Explore the vast range of titles available.

This study investigated nutrient removal from anaerobic digestion effluent by cultivating mixed-culture microalgae enriched from anaerobic sludge under different pH conditions: RUC (uncontrolled), R7–8 (maintained at 7–8), and R<8 (maintained below 8). Significant amounts of NH4+-N were lost by volatilization in RUC cultures due to increased pH values (≤8.6) during the early period of cultivation. The pH control strategies significantly affected the biological NH4+-N removal (highest in R7–8), microalgal growth (highest in R7–8), biomass settleability (highest in R<8), and microalgal growth relative to bacteria (highest in R<8) in the cultures. Parachlorella completely dominated the microalgal communities in the inoculum and all of the cultures, and grew well at highly acidic pH (<3) induced by culture acidification with microalgal growth. Microalgae-associated bacterial community structure developed very differently among the cultures. The findings call for more attention to the influence and control of pH changes during cultivation in microalgal treatment of anaerobic digestion effluent.

Microalgae and cyanobacteria are diverse groups of organisms with great potential to benefit societies across the world. These organisms are currently used in food, feed, pharmaceutical and cosmetic industries. In addition, a variety of novel compounds are being isolated. Commercial production of photosynthetic microalgae and cyanobacteria requires cultivation on a large scale with high throughput. However, scaling up production from lab-based systems to large-scale systems is a complex and potentially costly endeavor. In this review, we summarise all aspects of large-scale cultivation, including aims of cultivation, species selection, types of cultivation (ponds, photobioreactors, and biofilms), water and nutrient sources, temperature, light and mixing, monitoring, contamination, harvesting strategies, and potential environmental risks. Importantly, we also present practical recommendations and discuss challenges of profitable large-scale systems associated with economical design, effective operation and maintenance, automation, and shortage of experienced phycologists.

Microalgae are natural resources of intracellular compounds with a wide spectrum of applications in, e.g., the food industry, pharmacy, and biofuel production. The extracellular polymeric substances (EPS) released by microalgal cells are a valuable bioproduct. Polysaccharides, protein, lipids, and DNA are the main constituents of EPS. This review presents the recent advances in the field of the determinants of the synthesis of extracellular polymeric substances by microalgal cells and the EPS structure. Physical and chemical culture conditions have been analyzed to achieve useful insights into the development of a strategy optimizing EPS production by microalgal cells. The application of microalgal EPS for flocculation and mechanisms involved in this process are also discussed in terms of biomass harvesting. Additionally, the ability of EPS to remove toxic heavy metals has been analyzed. With their flocculation and sorption properties, microalgal EPS are a promising bioproduct that can potentially be used in harvesting algal biomass and wastewater management.

Microalgae offer significant potential in diverse fields, including biofuels, carbon capture, and high-value bioproducts. However, optimizing and scaling microalgae cultivation systems present several challenges due to the dynamic interactions among environmental factors such as light intensity, temperature, pH, nutrient concentration, and CO2 levels, as well as species-specific biological variability. Recent advancements in artificial intelligence (AI), particularly machine learning (ML) and automation, have provided innovative solutions to these challenges. This review explored the role of AI in enhancing microalgae technology, focusing on optimizing cultivation conditions, improving CO2 capture, maximizing biomass production, and automating system processes. Key case studies highlight successful applications of AI in biofuel production, carbon capture projects, and high-value compound manufacturing. Key case studies demonstrate that AI-driven models can increase biomass productivity by up to 15–57%, improve CO2 biofixation efficiency, and enhance lipid and high-value compound yields by more than 20–43% compared to traditional methods. Additionally, we discussed the limitations of current AI models, particularly in data availability and species-specific variability, and suggested future research directions to enhance the integration of AI and microalgae systems. By leveraging AI’s potential, microalgae technologies can become more efficient, scalable, and economically viable, addressing global sustainability challenges such as energy production and climate change mitigation.

Microalgae are well-known photosynthetic microorganisms used as cell factories for the production of relevant biotechnological compounds. Despite the outstanding characteristics attributed to microalgae, their industrial-scale production still struggles with scale-up problems and economic feasibility. One important bottleneck is the lack of suitable online sensors for the reliable monitoring of biological parameters, mostly concentrations of intracellular components, in microalgae bioprocesses. Software sensors provide an approach to improving the monitoring of those process parameters that are difficult to quantify directly and are therefore only indirectly accessible. Their use aims to improve the productivity of microalgal bioprocesses through better monitoring, control and automation, according to the current demands of Industry 4.0. In this review, a description of the microalgae components of interest as candidates for monitoring in a cultivation, an overview of software sensors, some of the available approaches and tools, and the current state-of-the-art of the design and use of software sensors in microalgae cultivation are presented. The latter is grouped on the basis of measurement methods used as software sensor inputs, employing either optical or non-optical techniques, or a combination of both. Some examples of software sensor design using simulated process data are also given, grouped according to their design, either as model-driven or data-driven estimators.

Microalgal biomass is currently considered as a sustainable and renewable feedstock for biofuel production (biohydrogen, biomethane, biodiesel) characterized by lower emissions of hazardous air pollutants than fossil fuels. Photobioreactors for microalgae growth can be exploited using many industrial and domestic wastes. It allows locating the commercial microalgal systems in areas that cannot be employed for agricultural purposes, i.e., near heating or wastewater treatment plants and other industrial facilities producing carbon dioxide and organic and nutrient compounds. Despite their high potential, the large-scale algal biomass production technologies are not popular because the systems for biomass production, separation, drainage, and conversion into energy carriers are difficult to explicitly assess and balance, considering the ecological and economical concerns. Most of the studies presented in the literature have been carried out on a small, laboratory scale. This significantly limits the possibility of obtaining reliable data for a comprehensive assessment of the efficiency of such solutions. Therefore, there is a need to verify the results in pilot-scale and the full technical-scale studies. This study summarizes the strengths and weaknesses of microalgal biomass production technologies for bioenergetic applications.

Using microalgae to treat wastewater has received growing attention in the world because it is regarded as a novel means for wastewater treatment. It is commonly recognized that large-scale cultivation and commercial application of microalgae are limited by the development of photobioreactor (PBR). Although there are a lot of PBRs for microalgae pure cultivation which used culture medium, specialized PBRs designed for wastewater treatment are rare. The composition of wastewater is quite complicated; this might cause a very different photosynthetic effect of microalgae compared to those grown in a pure cultivation medium. Therefore, PBRs for wastewater treatment need to be redesigned and improved based on the existing PBRs that are used for microalgae pure cultivation. In this review, different PBRs for microalgae cultivation and wastewater treatment are summarized. PBR configurations, PBR design parameters and types of wastewater are presented. In addition, the wastewater treatment efficiency and biomass productivity were also compared among each type of PBRs. Moreover, some other promising PBRs are introduced in this review, and a two-stage cultivation mode which combines both closed and open system is discussed as well. Ultimately, this article focuses on current problems and gives an outlook for this field, aiming at providing a primary reference for microalgae cultivation by using wastewater.

Humic substances (HS) act as biostimulants for terrestrial photosynthetic organisms. Their effects on plants are related to specific HS features: pH and redox buffering activities, (pseudo)emulsifying and surfactant characteristics, capacity to bind metallic ions and to encapsulate labile hydrophobic molecules, ability to adsorb to the wall structures of cells. The specific properties of HS result from the complexity of their supramolecular structure. This structure is more dynamic in aqueous solutions/suspensions than in soil, which enhances the specific characteristics of HS. Therefore, HS effects on microalgae are more pronounced than on terrestrial plants. The reported HS effects on microalgae include increased ionic nutrient availability, improved protection against abiotic stress, including against various chemical pollutants and ionic species of potentially toxic elements, higher accumulation of value-added ingredients, and enhanced bio-flocculation. These HS effects are similar to those on terrestrial plants and could be considered microalgal biostimulant effects. Such biostimulant effects are underutilized in current microalgal biotechnology. This review presents knowledge related to interactions between microalgae and humic substances and analyzes the potential of HS to enhance the productivity and profitability of microalgal biotechnology.

Microalgal products are an emerging class of food, feed, and nutraceuticals. They include dewatered or dried biomass, isolated pigments, and extracted fat. The oil, protein, and antioxidant-rich microalgal biomass is used as a feed and food supplement formulated as pastes, powders, tablets, capsules, or flakes designed for daily use. Pigments such as astaxanthin (red), lutein (yellow), chlorophyll (green), or phycocyanin (bright blue) are natural food dyes used as isolated pigments or pigment-rich biomass. Algal fat extracted from certain marine microalgae represents a vegetarian source of n-3-fatty acids (eicosapentaenoic acid (EPA), docosahexaenoic acid (DHA), γ-linolenic acid (GLA)). Gaining an overview of the production of microalgal products is a time-consuming task. Here, requirements and options of microalgae cultivation are summarized in a concise manner, including light and nutrient requirements, growth conditions, and cultivation systems. The rentability of microalgal products remains the major obstacle in industrial application. Key challenges are the high costs of commercial-scale cultivation, harvesting (and dewatering), and product quality assurance (toxin analysis). High-value food ingredients are commonly regarded as profitable despite significant capital expenditures and energy inputs. Improvements in capital and operational costs shall enable economic production of low-value food products going down to fishmeal replacement in the future economy.