CITARUM RIVER, WEST JAVA, INDONESIA
3. Results and Discussion
3.1 Physicochemical properties
The physicochemical characteristics at all of sampling locations along upstream Citarum river is shown in Table 2.
Table 2 Physicochemical properties of collected samples
Sampling Point Temp (°C) pH DO (mg/L) BOD (mg/L) COD (mg/L)
SI 20.8 6.8 5.31 10.07 14.70
S2 25.5 7.2 8.03 2.92 9.85
S3 26.3 6.6 1.62 13.60 43.85
84 27.2 6.7 3.14 14.21 58.85
S5 24,8 6.9 2.47 32.31 44.40
S6 26.4 6.7 2.43 16.61 58.85
Water Quality
Standard - 6-9 4 3 25
*Waterqualitystandardof river water Class 2, PPno.82/2001
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Temperatures range were suitable for mesophilic bacteria to grow. NCB belong to mesophilic bacteria that grow in temperature range of 15-55 °C, with the optimum temperature of 30-35 0 C (Hardjo et al., 1989). Temperature is an important factor that affects the growth rate and size of cells (Wang, 2010). The pH measurements ranged from 6.6 to 7.2.
According to Effendi (2003), this pH range is categorized as natural waters. The pH value of the water is a parameter affecting the composition of species in a community.
Microorganisms have an optimum pH range of 5 to 8. The pH of water at all observations locations still met water quality standards class 2.
Dissolved oxygen concentration in S3 (Dayeuhkolot) until S6 (Selacau, Batujajar) were lower than the water quality standard. It is because the photosynthesis is inhibited due to river pollution. Only S2 (Situ Cisanti) sample had BOD and COD value below the water quality standards, while all other locations have exceeded these standards. Dissolved Oxygen (DO) concentration was getting lower following the stream, however, BOD and COD values were higher. It shows that the more downstream, the pollution level of river water was increasing. All of the pollutant will accumulate in the downstream. In high BOD level, DO will decrease because the available oxygen in the river water consumed by microorganisms to oxidize organic materials. The COD value is directly proportional to the BOD value.
Furthermore, COD level is generally greater than BOD value since the number of chemical compounds that can be oxidized chemically greater than biologically (Maulini, 2014).
3.2 The Abundance of E. coli and Salmonella sp.
The abundance of E. coli and Salmonella sp. at all locations is shown in Table 3. The highest number of E.coli was founded in S5 (Nanjung), while the highest number of Salmonella sp. existed at S4 (Cilampeni). This results were in line with previous research showed by Ariesyady and Kusumah (2012) which mentioned that the region of Margaasih and Nanjung had the highest number of E. coli that originated from human and animal husbandry. Cilampeni and Katapang had the highest number of Salmonella sp. along the upstream of Citarum River, so that the improvement of sanitation and domestic wastewater treatment facilities is needed. The presence of E.coli and Salmonella sp. in the Cisanti spring seemed to be related with the use of animal manure on agricultural activities and a lot of the number of cattle sheds in the upstream of Citarum River. Livestock manure is discharged directly into the water body causing the quality of the upstream Citarum river worst (Wanadri, 2010).
Table 3 Abundance of E.coli and Salmonella sp.
Sampling point E.coli (x 10z/g) Salmonella sp. (CFU/g)
SI 0.3 1000
S2 240 90
S3 230 180
S4 2400 4200
S5 4600 1200
S6 230 70
3.4 The Abundance of Nitrogen Cycling Bacteria (NCB)
Table 4 shows the number and abundance of NCB isolates obtained from Upstream
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Citarum River sediment.
Table 4 NCB isolates and abundance Sampling
point
Number of NCB Isolates
Abundance of NCB (xlO5 CFU/g)
SI 5 67.81 ±39.29
S2 4 78.13 ±34.48
S3 4 127.34 ±54.30
S4 6 322.43 ±42.13
S5 2 204.71± 73.79
S6 4 86.63± 46.01
There were 25 NCB isolates obtained with the highest number of NCB isolates and abundance was found in S4 (Cilampeni). Higher abundance of NCB was affected by higher concentration of organic material originated from domestic wastewater discharged by local communities. Seven indigenous NCB isolates in upstream of Citarum river sediments were identified, namely Bacillus licheniformis NCB ctrm p.l, Brevibacterium iodinum NCB ctrm p.2, Bacillus barbaricus NCB ctrm p.2, Bacillus safensis NCB ctrm p.3, Bacillus pumilus NCB ctrm p.4, Stenotrophomonas pavanii NCB ctrm p.3 and uncultured bacterium NCB ctrm p.6.
3.5 Microcosm Test
Diversity index of Nitrogen Cycling Bacteria (NCB)
Figure 3 shows the NCB diversity index. The determination of diversity index was performed at the beginning of the microcosm test and acclimatization (HO), last day of acclimatization and inoculation E. coli (Hl4), and H21 which was the last day of the Microcosm test. The results figured out that NCB diversity index in HO ranged from 0.00 (control) to 0.56 (s2p3). After acclimatization process for 14 days, there was a slight decline of NCB diversity index with an average of 0.01. Furthermore, on day 21 it can be seen a greater decrease in NCB diversity index. The highest diversity index decrease result was found in treatment s3p4 by using S3 (Selacau, Batujajar) sediment with 15% addition of £ coli which had 0.27 decreasing point. Moreover, it can be concluded that NCB diversity index was getting lower due to higher sediment contamination level.
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The highest concentration of pollutants in the sediment with the addition of the highest concentrations of E. coli resulted in a highest decrease in diversity index of NCB.
Another factor that led to a decrease in NCB diversity index were the reduction of nutrients in the sediment and the presence of secondary metabolites produced by the bacteria during Microcosm test which inhibited the growth of NCB. At this Microcosm test, four bacteria species used were Bacillus groups which producing secondary metabolites (antibiotics) that inhibit the growth of pathogenic bacteria (Sansinenea and Ortiz, 2011). In addition, there was also Brevibacterium sp. which produce secondary metabolites that inhibit the growth of gram positive and negative bacteria (Admawy, 1982). Van Elsas et al. (2012) described that the diversity of soil bacteria was negatively correlated with the presence of pathogenic bacteria.
Higher number of pathogenic bacteria caused higher reduction of soil bacterial diversity index. In addition, the system of land with low biological complexity (low diversity) improve the ability of pathogenic bacteria to live in it (Van Elsas et al., 2007). Furthermore, analysis of variance was also conducted in the reduction data of NCB diversity index on H14 and H21. The summary of the ANOVA results is shown in Table 5.
Table 5 ANOVA recapitulation on reduction of NCB diversity index
Variation source Df
ss
MS F Sig. HypothesisPrimary effect A 2 0.061 0.031 13.050 0.000 Rejected Primary effect B 3 0.031 0.010 4.379 0.014 Rejected
AB interaction 6 0.137 0.023 9.779 0.000 Rejected
A =sedimentsource B=£. coli concentration
ANOVA result of reduction data in the diversity index of NCB in Table 5 shows that the hypothesis testing of single and combined primary variables had a significance value
<0.05, so the hypothesis was rejected, which means there was significant influence of each variable, the type of sediment source and volume concentration of E. coli to the reduction in the diversity index of NCB. There was also a significant interaction on the sediment type and volume of concentrations of E. coli to the decrease of diversity index. In other words that the difference in sediment source and the volume concentration of E.coli simultaneously gave a significant effect on the reduction of the NCB diversity index.