• 한국식품위생안전성학회지
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• 제14권1호
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• pp.1-8
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• 1999

There were few data for the distribution of the indicator organisms in the commercial plant foods, and for the normal flora and for the foodborne agents within the country. First of all it must be investigated the distribution of the indicator organisms. And also it is very important to prepare the sanitation criteria for the plant foods through the microbiological examination and the investigation of tendency to change of the indicator organisms according to the storage temperature and period. The average number of total viable counts for grains was 2.9$\times$105/g, psychrophilic bacteria 2.9$\times$105/g, heterotrophic bacteria 3.1$\times$105/g, heat-resistant bacteria 2.1$\times$103/g, Pseudomonas aeruginosa 23/g. That for beans was 6.3$\times$102/g, psychrophile 34/g, heterotroph 1.7$\times$102/g. That for sesames was 1.4$\times$105/g, coliform 350/g, psychrophile 7.4$\times$104/g, heterotroph 5.8$\times$104/g, Pseud. aeruginosa 2.3$\times$103/g. heat-resistant bacteria 150/g. That for potatoes was 2.0$\times$107/g, coliform 5.0$\times$104/g, psychrophile 1.8$\times$107, heterotroph 1.4$\times$107/g, heat-resistant bacteria 3.3$\times$104/, Staphylococcus 2.7$\times$105/g, fecal streptococcus 4.5$\times$103/g, Pseud. aeruginosa 7.0$\times$103/g. That for mushrooms was 1.2$\times$108/g, psychrophile 9.4$\times$107/g, heterotroph 1.0$\times$109/g, heat-resistant bacteria 1.6$\times$105/g, Pseud. aeruginosa 1.3$\times$103/g. That for vegetables was 5.9$\times$1011/g, coliform 1.8$\times$106g/, Staphylococcus 1.1$\times$1012/g, heterotroph 8.4$\times$1011/g, heat-resistant bacteria 7.6$\times$106/g, Staphylococcus 1.1$\times$107/g, fecal streptococcus 1.1$\times$104/g, Pseud. aerugniosa 5.2$\times$104/g. That for nuts 3.9$\times$104/g, coliform 3.9$\times$103/g, psychrophile 4.0$\times$104/g, heterotroph 3.2$\times$104/g, heat-resistant bacteria 400/g. In commercial grains and beans, SPC, psychrophile, heterotroph and heat-resistant bacteria stored at 1$0^{\circ}C$, 2$0^{\circ}C$, 3$0^{\circ}C$ were constant. Staphylococcus, coliform, Pseud. aeruginosa were decreased a little n grains, but were not detected in beans. In mushrooms, all indicator organisms were increased as time goes on and were increased rapidly at 2$0^{\circ}C$. In sesames, coliform was not detected at all temperature. psychrophile was increased for 7 days, the others were constant. In potatoes, SPC, psychrophile, heat-resistant bacteria, heterotroph had a tendency to increase and the others were constant. In vegetables, indicator organisms were had a tendency to increase, psychrophile, heterotroph were rapidly increased after 7 days. In nuts, SPC, coliform, psychrophile heterotroph, heat-resistant bacteria, Pseud. aeruginosa were constant, staphylococcus and fecal streptococcus were not detected.

• 한국환경보건학회지
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• 제34권1호
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• pp.86-94
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• 2008

Lake Shiwha, an artificial lake located near metropolitan Seoul, offers a unique water environment and has been suspected to have high levels of chemical and microbiological contaminations. Lake Shiwha was originally connected to the sea but currently has four major surface water inputs from agricultural, municipal, industrial areas and in addition an occasional inflow from the sea. The objectives of this study are to investigate the relative contribution of microbial contaminants from each of the inflowing surface waters and to identify appropriate microbial indicator organisms in this unique water environment. We measured the levels of microbial contaminations in the four inflowing surface waters. A number of microbial indicator organisms including total coliform (TC), fecal coliform (FC), E. coli, Enterococci, somatic and male-specific coliphages were analyzed. Bacterial indicator microorganisms were detected and quantified by the $Colilert^{(R)},\;Enterolert^{(R)}$ kit. Surface water (50 l) was sampled by $ViroCap^{TM}\;5"$ cartridge filters and analyzed by the single agar layer method for detecting coliphages. The concentrations of TC, FC, E. coli, and Enterococci were 1543 CFU/100 ml${\sim}1.99{\times}10^6$ CFU/100 ml, 0 CFU/100 ml${\sim}202$ CFU/100ml, 0 CFU/100 ml${\sim}1.80{\sim}10^5$ CFU/100ml, 74 CFU/100 ml${\sim}3408$ CFU/100 ml, respectively. The male-specific and somatic coliphages were detected in three different inflowing surface waters. Isolated E. coli and Enterococci strains were further analyzed by 16s rDNA amplification and subsequent phylogenetic analysis from Jungwang-chun, Ansan-chun, Banwol-chun and penstock of inflowing surface water. Our results indicated that the concentrations of different fecal indicator microorganisms might not be highly correlated with each other. Multiple microbial indicator organisms should be used for monitoring microbial contamination and microbial source tracking methods.

• 한국생물공학회:학술대회논문집
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• 한국생물공학회 2001년도 추계학술발표대회
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• pp.815-818
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• 2001

수계 미생물의 세포 농도 정도를 DST와 spectrophotometer를 이용하여 간편하고 빠르게 측정할 수가 있었다. 기존의 MPN와 MF의 방법은 노동집약적이며 false positive나 false negative의 확률이 높고 검출 시간도 하루이상 소요되는 단점이 있었다. 그러나, 세포 성장거동과 DST의 원리를 웅용하여 간편한 검출 시스템을 정량적으로 기술함으로써 쉽고 빠르게 수계 미생물의 농도를 측정하는 방법을 제시하였다.

• 한국환경보건학회지
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• 제19권2호
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• pp.10-15
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• 1993

Hygienic condition of farm waters has an effect on the hygiene of dairy foods. So we examined Standard Plate Count, coliform, E. coli, heat-resistant bacteria, psychrophilic bacteria, Pseudomonas aeruginosa and enterococcus for the bacterial sanitation of 78 farm waters in Kyunggi Province. Of the 78 farm waters, the average number of psychrophilic bacteria was 750 $\pm$ 170/ml, SPC 440 $\pm$ 130/ml, Pseudomonas aeruginosa 130 $\pm$ 97/100/ml, Coliform 22 $\pm$ 17/ml, E. coli 10 $\pm$ 6/100/ml, Heatresistant bacteria 5 $\pm$ 1ml, and Enterococcus 2 $\pm$ 1/100/ml. The percent of over than 1000/ml in SPC and psychrophilic bacteria of 78 farm water was 11.5% and 23.1%, respectively. The rate of over than 10/ml in coliform and heat-resistant bacteria was 12.8% and 15.4%, respectively and the rate of over than 10/100 ml in E. coli, Pseudomonas aeruginosa and enterococcus was 8.9%, 33.3%, and 2.6%, respectively. Pseudomonas aeruginosa was no significant between any other indicator organisms, and psychrophilic bacteria was significant with only SPC but other indicator organisms were highly significant with each other.

• 한국환경보건학회지
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• 제22권4호
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• pp.109-121
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• 1996

It was intended to investigate the effect of the microbiological kitchen hygiene such as dishclothes and scrubbers. The 8indicator organisms (standard plate counts, coliform, heterotroph, enterococcus, staphylococcus, heat-stable bacteria, psychrotroph, Pseudomonas aeruginosa) were detected highly in dishwaters, dishcloth and scrubber. Coliform and Staphylococcus aureus were appeared on dishcloth dominantly than the scrubber, and the scrubbers were intruded by hetrotrophs and psychrotrophs numerously than dishclothes. The germ-resistant sponge inhibited the growth of the most of test strain, and appeared the about 100% reduction rate after 24 hr, but did not affect Pseudomonas aeruginosa and P. fragi so typically after 24 hr. The anti-microorganism durability of germ-resistant sponge, treated with food soil, was maintained by 10 days, the early stage strain density was founded in 20 days, and the strains grew after 30 days.

• 상하수도학회지
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• 제20권4호
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• pp.627-635
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• 2006

Combined sewer overflow (CSOs) is a primary diffuse source degrading water quality of urban streams. In this study, CSOs caused by 5 different rainfall events at an urban watershed located in Daejeon city were monitored for the indicator microorganism concentrations. Event mean concentration (EMC) of the indicator microorganisms were: total coliform = $2.46{\times}10^6CFU/100mL$; fecal coliform = $1.01{\times}10^6CFU/100mL$; E.coli = $5.20{\times}10^5CFU/100mL$; and Fecal Streptococci = $6.08{\times}10^5CFU/100mL$. In addition, coliform concentrations were well correlated with suspended solid concentrations and the first flush effects were identified. Settling tests were carried out to estimate removal rate of indicator organisms by sedimentation from CSOs. As microorganisms are discharged in association with suspended solid, ten minutes of settlement can lower 44% of indicator microorganism leading.

• 한국환경보건학회지
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• 제36권3호
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• pp.229-235
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• 2010

Efforts to evaluate water pollution using indicator microorganisms have been underway for decades, and driven by research on water purity control applications, water quality criteria are growing more and more strict. Furthermore, recent reports indicate that high concentrations of antibiotics are not absorbed, and are present in excrement from animals and humans dosed with unnecessarily high levels of antibiotics. This has emerged as very important issue from the standpoint of being an ecological and health hazard. In this study, water pollution was analyzed through physicochemical and microbiological means, and antibiotic resistance in indicator microorganisms was assessed. In physicochemical analysis, biochemical oxygen demand (BOD)$_5$ and chemical oxygen demand (COD)$_{Mn}$ evaluation showed that pollution by organisms was highest at the G1 location with a high human population, and the DP location which has many livestock-containing households. The indicator organism levels at the G1 location were: Total Coliforms (1205 colony forming units (CFU)/100 ml), Fecal Coliforms (270 CFU/100 ml), Escherichia coli (253 CFU/100 ml) and Fecal Streptococci (210 CFU/100 ml), while for the DP location levels were: Total Coliforms (1480 CFU/100 ml), Fecal Coliforms (438 CFU/100 ml), E. coli (560 CFU/100 ml), and Fecal Streptococci (348 CFU/100 ml). Levels of fecal indicator microorganisms such as Fecal Coliforms, E. coli and Fecal Streptococci were high at all locations in the fall (the period after the rainy season), and the yearly distribution was similar between these organisms. If the number of livestock-containing households was high, almost all strains of E. coli (as distinct from the other indicator organisms) showed resistance to antibiotics, with the degree of resistance varying between areas. E. coli strains from the OY area in particular, which has a high population density, showed strong resistance to AM10 and Va30. While strong antibiotic resistance was observed overall at the DP and OY locations, no resistance was observed at the EB location.

• 한국환경보건학회지
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• 제24권1호
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• pp.141-150
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• 1998

This study was performed to investigate the distribution of Yersiniae and correlation between Yersiniae and indicator organism by time and area in spring water located in northern part of Seoul. Samples collected from 46 spring waters located in four mountains(Dobong, Bukhan, Surak, Bulam) were inspected to detect Yersiniae and indicator organisms. And also there were examined bioserological characteristics and resistance of ahtibiotics of the isolated Yersiniae.The result were as follows. 1. The isolation rate of Yersiniae was 22% in February and 20% in April. The isolated species were 6 strains of Y. enterocolitica, 6 strains of Y. aldova, 4 strains of Y. intermedia and 43 strains of Y. pseudotuberculosis. The serotype of Y. pseudotuberculosis isolated from was all O:5 and biotype of Y. enterocolitica isolated from was all O:3. 2. The Geometric mean of standard plate count, coliform, and psychrotrophilic bacteria were 3.4 CFU/ml, 1.2 MPN/100 ml and 33.0 CFU/ml in February and 3.1 CFU/ml, 1.5 MPN/100 ml and 20.5 CFU/ml in April respectively. There was no significant difference by time and area but the indicator organisms were correlated significantly with each other (p<0.05). 3. Because detection of Yersiniae was not statistically associated with indicator organism, Yersiniae can be detected in the spring water approved microbiologically (p<0.05). 4. The Yersiniae isolated were resistant to Ampicillin, Colistin, Carbenicillin and Coilstin. All isolaed Y. enterocolitica were resistant to Ampicillin (100%). In the case of Y. pseudotuberculosis, only 1 of 3 isolated was resistant to Colistin but susceptible to other antibiotics.

• 한국환경독성학회:학술대회논문집
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• 한국환경독성학회 1993년도 제12회 총회 및 학술 발표회 특별강연요지집
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• pp.4-5
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• 1993

Toxicity tests in our laboratory are conducted usually with mass-reared organisms. They are under the same environmentel conditions throughout seasons and are supplied at specific age. A total of 38 species of aquatic organisms are being reared. We have attempted to establish pruified strains or to select clones of various parthenogenic organisms. The merits or demerits of our culturing test organisms are discussed. The differences in the susceptibility among clones or strains of test organism are also discussed. For a single species test, algae, daphnia, fish are often used. However, we usually use early stages, but occasionally, adults fish are used for reproduction tests. As an another important aspect, the toxicity through food chains has been studied. In this study, we select a pair of species belonging different trophic levels. The differences between single species tests and multispecies tests will be discussed. Even a single species test intends to assess the effects of chemicals on ecosystem levels, however, this idea is not applicable to ecosystems. Single species tests with standard organisms and multispecies tests are contradictory in concept. One type of multispecles tests is indoor microcosms being composed of severel species artificially assembled, and another is composed of natural components (both indoor and outdoor). We have used three types of outdoor mesocosms using ponds and three types of artificial streams. The mesocosms is useful to not only to analyze the floral or faun61 changes but also to study the fate or behaviour of chemicals in naturd environments. Lastly, usefulness of the field observation or experiments or semi-field experiments will be discussed. This will enhance the exploitation of early warning systems utilizing indicator organisms or animal behaviour.aviour.

• Environmental Analysis Health and Toxicology
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• 제23권4호
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• pp.231-245
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• 2008

Various methods for detecting changes in response behaviors of indicator specimens are presented for monitoring effects of toxic treatments. The movement patterns of individuals are quantitatively characterized by statistical (i.e., ANOVA, multivariate analysis) and computational (i.e., fractal dimension, Fourier transform) methods. Extraction of information in complex behavioral data is further illustrated by techniques in ecological informatics. Multi-Layer Perceptron and Self-Organizing Map are applied for detection and patterning of response behaviors of indicator specimens. The recent techniques of Wavelet analysis and line detection by Recurrent Self-Organizing Map are additionally discussed as an efficient tool for checking time-series movement data. Behavioral monitoring could be established as new methodology in integrative ecological assessment, tilling the gap between large-scale (e.g., community structure) and small-scale (e.g., molecular response) measurements.