This paper examines the potential of algae biofuel production in conjunction with wastewater treatment. Current technology for algal wastewater treatment uses facultative ponds, however, these ponds have low productivity (∼10 tonnes/ha.y), are not amenable to cultivating single algal species, require chemical flocculation or other expensive processes for algal harvest, and do not provide consistent nutrient removal. Shallow, paddlewheel-mixed high rate algal ponds (HRAPs) have much higher productivities (∼30 tonnes/ha.y) and promote bioflocculation settling which may provide low-cost algal harvest. Moreover, HRAP algae are carbon-limited and daytime addition of CO2 has, under suitable climatic conditions, the potential to double production (to ∼60 tonnes/ha.y), improve bioflocculation algal harvest, and enhance wastewater nutrient removal. Algae biofuels (e.g. biogas, ethanol, biodiesel and crude bio-oil), could be produced from the algae harvested from wastewater HRAPs, The wastewater treatment function would cover the capital and operation costs of algal production, with biofuel and recovered nutrient fertilizer being by-products. Greenhouse gas abatement results from both the production of the biofuels and the savings in energy consumption compared to electromechanical treatment processes. However, to achieve these benefits, further research is required, particularly the large-scale demonstration of wastewater treatment HRAP algal production and harvest.

E. coli O157:H7 is a foodborne pathogen that constitutes a global threat to human health. However, the quantification of this pathogen in food and environmental samples may be problematic at the low cell numbers commonly encountered in environmental samples. In this study, we used recombinase polymerase amplification (RPA) for the detection of E. coli O157:H7, real-time quantitative PCR (qPCR) for quantification, and droplet digital PCR (ddPCR) for absolute and accurate quantification of E. coli O157:H7 from spiked and environmental samples. Primer and probe sets were used for the detection of stx1 and stx2 using RPA. Genes encoding for stx1, stx2, eae, and rfbE were used to quantify E. coli O157:H7 in the water samples. Furthermore, duplex ddPCR assays were used to quantify the pathogens in these samples. Duplex assay set 1 used stx1 and rfbE genes, while assay set 2 used stx2 and eae genes. Droplet digital PCR was used for the absolute quantification of E. coli O15:H7 in comparison with qPCR for the spiked and environmental samples. The RPA results were compared to those from qPCR and ddPCR in order to assess the efficiency of the RPA compared with the PCR methods. The assays were further applied to the dairy lagoon effluent (DLE) and the high rate algae pond (HRAP) effluent, which were fed with diluted DLE. The RPA detected was <10 CFU/mL, while ddPCR showed quantification from 1 to 10⁴ CFU/mL with a high reproducibility. In addition, quantification by qPCR was from 10³ to 10⁷ CFU/mL of the wastewater samples. Therefore, the RPA assay has potential as a point of care tool for the detection of E. coli O157:H7 from different environmental sources, followed by quantification of the target concentrations.

This study used pilot-scale high-rate algae ponds to assess algal–bacteria biomass productivity and wastewater nutrient removal as well as the impact of mechanical and hydrothermal pretreatments on biomass disintegration, methane production kinetics, and anaerobic digestion (AD) energy balance. Mechanical pretreatment had a minor effect on biomass disintegration and methane production. By contrast, hydrothermal pretreatment significantly reduced particle size and increased the solubilized organic matter content by 3.5 times. The methane yield and production rate increased by 20–55% and 20–85%, respectively, with the highest values achieved after pretreatment at 121 °C for 60 min. While the 1st-order and pseudo-1st-order reaction equation models fitted methane production from untreated biomass best (R² > 0.993), the modified Gompertz sigmoidal-type model provided a superior fit for hydrothermally pretreated algae (R² ≥ 0.99). The AD energy balance revealed that hydrothermal pretreatment improved the total energy output by 25–40%, with the highest values for volume-specific and mass-specific total energy outputs reaching 0.23 kW per digester m³ and 2.3 MW per ton of biomass volatile solids. Additionally, net energy recovery (energy output per biomass HHV) increased from 20% for untreated algae to 32–34% for hydrothermally pretreated algae, resulting in net energy ratio and net energy efficiency of 2.14 and 68%, respectively.

Our study objective was to determine the apparent metabolizable energy (AME) and apparent ileal amino acid digestibility (AIAAD) of spirulina fed to broiler chickens and laying hens using the difference method. In both experiments, birds were either fed corn-soybean meal basal diets, containing no spirulina and formulated to provide the nutrient requirements of either broilers or layers, or fed test diets consisting of 25% spirulina and 75% of the appropriate basal diet. Titanium dioxide was added to all diets as an indigestible marker. The diets were fed to 10 replicate cages/treatment of broilers and 15 replicate cages/treatment of laying hens. The AME of spirulina for broilers was significantly lower (p < 0.05) (2368 ± 104 kcal/kg, as fed) than for laying hens (3144 ± 173 kcal/kg, as fed), suggesting bird type and age may influence energy utilization. The AIAAD of spirulina fed to broiler chickens did not differ from that of laying hens (p > 0.05), except for valine, alanine, and glycine, which were all significantly higher in laying hens (p < 0.05). Overall, the AIAAD for nonessential amino acids averaged 81.1%, with no significant difference between essential and nonessential amino acids. Differences in spirulina nutrient content cited in the literature support further research to determine the optimal inclusion of this alternative ingredient in broiler and layer diets.