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  5. Bacterial Strain Identification from Drinking Water in Water Treatment Systems

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Article
English
2025

Bacterial Strain Identification from Drinking Water in Water Treatment Systems

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English
2025
Deleted Journal
Vol 13
DOI: 10.4028/p-swu9ge

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Mohd Hafiz Dzarfan Othman
Mohd Hafiz Dzarfan Othman

Universiti Teknologi Malaysia

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Mustapha Salisu Muhammad
Mohd Hafiz Dzarfan Othman
Mohd Hafiz Puteh
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Abstract

The availability of clean and safe water for drinking is essential for human life and existence, which ideally should be suitable for consumption and not contain pathogenic microorganisms, or any contamination leading to pollution. Water treatment systems are integral to modern water purification processes, yet they are frequently challenged by biofouling. Biofouling continues to be a major obstacle in water treatment systems, resulting in decreased efficiency, higher energy usage, and increased operational expenses. Therefore, this study aimed to determine the bacteriological characteristics of drinking water by isolating and identifying bacterial strains from water samples contributing to biofouling. Samples were obtained from water treatment systems (WTS) at different locations in Malaysia. Selected isolates of unique bacterial strains were identified and assigned their accession numbers. Phylogenetic analysis revealed that these isolates were related to Bacillus cereus, Stenotrophomonas maltophilia , and Stenotrophomonas pavanii species, suggesting that deterioration in water quality from the source, human error, and technical failure may cause decline even if the most desirable treatment systems and disinfection procedures applied.

How to cite this publication

Mustapha Salisu Muhammad, Mohd Hafiz Dzarfan Othman, Mohd Hafiz Puteh, Nik Ahmad Nizam Nik Malek, Abdul Razis Saidin, A. Yusof, Roziana Kamaludin, Siti Maryam, Ojo Samuel, Chia Ming Liew, Anzana Parvin, Nurul Huda (2025). Bacterial Strain Identification from Drinking Water in Water Treatment Systems. Deleted Journal, 13, pp. 83-96, DOI: 10.4028/p-swu9ge.

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Publication Details

Type

Article

Year

2025

Authors

12

Datasets

0

Total Files

0

Language

English

Journal

Deleted Journal

DOI

10.4028/p-swu9ge

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