Bacteriological Contamination Detection in Water
and Wastewater Samples Using OD600

Domańska, Magdalena; Hamal, Kamila; Jasionowski, Bartosz; Łomotowski, Janusz

doi:10.15244/pjoes/94838

Cited by 14 publications

(8 citation statements)

References 12 publications

(14 reference statements)

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“…After the value of the subgraph centrality of each node is calculated, the subgraph centrality of the super network can be obtained by calculating the average value. In literature [17], the formula for calculating the centrality of the hypernetwork subgraph is…”

Section: Topological Metrics For Hypernetworkmentioning

confidence: 99%

Water Quality Substance Detection System Based on Internet of Things

Zhang

2022

Security and Communication Networks

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According to the sources of pollution in different river regions, the characteristics of rivers and lakes, and on the basis of investigation and analysis of the actual situation of water environment monitoring in different river regions, this paper carries out a research on the optimization of water quality detection and gives the definition of a super network as a super network based on a hypergraph structure. Moreover, according to the simulation results of topological parameters, this paper analyzes the structural characteristics of the super network and combines the Internet of Things technology to construct a water quality material detection system. In addition, this paper evaluates the water quality detection effect of the system proposed in this paper through a control experiment. According to the quality inspection results, it can be seen that the accuracy rate of the water quality material detection system based on the Internet of Things proposed in this paper is more than 92%, which verifies that the system model proposed in this paper has a good effect.

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Section: Topological Metrics For Hypernetworkmentioning

confidence: 99%

Water Quality Substance Detection System Based on Internet of Things

Zhang

2022

Security and Communication Networks

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“…We have two speculations. First, the optional density (OD 600 ) was used to measure the concentration of the bacterial solution because that this method is suitable for measuring a large number of cultures, and is more accurate for homogeneous bacterial solutions [42,43] However, these screening strains are aerobic bacteria which can easily live in contact with the air on the surface of the culture medium and whose solutes are not homogeneous (Figure 7), thus the OD 600 value is low. Second, although 1 mL bacterial solution were added to the fresh medium at the beginning of the experiment, the concentration of 1 mL solution (OD 600 ) was not completely consistent from transfer to transfer.…”

Section: Discussionmentioning

confidence: 99%

Isolation and Characterization of Viscosity-Reducing and Biosurfactant-Producing Bacteria in Low-Permeability Reservoir

Bian

Wei

et al. 2023

International Journal of Energy Research

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Microbialenhanced oil recovery has gained more attention in recent years due to its low cost and eco-friendliness. However, studies on the application of this technique in the low-permeability reservoirs are few. In this study, eight strains from the Ordos Basin low-permeability reservoir that produce biosurfactant and reduce viscosity were identified. Strains could produce biosurfactants (lipopeptide and glycolipids) to emulsify the oil and had good tolerance on temperature (25°C-50°C), salinity (1 g/L-50g/L), and pH (5-10). After the actions of A-3, SC4534(2), SC4561, and JSC4535, the content of long-chain n-alkanes were decreased by 51.2%, 28.3%, 35.2%, and 28.9%, respectively. The naphthalene in aromatic hydrocarbons was also effectively degraded by the strains that were screened, and the degradation rate was higher than 84%. Additionally, all strains were able to reduce oil viscosity, which was reduced by 27-51% (in seven days). 16S rRNA gene sequencing analysis indicated that seven strains belong to the genus Bacillus and one belongs to the genus Rhodospirillaceae. The results revealed that the existence of high-efficiency strains that can significantly improve the properties of crude oil in low-permeability oil fields though biodegradation and use of biosurfactants, which is of great significance for the application of MEOR in low-permeability oil fields.

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“…The isolates showed varying rates of growth indicated by differences in turbidity which corresponded to the OD600 values. The degree of turbidity in the broth culture is directly related to the number of microorganisms, studies have shown that cell density is proportional to OD600 according to Domańska et al (2019). Udall et al (2015) reported lower values for growth (0.77-1.80 OD600) by environmental Pseudomonas after 3 days of incubation.…”

Section: Discussionmentioning

confidence: 99%

Biofilm Formation Capability of Cowpea Nodular Bacterial Isolates in Static Microcosms

HM¹

2023

AJBAR

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Bacteria are known to form microbially derived sessile communities that are irreversibly attached to biotic or abiotic surfaces known as biofilms. Biofilm formation is an adaptive strategy for the successful colonization of plant surfaces. Forty bacterial isolates of cowpea nodules from 12 smallholder farms in Northern Nigeria were evaluated for biofilm growth, attachment and strength in static microcosms. Replicate King’s B (KB) microcosms (n = 8) were incubated statically for 7 days before assessments. Growth and attachment were determined by measuring optical density (OD600nm) and absorbance (A570 nm) respectively. Strength (grams) was determined by maximum deformation mass (MDM) assay using glass balls (mean weight of 0.0115g). A significant MDM was recorded when more than one replicate retained at least one ball for at least 5 seconds. One-way Analysis of Variance (ANOVA) was used to determine significant mean differences (p<0.05). Similarities and variations in biofilm formation were assessed by Hierarchical Cluster Analysis (HCA) using the Ward method. Half of the isolates showed good biofilm growth and attachment. Twelve of the 40 isolates showed various levels of strength. Isolates 16F and 39L were rated well in all three biofilm parameters. There were significant differences in the mean values of the assessed biofilm parameters among the isolates. Mean growth ranged between 1.493 (Isolate 32K) and 2.101 OD600 (Isolate 19G). Mean attachment levels (A570) ranged from 0.084 (Isolate 9D) to 1.543 (Isolate 30K). Only isolate 2A had significantly higher biofilm strength (2.412g) than the rest of the isolates. HCA analysis indicated similarities as well as variations in biofilm formation by isolates within and between sites. Isolates from all the study sites were positive for at least one of the tested biofilm parameters. The ability of the isolates to form biofilms indicated that some of them could be suitable for biotechnological applications such as in biofertilizer production

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Bacteriological Contamination Detection in Water and Wastewater Samples Using OD600

Cited by 14 publications

References 12 publications

Water Quality Substance Detection System Based on Internet of Things

Water Quality Substance Detection System Based on Internet of Things

Isolation and Characterization of Viscosity-Reducing and Biosurfactant-Producing Bacteria in Low-Permeability Reservoir

Biofilm Formation Capability of Cowpea Nodular Bacterial Isolates in Static Microcosms

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