• Journal of Environmental Health Sciences
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• v.33 no.4
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• pp.293-298
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• 2007

The microorganism for ammonia gas removal was isolated from composting product. This was identified as Brevundimonas diminuta by morphological, biochemical characteristics study and 16S rDNA sequence analysis. Optimal incubation temperature for cell growth and oxidizing ability of $NH_4-N$ was $30^{\circ}C$ and optimal initial pH was 7. Glucose affected the growth of cell and the removal of $NH4^+$. The growth rate of the isolates were increased when grown in the presence of 0.05-1%(w/v) glucose in the selective medium and lurker increases in glucose concentration to 2% caused significant decreases in the cell growth and oxidizing ability of $NH4^+$.

• Microbiology and Biotechnology Letters
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• v.45 no.3
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• pp.257-264
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• 2017

Mixed substrate oil cakes are known to emit sulfides, ammonia, and amines. Microorganisms capable of removing odorous gases related to these sulfur compounds were isolated from colonies enriched in vials containing oil cakes and water. Activity tests for hydrogen sulfide and methyl mercaptan reduction were performed to measure the sulfide reduction ratio of the isolates. Control groups were prepared with 0.25 g oil cakes and 10 ml water in a 100-ml vial without inoculation. The experimental groups were prepared similarly, albeit with an inoculum. Hydrogen sulfide removal efficiency of >90% was observed for an isolate, which was identified as Brevundimonas diminuta by 16S rDNA sequence analysis. The sequence was deposited in the Korean Collection for Type Cultures under the accession number KCTC11724BP. B. diminuta could remove up to 200 ppmv standard hydrogen sulfide in 24 hours and demonstrated a maximum hydrogen sulfide and methyl mercaptan removal efficiency of 100% at 453 ppmv and 98 ppmv, respectively, in vial tests. Furthermore, B. diminuta cells in 20% (v/w) medium showed removal efficiency of >85% for sulfur compounds in an odor emission chamber for swine manure.

• Journal of Microbiology and Biotechnology
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• v.17 no.5
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• pp.769-773
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• 2007

With the aim to produce ascorbic acid-2-phosphate(AsA-2-P) from L-ascorbic acid(AsA, Vitamin C), nine bacteria conferring the ability to transform AsA to AsA-2-P were isolated from soil samples alongside known strains from culture collections. Most isolates were classified to the genus Brevundimonas by 16S phylogenetic analysis. Among them, Brevundimonas diminuta KACC 10306 was selected as the experimental strain because of its the highest productivity of AsA-2-P. The optimum set of conditions for the AsA-2-P production from AsA using resting cells as the source of the enzyme was also investigated. The optimum cultivation time was 16 h and the cell concentration was 120g/l(wet weight). The optimum concentrations of AsA and pyrophosphate were 550mM and 450mM, respectively. The most effective buffer was 50mM sodium formate. The optimum pH was 4.5 and temperature was $40^{\circ}C$. Under the above conditions, 27.5g/l of AsA-2-P was produced from AsA after 36 h of incubation, which corresponded to a 19.7% conversion efficiency based on the initial concentration of AsA.

• Korean Journal of Clinical Laboratory Science
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• v.47 no.4
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• pp.279-285
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• 2015

This study studied samples taken off surfaces at three sites (Unit chairs, light handles, cuspidors) of 19 dental hospitals and 28 clinics located in Gyeonggi-do and Incheon, South Korea. The bacterial contamination levels of surfaces were $44.82{\times}10^3CFU/mL$ in cuspidors, higher than in unit chairs ($5.47{\times}10^3CFU/mL$) and light handles ($16.28{\times}10^3CFU/mL$). The values were statistically higher at dental hospitals than at dental clinics, the greater number of patients being associated with the higher bacterial cell count in the cuspidors. The results of identifying the strains isolated purely from surfaces at dental clinic showed Gram positive 47.3% and Gram negative 52.7%. Among Gram positive, the most numberous bacteria were Micrococcus luteus (10.9%), Bacillus pumilus (3.6%), and Staphylococcus aureus (3.6%). Among Gram negative, the most numberous bacteria were Acinetobacter ursingii (5.5%), Brevundimonas diminuta (4.5%), Chryseobacterium (Flavo.) indologenes (CDC IIb) (4.5%), and Methylobacterium sp. (4.5%). This study measures the level of bacterial contamination and identifies the strains isolated in dental clinics. It recognizes the importance of infection control, and the results of the study may be considered as the basis for establishing specific plans for prevention of infection.

• 한국생물공학회:학술대회논문집
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• 2000.04a
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• pp.125-128
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• 2000

A recycling reactor system operated under sequential anoxic and oxic conditions for the swine wastewater has been developed, in which piggery slurry is fermentatively and aerobically treated and then part of the effluent recycled to the pigsty. This system significantly removes offensive smells (at both pigsty and treatment plant), BOD and other loads, and appears to be costeffective for the small-scale farms. The most dominant heterotrophs were Alcaligenes faecalis, Brevundimonas diminuta and Streptococcus sp. in order while lactic acid bacteria were dominantly observed in the anoxic tank. We propose a novel monitoring system for a recycling piggery slurry treatment system through neural networks. Here we tried to model treatment process for each tank(influent, fermentation, aeration, first sedimentation and fourth sedimentation tanks) in the system based on population densities of heterotrophic and lactic acid bacteria. Principle component analysis(PCA) was first applied to identify a relation between input(microbial densities and parameters for the treatment such as population densities of heterotrophic and lactic acid bacteria, suspended solids (SS), COD, $NH_3-N$, ortho-P, and total-P) and output, and then multilayer neural networks were employed to model the treatment process for each tank. PCA filtration of input data as microbial densities was found to facilitate the modeling procedure for the system monitoring even with a relatively lower number of input. Neural networks independently trained for each treatment tank and their subsequent combinatorial data analysis allowed a successful prediction of the treatment system for at least two days.

• Biotechnology and Bioprocess Engineering:BBE
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• v.5 no.5
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• pp.355-361
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• 2000

A recycling reactor system operated under sequential anoxic and oxic conditions for the treatment of swine wastewater has been developed, in which piggery slurry is fermentatively and aerobically treated and then part of the effluent is recycled to the pigsty. This system significantly removes offensive smells (at both the pigsty and the treatment plant), BOD and others, and may be cost effective for small-scale farms. The most dominant heterotrophic were, in order, Alcaligenes faecalis, Brevundimonas diminuta and Streptococcus sp., while lactic acid bacteria were dominantly observed in the anoxic tank. We propose a novel monitoring system for a recycling piggery slurry treatment system through the use of neural networks. In this study, we tried to model the treatment process for each tank in the system (influent, fermentation, aeration, first sedimentation and fourth sedimentation tanks) based upon the population densities of the heterotrophic and lactic acid bacteria. Principal component analysis(PCA) was first applied to identify a relationship between input and output. The input would be microbial densities and the treatment parameters, such as population densities of heterotrophic and lactic acid bacteria, suspended solids(SS), COD, NH$_4$(sup)+-N, ortho-phosphorus (o-P), and total-phosphorus (T-P). then multi-layer neural networks were employed to model the treatment process for each tank. PCA filtration of the input data as microbial densities was found to facilitate the modeling procedure for the system monitoring even with a relatively lower number of imput. Neural network independently trained for each treatment tank and their subsequent combined data analysis allowed a successful prediction of the treatment system for at least two days.