Review on significant parameters in water quality and the related artificial intelligent applications

Shamsudin, S. N.; Azman, Ahmad Aftas; Ismail, Nurlaila; Rahiman, Mohd Hezri Fazalul; Ahmad, Ausaf; Taib, Mohd Nasir

doi:10.1109/icsgrc.2015.7412485

Cited by 4 publications

(2 citation statements)

References 32 publications

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“…Water serves as a medium for metabolic processes and a habitat for aquatic life, which physical, chemical and biological factors can influence. Changes in water quality metrics reflect changes in the aquatic ecosystem and have an impact on the interaction of aquatic biota in the aquatic environment (Shamsudin et al, 2015;Irfan and Alatawi, 2019). Shrimp aquaculture is a potential global market gaining attention owing to increased demand and greatly contributing to economic growth.…”

Section: Discussionmentioning

confidence: 99%

Characterization of bacterial communities in prebiotics and probiotics treated shrimp farms from Kuantan

Siew, S. W.,

Kosnin, I. N.,

Zulkifli, N. F.

et al. 2023

MJM

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Aims: Prebiotics and probiotics profoundly enhance water quality and shrimp development to tackle infectious disease in shrimp farming. This study evaluated the impact of prebiotics and probiotics treatments in water by assessing the physicochemical properties and bacterial communities in local shrimp ponds. Methodology and results: Water was collected from shrimp pond 1 (SP1), treated with prebiotics and probiotics, and shrimp pond 2 (SP2), treated with only prebiotics. The physicochemical parameters of water from two shrimp ponds were measured, including pH, dissolved oxygen (DO), ammonia concentration and temperature. The total environmental DNA (eDNA) was extracted from the water samples and sequenced using amplicon sequencing targeting the full length of the 16S rRNA gene region via the Oxford Nanopore Technology Flongle. The water quality analysis indicated that SP1 had better water quality than SP2 for shrimp aquaculture. The dominant phyla in both shrimp ponds were Proteobacteria and Bacteroidota. SP1 samples had unique microbiota at the phylum level, including Bdellovibrionota, Firmicutes A, Patescibacteria and unclassified Rhizobiales, Saprospiraceae, Vulcanococcus and HIMB114 at the genus level. The alpha-and beta-diversity showed insignificant differences in microbiota composition between SP1 and SP2 (p-value>0.05). Conclusion, significance and impact of study:Research findings demonstrated that the probiotic-treated shrimp pond (SP1) had better water quality and more diverse microbial communities than the shrimp pond that was not treated with probiotics (SP2).

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Section: Discussionmentioning

confidence: 99%

Characterization of bacterial communities in prebiotics and probiotics treated shrimp farms from Kuantan

Siew, S. W.,

Kosnin, I. N.,

Zulkifli, N. F.

et al. 2023

MJM

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“…Journal Pre-proof Water quality models discuss different water properties such as DO, temperature, pH, conductivity, turbidity and total algae (Shamsudin et al, 2016). DO and its dropdown challenges are nowadays the focus of many systematic investigations.…”

Section: J O U R N a L P R E -P R O O Fmentioning

confidence: 99%

Numerical simulation of Dissolved Oxygen as a water quality indicator in artificial lagoons—Case study El Gouna, Egypt

Abouelsaad

Matta²,

Omar³

et al. 2022

Regional Studies in Marine Science

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Digital water: artificial intelligence and soft computing applications for drinking water quality assessment

Chhipi‐Shrestha

Mian

Mohammadiun

et al. 2023

Clean Techn Environ Policy

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Review on significant parameters in water quality and the related artificial intelligent applications

Cited by 4 publications

References 32 publications

Characterization of bacterial communities in prebiotics and probiotics treated shrimp farms from Kuantan

Characterization of bacterial communities in prebiotics and probiotics treated shrimp farms from Kuantan

Numerical simulation of Dissolved Oxygen as a water quality indicator in artificial lagoons—Case study El Gouna, Egypt

Digital water: artificial intelligence and soft computing applications for drinking water quality assessment

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Review on significant parameters in water quality and the related artificial intelligent applications

Cited by 4 publications

References 32 publications

Characterization of bacterial communities in prebiotics and probiotics treated shrimp farms from Kuantan

Characterization of bacterial communities in prebiotics and probiotics treated shrimp farms from Kuantan

Numerical simulation of Dissolved Oxygen as a water quality indicator in artificial lagoons—Case​ study El Gouna, Egypt

Digital water: artificial intelligence and soft computing applications for drinking water quality assessment

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Product

Resources

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Numerical simulation of Dissolved Oxygen as a water quality indicator in artificial lagoons—Case study El Gouna, Egypt