Potential of Synechococcus elongatus UTEX 2973 as a feedstock for sugar production during mixed aquaculture and swine wastewater bioremediation.

The demand for protein is increasing with an expanding world population and is influencing the rapid growth of fish and animal agriculture. These sectors are becoming a significant source of water pollution and need to develop environmentally sustainable techniques that are cost-effective, ideally with potential for downstream value-added production. This study investigated the potential of one of the fastest-growing cyanobacterial species, Synechococcus elongatus UTEX 2973, for bioremediation of mixed wastewater (combination of sturgeon and swine wastewater). Three different mixing ratios (25:75, 50:50, and 75:25 sturgeon:swine) were compared to find a suitable combination for the growth of S. elongatus as well as carbohydrate accumulation in biomass. The final biomass production was found to be 0.65 ± 0.03 g Dry cell Weight (DW)/L for 75%-25 %, 0.90 ± 0.004 g DW/L for 50%-50 %, and 0.71 ± 0.04 g DW/L for 25%-75 % sturgeon-swine wastewater combination. Cyanobacteria cultivated in 50%-50 % sturgeon-swine wastewater also accumulated 70 % total carbohydrate of DW, whereas 75%-25 % sturgeon-swine and 25%-75 % sturgeon-swine accumulated 53 % and 45 %, respectively. Subsequently, the S. elongatus cells were grown in a separate batch of 50%-50 % sturgeon-swine wastewater and compared with cells grown in BG11 synthetic growth media. Cultivation in BG11 resulted in higher biomass production but lower carbohydrate accumulation than 50%-50 % mixed wastewater. Final biomass production was 0.85 ± 0.08 g DW/L for BG11 and 0.65 ± 0.04 g DW/L for 50%-50 % sturgeon-swine wastewater. Total carbohydrate accumulated was 75 % and 64 % of DW for 50%-50 % sturgeon-swine mixed wastewater and BG11 growth media, respectively, where glycogen was the main carbohydrate component (90 %). The nutrient removal efficiencies of S. elongatus were 67.15 % for orthophosphate, 93.39 % for nitrate-nitrite, and 97.98 % for ammonia. This study suggested that S. elongatus is a promising candidate for enabling simultaneous bioremediation of mixed wastewater and the production of value-added biochemicals.

Depuration of live oysters to reduce Vibrio parahaemolyticus and Vibrio vulnificus: A review of ecology and processing parameters.

Consumption of raw oysters, whether wild-caught or aquacultured, may increase health risks for humans. Vibrio vulnificus and Vibrio parahaemolyticus are two potentially pathogenic bacteria that can be concentrated in oysters during filter feeding. As Vibrio abundance increases in coastal waters worldwide, ingesting raw oysters contaminated with V. vulnificus and V. parahaemolyticus can possibly result in human illness and death in susceptible individuals. Depuration is a postharvest processing method that maintains oyster viability while they filter clean salt water that either continuously flows through a holding tank or is recirculated and replenished periodically. This process can reduce endogenous bacteria, including coliforms, thus providing a safer, live oyster product for human consumption; however, depuration of Vibrios has presented challenges. When considering the difficulty of removing endogenous Vibrios in oysters, a more standardized framework of effective depuration parameters is needed. Understanding Vibrio ecology and its relation to certain depuration parameters could help optimize the process for the reduction of Vibrio. In the past, researchers have manipulated key depuration parameters like depuration processing time, water salinity, water temperature, and water flow rate and explored the use of processing additives to enhance disinfection in oysters. In summation, depuration processing from 4 to 6 days, low temperature, high salinity, and flowing water effectively reduced V. vulnificus and V. parahaemolyticus in live oysters. This review aims to emphasize trends among the results of these past works and provide suggestions for future oyster depuration studies.

Development of a suitability assessment model for the cultivation of intertidal macroalgae in the United States.

The focus of this novel study was to determine the comparative suitability of intertidal macroalgae production along the coast of the contiguous United States and determine the optimal locations to consider commercial cultivation using geographic information systems (GIS) software. Intertidal macroalgae cultivation represents an immense opportunity in the United States. The market demand for macroalgae has been growing and is expected to continue with the discovery of new uses. Currently, the coastal waters of the United States are extremely underutilized, particularly for macroalgae production. This study considered economic and environmental factors at a national scale, finally assessing the viability in a representative body of water with in-situ water sampling. The results of this study suggest that intertidal macroalgae cultivation is most ideally suited for the southeastern United States, primarily due to lower costs of production and more hospitable coastlines. Based on a limited water quality samples, it is feasible for macroalgae cultivation. However, due to the informational deficits, as acknowledged in this study, more work is required to refine and enhance the assessment model. This paper identifies these gaps and lists recommendations to overcome these knowledge gaps.

Physicochemical data of p-cresol, butyric acid, and ammonia.

There is a renewed interest in treating odorous contaminants such as butyric acid, p-cresol, and ammonia that are emitted from animal farming operations. However, developing newer treatment technologies require quantitative information regarding the properties of the target pollutants. Therefore, in this communication, baseline data related to physicochemical and thermodynamic properties of butyric acid, p-cresol, and ammonia were predicted using computational chemistry. Density functional theory was employed via B3LYP functional coupled with polarized 6-31G (d) basis set without any solvent effects using Gaussian 16W and GaussView6. The predicted baseline properties collected here are expected to be useful to scientists and engineers working in environmental mitigation technologies in developing treatment processes and make the animal agricultural industry environmental friendly and sustainable.

The effect of salinity and alkalinity on growth and the accumulation of copper and zinc in the Chlorophyta Ulva fasciata.

Copper and zinc accumulation in macroalgae is a complex issue. While these metals exist as micronutrients and can serve to add nutritional value to the macroalgae when consumed by both plants and animals, elevated levels of the metals can reduce growth or even kill the algae. Many water parameters can influence the toxicity of the metals, though past studies have rarely isolated individual water parameters. This study aimed to independently determine the effects that salinity and alkalinity have on the growth and accumulation of these two metals on the macroalgae Ulva fasciata, distinguishing the effects of salinity and alkalinity as whole parameters from the collective effects of the water different constituents. The effect of salinity was determined using sodium chloride additions rather than seawater dilution, as performed in past studies, while alkalinity was tested using sodium bicarbonate additions to artificial seawater. The results of the study reinforce previous findings that copper is very toxic to macroalgae, even at low concentrations (50 µg L-1) though the effects of zinc remain inconclusive at 50 µg L-1, since the experiment was conducted over only a two-week trial period. The research suggests that salinity and alkalinity have no significant effect on the toxicity of copper to the growth of the macroalgae, but alkalinity significantly reduced copper and increased zinc accumulation in U. fasciata. The results of this study warrant further research in the field to investigate which other components of seawater and macroalgae reduce metal toxicity in the macroalgae. Additionally, these findings suggest the need for further refinement of toxicity models when adapted to macroalgae.

A comparison of image processing techniques for bird recognition.

Bird predation is one of the major concerns for fish culture in open ponds. A novel method for dispersing birds is the use of autonomous vehicles. Image recognition software can improve their efficiency. Several image processing techniques for recognition of birds have been tested. A series of morphological operations were implemented. We divided images into 3 types, Type 1, Type 2, and Type 3, based on the level of difficulty of recognizing birds. Type 1 images were clear; Type 2 images were medium clear, and Type 3 images were unclear. Local thresholding has been implemented using HSV (Hue, Saturation, and Value), GRAY, and RGB (Red, Green, and Blue) color models on all three sections of images and results were tabulated. Template matching using normal correlation and artificial neural networks (ANN) are the other methods that have been developed in this study in addition to image morphology. Template matching produced satisfactory results irrespective of the difficulty level of images, but artificial neural networks produced accuracies of 100, 60, and 50% on Type 1, Type 2, and Type 3 images, respectively. Correct classification rate can be increased by further training. Future research will focus on testing the recognition algorithms in natural or aquacultural settings on autonomous boats. Applications of such techniques to industrial, agricultural, or related areas are additional future possibilities.