A comparison of methods for the non-destructive fresh weight determination of filamentous algae for growth rate analysis and dry weight estimation

Integrated biotechnology to mitigate green tides

Around the world, green tides are happening with increasing frequency because of the dual effects of increasingly intense human activity and climate change; this leads to significant impacts on marine ecology and economies. In the last decade, the world's largest green tide, which is formed by Ulva/Enteromorpha porifera, has become a recurrent phenomenon every year in the southern Yellow Sea (China), and it has been getting worse. To alleviate the impacts of such green tide outbreaks, multiple measures need to be developed. Among these approaches, biotechnology plays important roles in revealing the outbreak mechanism (e.g., molecular identification technology for algal genotypes), controlling and preventing outbreaks at the origin sites (e.g., technology to inhibit propagation), and utilizing valuable algal biomass. This review focuses on the various previously used biotechnological approaches that may be applicable to worldwide seaweed blooms that result from global climate change and environmental degradation.

Chlorophyll-a Pigment Measurement of Spirulina in Algal Growth Monitoring Using Portable Pulsed LED Fluorescence Lidar System

Chlorophyll-a measurement is important in algal growth and water quality monitoring in natural waters. A portable pulsed LED fluorescence lidar system based on the preliminary algal organic matter and pigments excitation–emission matrix (EEM) of commercialized AZTEC Spirulina powder at varying concentrations was developed. Fluorescence peaks from EEMs showed increasing intensity as the Spirulina concentration increases. Using this information, an LED fluorescence lidar with a wavelength of 385 nm, pulse width of 10 ns, and repetition frequency of 500 kHz was constructed for chlorophyll detection at 680 nm. Turbidity measurements were also conducted at 700 nm emission wavelength at the same excitation wavelength. Range-resolved fluorescence lidar signals from the portable pulsed LED fluorescence lidar system are highly correlated with the standard methods such as optical density at 680 nm (R2 = 0.87), EEM fluorescence chlorophyll-a pigment at 680 nm (R2 = 0.89), and corrected chlorophyll-a concentration (R2 =0.92). The F680/F700 lidar ratio was measured to provide a linear relationship of chlorophyll-a and turbidity in waters. The F680/F700 measurement showed strong correlations with Spirulina concentration (R2 = 0.94), absorbance at 680 nm (R2 = 0.84), EEM chlorophyll-a pigment at 680 nm (R2 = 0.83), and corrected chlorophyll-a concentration (R2 = 0.86). Results revealed that this new technique of chlorophyll-a measurement can be used as an alternative to other standard methods in algal growth monitoring.

Macroalgal release of dissolved organic carbon in coral reef and its interaction with the bacteria associated with the coral Porites lutea

Macroalgae supersede corals in the reefs worldwide, converting the coral-dominant systems into algal-dominant ones. Dissolved organic carbon (DOC) released by macroalgae play a prominent role in degrading the coral reefs by stimulating the bacterial growth and metabolism. However, the long-term remineralization of macroalgal DOC and their contribution to the carbon pool are least studied. In this study, we quantified the DOC released by five species of macroalgae that affected live corals through their physical contact and their subsequent remineralization for 100 days by coral mucus bacteria. Also, we analyzed the changes in bacterial community structure after 30 days of exposure to the macroalgal DOC. All the macroalgae released a significant amount of DOC ranging from 2.2 ± 0.17 to 8.1 ± 0.36 μmol C g^-1 h^-1 (mean ± SD). After 100 days, between 9.2 and 30.9% of the macroalgal DOC remained recalcitrant to bacterial remineralization. There was no apparent change in the dominant bacterial groups exposed to the DOC released by the green macroalgae Caulerpa racemosa and Halimeda sp. In comparison, the Proteobacteria group decreased with a prominent increase in the Firmicutes, Planctomycetes, and Bacteroidetes group in the samples exposed to DOC released by the brown macroalgae Turbinaria ornata, Sargassum tenerrimum, and Padina gymnospora. These inclusive data suggest that the DOC released by different species of macroalgae differed on their lability to microbial mineralization and highlight the comparable patterns in microbial responses to macroalgal exudates across different species.

Removal of metals from aqueous solutions using dried Cladophora parriaudii of varying biochemical composition

Macroalgal biosorption has shown promise for the removal of metal ions from wastewaters, whose presence can pose a threat to the aquatic environment. There is a wealth of literature published on macroalgal biosorption, the common thread being that the biosorbent material was collected from the field, under undefined conditions. These studies offer little insight into the impact of prior cultivation or biomass production practices upon the biosorbent material, its adsorptive physico-chemical properties and its subsequent capacity for metal removal. The present study sought to investigate the influence of changes in macroalgal cultivation, specifically nutrient regime, upon biomass properties and the resultant adsorption performance. The macroalga Cladophora parriaudii was cultivated under six different nutrient regimes; 2:1 and 12:1 N:P molar ratios, with nitrogen supplied either as ammonium (NH₄⁺), nitrate (NO₃^-), or urea (CO(NH₂)₂). These nutrient regimes were designed to produce biomass of varying biochemical and cell surface profiles. After cultivation, the biomass was rinsed, dried, biochemically analysed and then used for the removal of four individual metals from solution. Metal removal varied considerably between treatments and across initial metal concentrations, with removal values of 46-85%, 9-80%, 8-71%, and 49-94% achieved for Al, Cu, Mn, and Pb, respectively, with initial metal concentrations varying between 0 and 150 mg L^-1. The observed variation in metal removal can only be attributed to differences in biochemistry and cell surface properties of the biosorbent induced by nutrient regime, as all other variables were constant. This study demonstrates that prior cultivation conditions influence the biochemistry of a biosorbent material, namely macroalgae Cladophora parriaudii, which has an impact upon metal removal. This aspect should be given due consideration for future biosorption research and when reviewing already published literature.

Elevated pCO2 reinforces preference among intertidal algae in both a specialist and generalist herbivore

Ocean acidification (OA) can induce changes in marine organisms and species interactions. We examined OA effects on intertidal macroalgal growth, palatability, and consumption by a specialist crab (Pugettia producta) and a generalist snail (Tegula funebralis) herbivore. Moderate increases in pCO2 increased algal growth in most species, but effects of pCO2 on C:N and phenolic content varied by species. Elevated pCO2 had no effect on algal acceptability to herbivores, but did affect their preference ranks. Under elevated pCO2, electivity for a preferred kelp (Egregia menziesii) and preference rankings among algal species strengthened for both P. producta and T. funebralis, attributable to resilience of E. menziesii in elevated pCO2 and to changes in palatability among less-preferred species. Preferred algae may therefore grow more under moderate pCO2 increases in the future, but their appeal to herbivores may be strengthened by associated shifts in nutritional quality and defensive compounds in other species.

Estimation of the Chlorophyll-A Concentration of Algae Species Using Electrical Impedance Spectroscopy

Algae are a significant component of a biological monitoring program in an aquatic ecosystem. They are ideally suited for water quality assessments because of their nutrient requirements, rapid reproduction rate, and very short life cycle. Algae composition and temporal variation in abundances are important in determining the trophic level of lakes, and those can be estimated by the Chlorophyll-a (Chl-a) concentration of the species. In this work, a non-destructive method was employed to estimate the Chlorophyll-a concentration of multiple algae species using electrical impedance spectroscopy (EIS). The proposed EIS method is rapid, cheaper, and suitable for in situ measurements compared with the other available non-destructive methods, such as spectrophotometry and hyperspectral or multispectral imaging. The electrical impedances in different frequencies ranging from 1 to 100 kHz were observed using an impedance converter system. Significant observations were identified within 3.5 kHz for multiple algae species and therefore reported in the results. A positive correlation was found between the Chlorophyll-a and the measured impedance of algae species at different frequencies. Later, EIS models were developed for the species in 1–3.5 kHz. A correlation of 90% was found by employing a least squares method and multiple linear regression. The corresponding coefficients of determination were obtained as 0.9, 0.885, and 0.915, respectively for 49 samples of Spirulina, 41 samples of Chlorella, and 26 samples of mixed algae species. The models were later validated using a new and separate set of samples of algae species.

Investigating algae for CO2 capture and accumulation and simultaneous production of biomass for biodiesel production

Carbon capture and sequestration technologies are used to reduce carbon emissions. Membranes, solvents, and adsorbents are the three major methods of CO₂ capture. One of the promising methods is the use of algae to absorb CO₂ from flue gases and convert it into biomass. Algae have great potential as renewable fuel sources and CO₂ capture using photosynthesis for carbon fixation has also attracted much attention. This paper presents an extensive and in-depth report on the utilization of algae for carbon capture and accumulation. This is done in conjunction with cultivating the algae for the production of biomass for biodiesel production. Different systems are investigated for algae cultivation as well as carbon capture to effectively mitigate carbon emissions. The performance and productivity of these biosystems depend on various conditions including algae type, light sources, nutrients, pH, temperature, and mass transfer. Macroalgae and microalgae species were explored to determine their suitability for carbon capture and sequestration, along with the production of biodiesel. The steps for producing biodiesel were comprehensively reviewed, which are harvesting, dehydrating, oil extraction, oil refining, and transesterification. This technology combines active carbon capture with the potential of biodiesel production.

A Practical Electronic Health Record-Based Dry Weight Supervision Model for Hemodialysis Patients

Objective: Dry Weight (DW) is a typical hemodialysis (HD) prescription for End-Stage Renal Disease (ESRD) patients. However, an accurate DW assessment is difficult due to the complication of body components and individual variations. Our objective is to model a clinically practicable DW estimator. Method: We proposed a time series-based regression method to evaluate the weight fluctuation of HD patients according to Electronic Health Record (EHR). A total of 34 patients with 5100 HD sessions data were selected and partitioned into three groups; in HD-stabilized, HD-intolerant, and near-death. Each group’s most recent 150 HD sessions data were adopted to evaluate the proposed model. Results: Within a 0.5 kg absolute error margin, our model achieved 95.44%, 91.95%, and 83.12% post-dialysis weight prediction accuracies for the HD-stabilized, HD-intolerant, and near-death groups, respectively. Within a 1%relative error margin, the proposed method achieved 97.99%, 95.36%, and 66.38% accuracies. For HD-stabilized patients, the Mean Absolute Error (MAE) of the proposed method was 0.17 kg ± 0.04 kg. In the model comparison experiment, the performance test showed that the quality of the proposed model was superior to those of the state-of-the-art models. Conclusion: The outcome of this research indicates that the proposed model could potentially automate the clinical weight management for HD patients. Clinical Impact: This work can aid physicians to monitor and estimate DW. It can also be a health risk indicator for HD patients.