinhardtii.

A comprehensive review on carotenoids in foods and feeds: status quo, applications, patents, and research needs

Carotenoids are isoprenoids widely distributed in foods that have been always part of the diet of humans. Unlike the other so-called food bioactives, some carotenoids can be converted into retinoids exhibiting vitamin A activity, which is essential for humans. Furthermore, they are much more versatile as they are relevant in foods not only as sources of vitamin A, but also as natural pigments, antioxidants, and health-promoting compounds. Lately, they are also attracting interest in the context of nutricosmetics, as they have been shown to provide cosmetic benefits when ingested in appropriate amounts. In this work, resulting from the collaborative work of participants of the COST Action European network to advance carotenoid research and applications in agro-food and health (EUROCAROTEN, www.eurocaroten.eu, https://www.cost.eu/actions/CA15136/#tabs|Name:overview) research on carotenoids in foods and feeds is thoroughly reviewed covering aspects such as analysis, carotenoid food sources, carotenoid databases, effect of processing and storage conditions, new trends in carotenoid extraction, daily intakes, use as human, and feed additives are addressed. Furthermore, classical and recent patents regarding the obtaining and formulation of carotenoids for several purposes are pinpointed and briefly discussed. Lastly, emerging research lines as well as research needs are highlighted.

Influence of Low Salt Concentration on Growth Behavior and General Biomass Composition in Lyngbya purpurem (Cyanobacteria)

Cyanobacteria are essential for the vast number of compounds they produce and the possible applications in the pharmaceutical, cosmetical, and food industries. As Lyngbya species' characterization is limited in the literature, we characterize this cyanobacterium's growth and biomass. L. purpureum was grown and analyzed under different salinities, culture media, and incubation times to determine the best conditions that favor its cell growth and the general production of proteins, carbohydrates, lipids, and some pigments as phycocyanin and chlorophyll a. In this study, each analyzed biomolecule's highest content was proteins 431.69 mg g^-1, carbohydrates 301.45 mg g^-1, lipids 131.5 mg g^-1, chlorophyll a 4.09 mg g^-1, and phycocyanin 40.4 mg g^-1. These results can provide a general context of the possible uses that can be given to biomass and give an opening to investigate possible biocompounds or bio metabolites that can be obtained from it.