Penilaian Kualiti Air dan Komuniti Mikrob dalam Perlombongan Artisanal- Sedimen Terjejas Sungai Cikidang, Banten, Java, Indonesia

Translated title of the contribution: Water Quality and Microbial Community Assessment in Artisanal Mining- Affected Sediments of Cikidang River, Banten, Java, Indonesia

Noverita Dian Takarina, Ayu Maulida Sukma, Andrio Adiwibowo, Sitaresmi

Research output: Contribution to journalArticlepeer-review

Abstract

The total microbial diversity and community in submerged sediments near mining sites, transition and intact sites at Cikidang River, Banten were assessed using 16S rDNA sequence data and biodiversity indices. Assessed water quality parameters in the river were water current, dissolved oxygen (DO), pH, redox potential, salinity, temperature and turbidity. Microbial alpha diversity used were Shannon diversity index, ChaoI index and Operational Taxonomic Units (OTUs). These analyses indicated a total of 50 taxa of sediment microbes. Based on Shannon diversity index, the highest value was observed at mining site. High abundant microbes in sediments at mining sites for phylum, class, order, family and genera levels were represented by Proteobacteria, Gammaproteobacteria, Pseudomonadales, Moraxellaceae, and Acinetobacter, respectively. In contrast, high abundant microbes in the sediment of the intact site for each taxon consisted of Firmicutes, Alphaproteobacteria, Erysipelotrichales, Erysipelotrichaceae, and Erysipelothrix. The water quality of mining sites was characterised by alkaline pH (8.807, 95% CI: 8.624 - 8.990) and lower redox potential (59.000 mV, 95% CI: 36.233 - 81.767) that differed significantly from the intact sites (P<0.05). This study also confirmed that mining sites have a higher genus diversity. Research on potential microbes of related genus as bioremediators could be recommended for further study.

Translated title of the contributionWater Quality and Microbial Community Assessment in Artisanal Mining- Affected Sediments of Cikidang River, Banten, Java, Indonesia
Original languageUndefined/Unknown
Pages (from-to)1339-1352
Number of pages14
JournalSains Malaysiana
Volume51
Issue number5
DOIs
Publication statusPublished - May 2022

Keywords

  • 16S rDNA sequence data
  • Community
  • microorganism
  • mining
  • sediment

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