Algal Concentration Research Articles

Fabrication of Magnetic Silica Nanomaterials and Their Effects on Algal Harvesting

Harmful algal blooms are a global problem in water environments, and their explosive growth endangers the health of aquatic ecosystems. Magnetic nanomaterials for the harvesting of microalgae have received a lot of attention because of their high efficiency, low cost, and ease of operation. In this study, magnetic mesoporous silica nanomaterials were prepared using Fe3O4 as a carrier and harvesting on Chlorella sp. HQ. It was found that silica coated with magnetic Fe3O4 microspheres has good dispersion. The harvesting of Chlorella sp. HQ via magnetic mesoporous silica could be maintained over a wide pH range (4 to 12). After the removal of organic components from the surface of the material, the magnetic mesoporous silica obtained a better porous structure. The ethanol reflux method was more beneficial than the calcination method in maintaining the stable structure of the material, thus improving the harvesting efficiency of the material for the microalgae Chlorella sp. HQ by a maximum of 17.8% (65.9% to 83.7%). When the molar ratio of active agent cetyltrimethylammonium bromide (CTAB) and stabilizer polyvinylpyrrolidone (PVP) was 1: 0.092 at pH 4 and algal concentration of 0.5 g/L, the materials showed the maximum harvesting efficiency of Chlorella sp. HQ was 84.2%.

Simultaneous utilization of CO2 and nitrate wastes from compact recirculating aquaculture system for improving algal biomass (Scenedesmus armatus) production

Tilapia cultivation in an air-tight culture tank of a recirculating aquaculture system (RAS) was conducted for 8 days to produce CO2 for growing Scenedesmus armatus in bubble column photobioreactors. The average CO2 concentrations in the headspace of the culture tank were determined at 925 ± 73.4 and 1619 ± 197.7 ppm for fish stocking densities of 3 and 10 kg/m3, respectively. These CO2 concentrations were higher than CO2 concentrations at the tank inlet (496 ± 13.9 ppm) exposed to the atmosphere. Using the captured CO2 and nitrate from the effluent of a commercial tilapia farm for cultivating S. armatus yielded higher algal biomass concentration (621 ± 41.2 mg/L) than using ambient air (410 ± 30.1 mg/L). Insufficient nitrate in RAS effluent is the limiting factor for CO2 utilization and algal biomass production. In conclusion, this study demonstrates the possibility of repurposing CO2 from RAS to enhance algal cultivation.

Feasibility of growing microalgae on wastewaters collected from a vinegar plant for, concurrently, nutrient removal and biomass production

In this work, feasibility of using winemaking wastewater (WW), vinegar wastewater (VW), and pickle wastewater (PW) to cultivate microalgae was investigated. Results showed that the three wastewaters possessed different nutrient profiles due to their various sources, and VW was much richer in nutrients than WW and PW. The maximum biomass concentrations of 0.73, 2.45, and 0.64 g L−1 were observed when Chlorella vulgaris was cultivated in WW, VW, and PW, respectively, suggesting that VW was a potential algal culture medium. Moreover, four algal strains could grow well on VW, but biomass production and nutrient removal of C. vulgaris were significantly higher than that of the other three strains, indicating that this alga was a promising algal strain for VW treatment. Furtherly, initial cell density was optimized for improving nutrients removal and biomass production. The maximum biomass concentration and productivity of 2.83 g L−1 and 349.8 mg L−1 d−1, and TN, TP, and COD removal efficiencies of 80.02, 64.38, and 77.10 %, respectively, were obtained when initial cell density was 0.4 g L−1. Initial cell density had little impact on the algal chemical composition, but availability and concentration of nutrients and algal species exhibited remarkable influences on the chemical compositions of microalgae cultivated in these wastewaters. These findings not only verified the feasibility of using vinegar production wastewaters to cultivate microalgae, but also paved a way for large-scale microalgae cultivation using the wastewaters.

Hybrid machine learning techniques in the management of harmful algal blooms impact

Harmful algal blooms (HABs) are episodes of high concentrations of algae that are potentially toxic for human consumption. Mollusc farming can be affected by HABs because, as filter feeders, they can accumulate high concentrations of marine biotoxins in their tissues. To avoid the risk to human consumption, harvesting is prohibited when toxicity is detected. At present, the closure of production areas is based on expert knowledge and the existence of a predictive model would help when conditions are complex and sampling is not possible. Although the concentration of toxin in meat is the method most commonly used by experts in the control of shellfish production areas, it is rarely used as a target by automatic prediction models. This is largely due to the irregularity of the data due to the established sampling programs. As an alternative, the activity status of production areas has been proposed as a target variable based on whether mollusc meat has a toxicity level below or above the legal limit. This new option is the most similar to the actual functioning of the control of shellfish production areas. For this purpose, we have made a comparison between hybrid machine learning models like Neural-Network-Adding Bootstrap (BAGNET) and Discriminative Nearest Neighbor Classification (SVM-KNN) when estimating the state of production areas. The study has been carried out in several estuaries with different levels of complexity in the episodes of algal blooms to demonstrate the generalization capacity of the models in bloom detection. As a result, we could observe that, with an average recall value of 93.41% and without dropping below 90% in any of the estuaries, BAGNET outperforms the other models both in terms of results and robustness.

Enhancing the Growth Performance, Cellular Structure, and Rubisco Gene Expression of Cadmium Treated Brassica chinensis Using Sargassum polycystum and Spirulina platensis Extracts

Cadmium (Cd) is one of the highly toxic, non-essential heavy metals that inhibit plant growth and development by prompting chlorophyll loss and affecting photosynthetic activities. This study investigated the efficacy of Spirulina platensis and Sargassum polycystum extracts in alleviating Cd stress in Pak Choi at morpho-biochemical, anatomical, and molecular levels. Different concentrations (0, 25, 50, and 100 mL/L) of S. polycyctum (SAR), S. platensis (SPI), and a mixture of both extracts (SS) were exposed to 100 mg/kg Cd-contaminated Pak Choi seedlings. Non-Cd-treated Pak Choi and Cd-contaminated Pak Choi without algal extracts were assigned as positive and negative controls, respectively. The results showed that the application of algal extracts increased the plant height, fresh weight (FW), and dry weight (DW) as the extract level increased. This was greatest in 100SS with 37.51% (shoot length), 68.91% (root length), 110.8% (shoot DW), and 216.13% (root DW), while an increase of 176.7% (shoot FW) and 256.9% (root FW) was seen in the 100SPI treatment. Chlorophyll a, b, carotenoid, and chlorophyll fluorescence increased significantly after the treatment with 100SS. Antioxidant enzymes CAT, APX, POD, and protein were significantly increased in 100 mL/L extracts by 28.13% (100SS), 36.40% (100SAR), 46.92% (100SS), and 153.48% (100SS), respectively. The same treatment was also identified to dominate the development of root structures such as total length, surface area, projected area, diameter, volume, tips, and fork number. The highest reduction of Cd content in the root and shoot of Pak Choi was observed in 100SS with a 53.8% and 39.88% decrease, respectively. Increasing algal extract concentration also improved the leaf histological characteristics substantially, such as stomatal size and opening, mesophyll tissues, and vascular bundles. In addition, the fold change ratio of the Rubisco gene at 100SS treatment was noticeably greater than other algal extract treatments, with a 0.99 fold change when compared with the untreated sample. This present study illustrated that Sargassum polycyctum and Spirulina platensis extracts have the potential to effectively alleviate Cd stress in Pak Choi plants, especially with the application of 100 mL/L of an algal extract mixture. These findings contribute to the development of sustainable strategies for mitigating Cd toxicity in crops.

Selective ingestion and response by Daphnia magna to environmental challenges of microplastics

Our current understandings of the effects of microplastics and nanoplastics (MNPs) on aquatic animals are predominantly based on the single types of plastic particles. In the present study, we employed the highly fluorescent MNPs that incorporated aggregation-induced emission fluorogens and investigated the selective ingestion and response of Daphnia exposed to different types of plastics at environmentally relevant concentrations simultaneously. When daphnids were exposed to a single MNP, D. magna ingested them instantly in significant amounts. However, even low concentrations of algae had a significant negative impact on the MNP uptake. Specifically, algae caused the MPs to pass through the gut faster, reduced acidification and esterase activity, and changed the distribution of MPs in the gut. In addition, we also quantified the influences of size and surface charge on the selectivity of D. magna. The daphnids selectively ingested larger and positively charged plastics. MPs effectively reduced the uptake of NP and increased its gut passage time. Aggregation of positively and negatively charged MNPs also influenced the gut distribution and increased the gut passage time. The positively charged MPs accumulated in the middle and posterior gut, while aggregation of MNPs also increased acidification and esterase activity. These findings provided fundamental knowledge on the selectivity of MNPs and the microenvironmental responses of zooplankton guts.

Rapid Correction of Turbidity and CDOM Interference on Three-Dimensional Fluorescence Spectra of Live Algae Based on Deep Learning

In natural aquatic environments, the existence of colored dissolved organic matter (CDOM), suspended particles, and colloids can cause scattering and reflection of light and even emit fluorescence itself. Such interference negatively impacts algal fluorescence, further making it unreliable to measure the algal concentration using three-dimensional excitation–emission matrix (3D-EEM) fluorescence spectroscopy. In this study, we proposed a novel algal fluorescence anti-interference network (AFAI-Net) based on a convolutional neural network. The main procedure of this model can be divided into two parts: (1) to quickly determine if there is an interference of CDOM or turbidity in the detected algal samples; (2) to correct the interfered samples and output the fluorescent components of the algae. We trained the model using the 3D-EEMs of pure algal samples (non-interfered) and mixed samples of algae and CDOM or turbidity (interfered); as a result, the well-trained model achieved a total classification accuracy of 96.82%, and the RMSE of CDOM and turbidity removal fitting effects were 0.2274 and 0.3423, respectively. Compared with the non-negative weighted least squares (NNLS) regression analysis method, using the CNN model for CDOM correction resulted in 13.11%, 0.65%, and 5.69% reductions in the average deviation rate for PD, PG, and CM, respectively. Furthermore, the spectra corrected by the model predicted algal densities that were closer to the true algal densities. This study provides a new way to remove non-algal factors that affect algal fluorescence spectra in water bodies, which is beneficial to monitoring eutrophication and red tide in aquatic systems.

The Smart Predicting of Algal Concentration for Safer Drinking Water Production with Sensor Data.

To better predict the timely variation of algal blooms and other vital factors for safer drinking water production, a new AI scanning-focusing process was investigated for improving the simulation and prediction of algae counts. With a feedforward neural network (FNN) as a base, nerve cell numbers in the hidden layer and the permutation and combination of factors, etc., were fully scanned to select the best models and highly correlated factors. All the factors involved in the modeling and selection included the date (year/month/day), sensor data (temperature, pH, conductivity, turbidity, UV254-dissolved organic matter, etc.), lab measurements (algae concentration) and calculated CO2 concentration. The new AI scanning-focusing process resulted in the best models with the most suitable key factors, which are named closed systems. In this case study, models with highest prediction performance are the (1) date-algae-temperature-pH (DATH) and (2) date-algae-temperature-CO2 (DATC) systems. After the model selection process, the best models from both DATH and DATC were used to compare the other two methods in the modeling simulation process: the simple traditional neural network method (SP), where only date and target factor as inputs, and a blind AI training process (BP), which considers all available factors as inputs. Validation results show that all methods except BP had comparable results for algae prediction and other water quality factors, such as temperature, pH and CO2, among which DATC displayed an obviously poorer performance through curve fitting with original CO2 data compared to that of SP. Therefore, DATH and SP were selected for the application test, where DATH outperformed SP due to the uncompromised performance after a long training period. Our AI scanning-focusing process and model selection showed the potential for improving water quality prediction by identifying the most suitable factors. This provides a new method to be considered in the enhancing of numerical prediction for the factors in water quality prediction and broader environment-related areas.

Effect of co-culturing bacteria and microalgae and influence of inoculum ratio during the biological treatment of tannery wastewater

This present investigation is carried out to study the effect of algal and bacterial inoculum concentrations on the removal of organic pollutants and nutrients from the tannery effluent by the combined symbiotic treatment process. The bacterial and microalgal consortia was developed in laboratory setup and mixed together to perform this study. The Influence of algae and bacteria inoculum concentrations on the removal of pollutants such as Chemical Oxygen Demand (COD) and Total Kjeldahl Nitrogen (TKN) were studied using statistical optimization through Response surface methodology. For the design of experimental set up and optimization, full factorial Central composite design was used. The profiles of pH, Dissolved Oxygen (DO) and nitrate were also monitored and studied. The inoculum concentrations of microalgae and bacteria showed significant effect on Co-culturing on COD, TKN and nitrate removals as major response. The linear effect of bacterial inoculum has positive dominant influence on COD and TKN removal efficiencies. Nitrate utilization by microalgae increases with the increase in microalgal inoculum concentration. The maximum removal efficiencies of COD and TKN with 89.9% and 80.9% were obtained at optimum bacterial and algal inoculum concentrations of 6.7 g/L and 8.0 g/L respectively. These outcomes of this study are immensely favorable for maximizing the COD and nitrogen (nutrients) removal capabilities of microalgae-bacterial consortia in tannery effluent.

Clam challenges high concentrations of algae diet environment: Growth performance, metabolism physiology, and related gene expression characteristics

Increasing coastal pollution leads to frequent algal blooms, but little is known on the effect of growth and development in organisms with increasing algal concentration. In recent years, the clam Cyclina sinensis has been an important marine economic shellfish that is widely cultivated. This study investigated the effects of different Chlorella concentrations (5 × 105 cell/L (Diet T1), 1.25 × 106 cell/L (Diet T2), 1.3 × 107 cell/L (Diet T3), 1.25 × 108 cell/L (Diet T4), and 1.5 × 109 cell/L (Diet T5)) on the growth, enzyme activities of digestive, immune, and respiratory metabolism, and hepatopancreatic transcriptome gene expression characteristic response of C. sinensis. Results showed that the shell length growth rate, shell height growth rate, and survival rate of C. sinensis significantly decreased as the Chlorella concentration reached 5 × 105 cell/L. The condition factor of C. sinensis in Diet T1 and the hepatopancreas index of C. sinensis in Diet T4 were significantly higher than those in the other groups (P < 0.05). The enzyme activities of superoxide dismutase increased significantly with the rise in concentration of Chlorella, but the highest lysozyme in the hepatopancreas of C. sinensis was observed in the Diet T1 group. The enzyme activities of acid phosphatase and amylase in Diet T3, trypsin in Diet T5, lipase and succinate dehydrogenase in Diet T4, and lactate dehydrogenase in Diet T1 of C. sinensis were significantly higher than those in the other groups (P < 0.05). These results suggest that some enzyme activities related to digestion, metabolism, and respiration are inhibited with the Chlorella concentration increased. Furthermore, transcriptome results showed that the expression levels of G6P, IGFBP, CHI3L1, FAS, MyHC, and other genes related to glucose, protein, and fatty acid metabolism of C. sinensis were significantly downregulated in the Diet T3 and Diet T5 groups. All these results suggest that Chlorella concentrations above 5 × 105 cell/L should be avoided in practice. This study provides a scientific basis for C. sinensis culture and further extends the understanding of the metabolism of bivalves with diet concentration.

Development of a green and efficient photocatalytic mesh microalgae biorefinery (PMMB) system for sustainable biomass conversion under real solar light

Microalgae biorefinery, which produces carbohydrates, proteins and lipids, is a promising solution for addressing the energy crisis and food shortages. Sunlight-activated photocatalytic reactions have emerged as green strategies for microalgae biorefinery. In this study, a photocatalytic mesh microalgae biorefinery (PMMB) system was developed for the first time, which employed durable photocatalytic meshes to destroy algal cells while maintaining smooth fluid flow and preventing blockages. High efficiency was achieved by stacking photocatalytic meshes using appropriate parameters and providing the suitable temperature and UV irradiance through solar energy control. In addition, the optimal algal concentration of 4 g·L−1, which was used in the PMMB system, maximized biorefinery efficiency. Under actual weather conditions, the PMMB system converted microalgae into carbohydrates (293 mg·L−1), proteins (121 mg·L−1) and lipids (345 mg·L−1) within 60 h, demonstrating its practical feasibility. Compared with traditional microalgae biorefinery methods, PMMB has demonstrated superior economics, practical applicability, and effectiveness. The global applicability evaluation also suggested that the PMMB system could be accessible to all countries. Therefore, the PMMB system could be a green and efficient microalgae biorefinery system to support sustainable global development.

High Levels of Microplastics in the Arctic Sea Ice Alga Melosira arctica, a Vector to Ice-Associated and Benthic Food Webs.

Plastic pollution has become ubiquitous with very high quantities detected even in ecosystems as remote as Arctic sea ice and deep-sea sediments. Ice algae growing underneath sea ice are released upon melting and can form fast-sinking aggregates. In this pilot study, we sampled and analyzed the ice algaeMelosira arcticaand ambient sea water from three locations in the Fram Strait to assess their microplastic content and potential as a temporary sink and pathway to the deep seafloor. Analysis by μ-Raman and fluorescence microscopy detected microplastics (≥2.2 μm) in all samples at concentrations ranging from 1.3 to 5.7 × 104 microplastics (MP) m-3 in ice algae and from 1.4 to 4.5 × 103 MP m-3 in sea water, indicating magnitude higher concentrations in algae. On average, 94% of the total microplastic particles were identified as 10 μm or smaller in size and comprised 16 polymer types without a clear dominance. The high concentrations of microplastics found in our pilot study suggest thatM. arctica could trap microplastics from melting ice and ambient sea water. The algae appear to be a temporary sink and could act as a key vector to food webs near the sea surface and on the deep seafloor, to which its fast-sinking aggregates could facilitate an important mechanism of transport.

Cyanidiales-Based Bioremediation of Heavy Metals.

With growing urbanization and ongoing development activities, the consumption of heavy metals has been increasing globally. Although heavy metals are vital for the survival of living beings, they can become hazardous when they surpass the permissible limit. The effect of heavy metals varies from normal to acute depending on the individual, so it is necessary to treat the heavy metals before releasing them into the environment. Various conventional treatment technologies have been used based on physical, chemical, and biological methods. However, due to technical and economic constraints and poor sustainability towards the environment, the use of these technologies has been limited. Microalgal-based heavy metal removal has been explored for the past few decades and has been seen as an effective, environment-friendly, and inexpensive method compared to conventional treatment technology. Cyanidiales that belong to red algae have the potential for remediation of heavy metals as they can withstand and tolerate extreme stresses of heat, acid salts, and heavy metals. Cyanidiales are the only photosynthetic organisms that can survive and thrive in acidic mine drainage, where heavy metal contamination is often prevalent. This review focuses on the algal species belonging to three genera of Cyanidiales: Cyanidioschyzon, Cyanidium, and Galdieria. Papers published after 2015 were considered in order to examine these species' efficiency in heavy metal removal. The result is summarized as maximum removal efficiency at the optimum experimental conditions and based on the parameters affecting the metal ion removal efficiency. This study finds that pH, initial metal concentration, initial algal biomass concentration, algal strains, and growth temperature are the major parameters that affect the heavy metal removal efficiency of Cyanidiales.

Bromeliads compete with microorganisms for nutrients in their phytotelm

Tank bromeliads impound water between their leaves, and have been successfully used as a model system to develop ecological theory. One fundamental interaction remains, however, unexplored in this system: the potential for bromeliad plants to compete with aquatic microorganisms for nutrients in their water-filled tanks. Here we conduct the first experimental test of this interaction by directly blocking bromeliads from accessing phytotelm water and quantifying change in the concentrations of dissolved inorganic nitrogen, phosphate, autotrophic algae and heterotrophic bacteria. To understand any context-dependency of responses, we crossed this manipulation with different combinations of light exposure and allochthonous resource type. We found that bromeliads reduced the concentrations of dissolved inorganic nitrogen, especially when the resource was nutrient-rich. Bromeliads also reduced the concentration of heterotrophic bacteria within their tank regardless of environmental context and algal concentrations particularly under high light, nutrient-rich resource conditions. Our results demonstrate that bromeliads can strongly impact their phytotelm by reducing the concentration of key nutrients, concomitantly reducing densities of algae under optimal growth conditions. This strong competition with algae for nutrients may explain why high abundances of algae within wild tank bromeliads are only found under specific field conditions. Bacteria may have a more commensal relationship with bromeliads, as they tend to increase bromeliad nutrition through decomposition. In conclusion, our study underlines that tank bromeliads do not only provide habitats for other species, but also interact strongly with the aquatic ecosystem that they create.

Phosphorus uptake and accumulation in Chlamydomonas reinhardtii: Influence of biomass concentration, phosphate concentration, phosphorus depletion time, and light supply

The model microalga Chlamydomonas reinhardtii was cultivated under P depleted and P repleted conditions to test the influence of dissolved P concentration (0–20 mg-P·L−1), initial algal biomass concentration (0.17–0.57 g-DW·L−1), P-depletion time (1 h – 4 days) and light supply (continuous illumination versus darkness) on phosphate uptake rate (mg-P·h−1·L−1) and the cellular P content (as %P of dry cell mass). Dissolved P concentration positively influenced cellular P content, while biomass concentration and P-depletion time did not. Biomass concentration and P-depletion time instead positively influenced P uptake rates. Light supply neither influenced cellular P content nor P assimilation. These findings evidence that depleting the cells at high initial biomass concentration could enhance P removal during wastewater treatment in waste stabilization ponds. Practically, these findings imply that high P removal from wastewater could be achieved by exposing ‘concentrated’ P-depleted biomass to P-laden influent in a relatively short contact-time reactor and subsequently harvesting and removing the resultant P-rich biomass. This stage would be followed by normal biomass growth in larger ponds which depletes the remaining P, with this biomass being harvested and returned to the contact tank for P removal.

Removal of fenamiphos, imidacloprid, and oxamyl pesticides from water by microalgal Nannochloropsis oculata biomass and their determination by validated HPLC method

The present study assessed the removal of fenamiphos, imidacloprid, and oxamyl pesticides from water using algal Nannochloropsis oculata biomass. Several factors, such as algal biomass concentration, incubation time, and pesticide concentration, were studied for their impact on pesticide removal. Analysis and quantification of pesticides by rapid HPLC have been developed and validated. The optimum conditions were obtained at 15 min, 50 mg/L of pesticide concentration, and 4,500 mg/L of the algal biomass with 92.24% and 90.43% removal for fenamiphos and imidacloprid, respectively. While optimum parameters of 10 min incubation, 250 mg/L of pesticide concentration, and 2,750 mg/L of the algal biomass exhibited 67.34% removal for oxamyl. N. oculata, marine microalgae, successively removed different concentrations of the tested pesticides from water, and the algal biomass showed a potential reduction of pesticides in polluted water samples.

Modeling and mitigating fouling of microfiltration membranes for microalgae dewatering

Dewatering is energy-intensive for microalgae production, and microfiltration (MF) membranes are attractive because of their high energy efficiency. However, the membranes suffer from fouling by organic matter in the algae solutions, and there needs fundamental understanding of membrane fouling with actual algae solutions. Herein we thoroughly evaluate the dewatering performance of commercial polyethersulfone (PES) MF membranes using an integrated experiment and modeling approach. The effect of algae concentration, testing time, feed flow rate, and chemical cleaning on the dewatering performance and fouling-layer morphology are investigated. The fouling behavior can be successfully described using the Hermia and gel layer models with a gel concentration of 48 g/L for algae solutions. Furthermore, the PES membrane surface was grafted with hydrophilic zwitterions, which mitigated the fouling. For example, when challenged with 10 g/L algae solution in dead-end cells, the pristine and modified membrane exhibit water permeance of 80 and 170 L m−2 h−1 bar−1, respectively. Three cycles of dewatering and NaOH cleaning were performed to demonstrate the promise of the MF membranes for practical dewatering application.

A Rapid Assessment of Microalgal Concentration Using Turbidity Measurement for Shellfish Hatchery Seed Production

The goal of this study was to develop a rapid assessment of microalgal concentration using a turbidity meter to serve commercial shellfish hatcheries for feeding shellfish larvae and broodstock. We used four commonly used algal species, Tetraselmis suecica, Isochrysis galbana, Chaetoceros calcitrans, and Chaetoceros gracilis, generating serial dilutions of each and measuring cell concentrations and turbidity of each sample. We identified linear correlations between cell concentration and turbidity and established standard equations between cell concentration and turbidity for each species. We sampled and quantified algae from a shellfish hatchery using these equations and compared hemocytometer counts. No differences were found (P ≥ 0.174), indicating the accuracy of the equations. We expect that this method can provide a quick, accurate, easy method for shellfish hatcheries to quantify algal concentration and avoid either over- or underfeeding larvae and broodstock.

Experimental additions of allochthonous dissolved organic matter reveal multiple trophic pathways to stimulate planktonic food webs

Abstract There is still considerable debate as to whether the allochthonous (terrestrial) dissolved organic matter (DOM) mobilised during large flow events plays an important role in supporting secondary production in riverine food webs. Understanding how food webs respond to large pulses of terrestrial DOM (tDOM) is important for conceptualising the relative importance of energy sources supporting food webs. A mesocosm experiment (1,000 L) using three concentrations of leachate (1, 4, 8 mg C/L and a control) made from floodplain DOM was run for 34 days in a dam filled with water from Gunbower Creek in Northern Victoria, Australia. Nutrients, phytoplankton, zooplankton and stable isotope (δ13C signatures) data were collected to examine how floodplain nutrients affected growth and community structure within the lower food web typical of an Australian lowland river. All leachate additions led to very high concentrations of zooplankton and mixotrophic algae compared to the control. Mixotrophs dominated the algal biovolume of all leachate additions until Day (D)20 and appeared to drive changes in δ13C signatures of particulate organic matter (POM) which were significantly related to changes in zooplankton δ13C signatures. tDOM additions did not significantly suppress obligate autotroph growth which also appeared important as a food source, as reflected in the δ13C signatures of zooplankton and POM after D10. These results show the ability of phytoplankton and zooplankton communities in lowland rivers to respond quickly to changes in resource availability and quality. Mixotrophs appeared to provide an important trophic link between allochthonous carbon and primary consumers, and increased complimentarily to autotrophic production. This resulted in large net increases to phytoplankton biovolume and potentially played a significant role in driving changes in zooplankton growth. We suggest that allochthonous DOM may be highly bioavailable and support production through several different trophic pathways, offering a large boost to production via both autotrophy and heterotrophy. Furthermore, we contend that mixotrophy may be an important pathway for allochthonous organic matter to enter riverine food webs and support secondary production.

Utilization of Algae for the Green Synthesis of Silver Nanoparticles and Their Applications

This study aims to provide an overview of silver nanoparticles and their applications. Among the many applications for nanoparticles, nanoparticle synthesis is a particularly appealing research issue. Silver nanoparticle synthesis is an emerging field due to its wide applications in different fields. Silver nanoparticles are manufactured using a variety of processes, including physical, chemical, and biological approaches. Physical and chemical procedures are both expensive and dangerous. As a result, biological procedure is considered cleanest and safest as no toxic chemicals are used in this. The biological procedure includes the use of microbes, algae, and plant extract for the nanoparticle synthesis. Algal-mediated biosynthesis of silver nanoparticles is easy, nontoxic, environmentally friendly, and requires less time. Algae have the high capacity to take metals and reduce metal ions apart from their wider distribution and abundant availability. Algae can help in mass scale production of nanoparticles at a low cost. Several physical factors such as algal extract concentration, the effect of pH, time, and temperature controlled the formation and stabilization of silver nanoparticles. AgNPs are important because of their antimicrobial, antifungal, anticancer, and wound-healing activities. Algal-synthesized AgNPs are increasingly being used in biomedicine. Targeted drug delivery techniques employ silver nanoparticles. The benefit of wound healing by silver nanoparticles includes cytokine release, which inhibits mast cell infiltration and so acts as an anti-inflammatory agent. Nanoparticles maintain electrical and optical features that can be applied to biosensors. The high-quality production of algae-mediated silver nanoparticles will enhance the properties and usefulness of AgNPs for commercial use. Silver nanoparticles boost membrane permeability and generate a hole in <i>E. coli</i> bacteria's cell wall. This review highlighted the wide applications of silver nanoparticles in the field of medicines, therapeutics, cosmetics, biosensors, etc. and their different methods of synthesis.