Artificial pond water
Ontology highlight
ABSTRACT:
PROVIDER: PRJNA699411 | ENA |
REPOSITORIES: ENA
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Project description:Aquaculture has become a primary method to produce various aquatic products, and intensive aquaculture technologies have become commercially important. To improve the efficiency of intensive aquaculture per unit area without reducing the growth rate of cultured fish, the present study explored the potential of artificial substrata in ponds. Our results showed that the concentrations of total nitrogen (TN) and total phosphorous (TP) in the ponds with different stocking densities of grass carp were lower than those in the control group in most cases. Further, the feed conversion rate of grass carp was significantly reduced by introducing these artificial substrata, and the culture density could be significantly increased without reducing the growth rates of these fish. Artificial substrata also significantly enriched specific bacteria and changed the structure of the microbiota in pond water. The relative abundance of Proteobacteria was significantly increased, and bacteria closely related to N and P cycles, such as Hyphomicrobium, Chitinimonas, Legionella, Shewanella, Roseiflexus, and Planktothrix were significantly enhanced. These results showed that the artificial substratum could increase TN and TP removal in aquaculture pond water by enriching N and P cycle-related bacteria, thus significantly increasing the specific growth rate of grass carp and significantly reducing their feed conversion rate. Finally, the stocking density of grass carp and the yield per unit area of pond could be increased without reducing the growth rate.
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Project description:Pseudomonas aeruginosa is a common bacterium in the terminal plumbing system of buildings and it is from this niche that a substantial fraction of infections are acquired. To better understand P. aeruginosa biology in this environment, we examined the transcriptomes in tap water and pond water.
2017-10-24 | GSE104819 | GEO
Project description:Guangdong aquaculture pond water samples Targeted loci environmental
| PRJNA357316 | ENA
Project description:The abundance and diversity of bacteria in two types of ponds were investigated by quantitative PCR and Illumina MiSeq sequencing. The results revealed that the abundance of bacterial 16S rRNA genes in D ponds (with grass carp fed sudan grass) was significantly lower than that in E ponds (with grass carp fed commercial feed). The microbial communities were dominated by Proteobacteria, Cyanobacteria, Bacteroidetes, and Actinobacteria in both E and D ponds, while the abundance of some genera was significantly different between the two types of ponds. Specifically, some potential pathogens such as Acinetobacter and Aeromonas were found to be significantly decreased, while some probiotics such as Comamonadaceae unclassified and Bacillales unclassified were significantly increased in D ponds. In addition, water quality of D ponds was better than that of E ponds. Temperature, dissolved oxygen and nutrients had significant influence on bacterial communities. The differences in bacterial community compositions between the two types of ponds could be partially explained by the different water conditions.
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Project description:Aerolysin is a hemolytic toxin encoded by aerolysin gene (1482 bp) that plays a key role in the pathogenesis of Aeromonas hydrophila infection in fish. New speciesspecific primers were designed to amplify 326 bp conserved region of aerolysin gene for A. hydrophila. Twenty-five isolates of A. hydrophila recovered from fish and pond water were studied for detection of aerolysin gene. Aerolysin gene was detected in 85% of the isolates during the study. The designed primers were highly specific and showed no cross reactivity with Escherichia coli, Aeromonas veronii, Vibrio cholerae, Flavobacterium spp., Chyseobacterium spp. and Staphylococcus aureus. The sensitivity limit of primers for detection of aerolysin gene in the genomic DNA of A. hydrophila was 5 pg.
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Project description:Artificial water channels are synthetic molecules that aim to mimic the structural and functional features of biological water channels (aquaporins). Here we report on a cluster-forming organic nanoarchitecture, peptide-appended hybrid[4]arene (PAH[4]), as a new class of artificial water channels. Fluorescence experiments and simulations demonstrated that PAH[4]s can form, through lateral diffusion, clusters in lipid membranes that provide synergistic membrane-spanning paths for a rapid and selective water permeation through water-wire networks. Quantitative transport studies revealed that PAH[4]s can transport >109 water molecules per second per molecule, which is comparable to aquaporin water channels. The performance of these channels exceeds the upper bound limit of current desalination membranes by a factor of ~104, as illustrated by the water/NaCl permeability-selectivity trade-off curve. PAH[4]'s unique properties of a high water/solute permselectivity via cooperative water-wire formation could usher in an alternative design paradigm for permeable membrane materials in separations, energy production and barrier applications.
| S-EPMC7008941 | biostudies-literature
Project description:Aquaculture, which is the breeding of fishes in artificial ponds, seems to be gaining popularity among urban and sub-urban dwellers in Sub-Saharan Africa and Asia. Tenant aquaculture enables individuals irrespective of their profession to grow fishes locally in a little space. However, there are challenges facing aquaculture such as the availability of water, how to monitor and manage water quality, and more seriously, the problem of absence of dataset with which the farmer can use as a guide for fish breeding. Aquaponics is a system that combines conventional aquaculture with hydroponics (the method of growing plants in water i.e. soilless farming of crops). It uses these two technologies in a symbiotic combination in which the plant uses the waste from the fish as food while at the same time filtering the water for immediate re-use by the fish. This helps to solve the problem of frequent change of water. An Internet of Things (IoT) system consisting of an ESP-32 microcontroller which controls water quality sensors in aquaponics fish ponds was designed and developed for automatic data collection. The sensors include temperature, pH, dissolved oxygen, turbidity, ammonia and nitrate sensors. The IoT system reads water quality data and uploads the same to the cloud in real time. The dataset is visualized in the cloud and downloaded for the purposes of data analytics and decision-making. We present the dataset in this paper. The dataset will be very useful to the agriculture, aquaculture, data science and machine learning communities. The insights such dataset will provide when subjected to machine learning and data analytics will be very useful to fish farmers, informing them when to change the pond water, what stocking density to apply, provide knowledge about feed conversion ratios, and in predict the growth rate and patterns of their fishes.
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