농업용수의 미생물학적 안전성 조사 및 위생지표세균 농도와 병원성미생물 검출률과의 상관관계 분석
Investigation of Microbial Safety and Correlations Between the Level of Sanitary Indicator Bacteria and the Detection Ratio of Pathogens in Agricultural Water
2
조회
0
다운로드
2
인용
0
참고문헌
키워드
초록
BACKGROUND: Contaminated water was a major source of food-borne pathogens in various recent fresh produce- related outbreaks. This study was conducted to investigate the microbial contamination level and correlations between the level of sanitary indicator bacteria and the detection ratio of pathogens in agricultural water by logistic regression analysis. METHODS AND RESULTS: Agricultural water was collected from 457 sites including surface water (n=300 sites) and groundwater (n=157 sites) in South Korea from 2018 to 2020. Sanitary indicator bacteria (total coliform, fecal coliform, and Escherichia coli) and food-borne pathogens (pathogenic E. coli, E. coli O157:H7, Salmonella spp., and Listeria monocytogenes) were analyzed. In surface water, the coliform, fecal coliform, and E. coli were 3.27±0.89 log CFU/100 mL, 1.90±1.19 log CFU/100 mL, and 1.39±1.26 log CFU/100 mL, respectively. For groundwater, three kinds of sanitary indicators ranged in the level from 0.09 - 0.57 log CFU/100 mL. Pathogenic E. coli, Salmonella and Listeria monocytogenes were detected from 3%-site, 1.5%- site, and 0.6%-site water samples, respectively. According to the results of correlations between the level of sanitary indicator bacteria and the detection ratio of pathogens by logistic regression analysis, the probability of pathogen detection increased individually by 1.45 and 1.34 times as each total coli-form and E. coli concentration increased by 1 log CFU/100mL. The accuracy of the model was 70.4%, and sensitivity and specificity were 81.5% and 51.7%, respectively. CONCLUSION(S): The results indicate the need to manage the microbial risk of agricultural water to enhance the safety of fresh produce. In addition, logistic regression analysis is useful to analyze the correlation between the level of sanitary indicator bacteria and the detection ratio of pathogens in agricultural water.
Abstract
BACKGROUND: Contaminated water was a major source of food-borne pathogens in various recent fresh produce- related outbreaks. This study was conducted to investigate the microbial contamination level and correlations between the level of sanitary indicator bacteria and the detection ratio of pathogens in agricultural water by logistic regression analysis. METHODS AND RESULTS: Agricultural water was collected from 457 sites including surface water (n=300 sites) and groundwater (n=157 sites) in South Korea from 2018 to 2020. Sanitary indicator bacteria (total coliform, fecal coliform, and Escherichia coli) and food-borne pathogens (pathogenic E. coli, E. coli O157:H7, Salmonella spp., and Listeria monocytogenes) were analyzed. In surface water, the coliform, fecal coliform, and E. coli were 3.27±0.89 log CFU/100 mL, 1.90±1.19 log CFU/100 mL, and 1.39±1.26 log CFU/100 mL, respectively. For groundwater, three kinds of sanitary indicators ranged in the level from 0.09 - 0.57 log CFU/100 mL. Pathogenic E. coli, Salmonella and Listeria monocytogenes were detected from 3%-site, 1.5%- site, and 0.6%-site water samples, respectively. According to the results of correlations between the level of sanitary indicator bacteria and the detection ratio of pathogens by logistic regression analysis, the probability of pathogen detection increased individually by 1.45 and 1.34 times as each total coli-form and E. coli concentration increased by 1 log CFU/100mL. The accuracy of the model was 70.4%, and sensitivity and specificity were 81.5% and 51.7%, respectively. CONCLUSION(S): The results indicate the need to manage the microbial risk of agricultural water to enhance the safety of fresh produce. In addition, logistic regression analysis is useful to analyze the correlation between the level of sanitary indicator bacteria and the detection ratio of pathogens in agricultural water.
참고문헌 (37)
- Balali GI, "Microbial contamination, an increasing threat to the consumption of fresh fruits and vegetables in today’s world", International Journal of Microbiology, 2020, pp.3029295~ (2020)[DOI]
- Mikhail AFW, "An outbreak of Shiga toxin-producing Escherichia coli O157: H7 associated with contaminated salad leaves:epidemiological, genomic and food trace back investigations", Epidemiology & Infection, 146(2), pp.187~196 (2018)[DOI]
- 오소영, "재배농법에 따른 국내산 배추의 위해미생물 및 중금속 오염평가", 한국식품위생안전성학회지, 32(6), pp.500~506 (2017), 한국식품위생안전성학회[DOI]
- Aiyedun SO, "Foodborne outbreaks of microbial infection from fresh produce in Europe and North America : a systematic review of data from this millennium", International Journal of Food Science & Technology, 56(5), pp.2215~2223 (2021)[DOI]
- Beuchat LR, "Ecological factors influencing survi val and growth of human pathogens on raw fruits and vegetables", Microbes and Infection, 4(4), pp.413~423 (2002)[DOI]
- Beuchat LR, "Produce handling and processing practices", Emerging Infectious Diseases, 3(4), pp.459~ (1997)[DOI]
- Beuchat LR, "Pathogenic microorganisms associated with fresh produce", Journal of Food Protection, 59(2), pp.204~216 (1996)[DOI]
- Allende A, "Irrigation water quality for leafy crops : a perspective of risks and potential solutions", International Journal of Environmental Research and Public Health, 12(7), pp.7457~7477 (2015)[DOI]
- Van Der Linden I, "Enteric pathogen survival varies substantially in irrigation water from belgian lettuce producers", International Journal of Environmental Research and Public Health, 11(10), pp.10105~10124 (2014)[DOI]
- Steele M, "Irrigation water as source of foodborne pathogens on fruit and vegetables", Journal of Food Protection, 67(12), pp.2839~2849 (2004)[DOI]
- Söderström A, "A large Escherichia coli O157outbreak in Sweden associated with locally produced lettuce", Foodborne Pathogens and Disease, 5(3), pp.339~349 (2008)[DOI]
- Greene SK, "Recurrent multistate outbreak of Salmonella Newport associated with tomatoes from contaminated fields, 2005", Epidemiology & Infection, 136(2), pp.157~165 (2008)[DOI]
- Bottichio L, "Shiga toxin–producing Escherichia coli infections associated with romaine lettuce—United States, 2018", Clinical Infectious Diseases, 71(8), pp.e323~e330 (2018)[DOI]
- Uyttendaele M, "Microbial hazards in irrigation water : standards, norms, and testing to manage use of water in fresh produce primary production", Comprehensive Reviews in Food Science and Food Safety, 14(4), pp.336~356 (2015)[DOI]
- Barrell RA, "Microbiological standards for water and their relationship to health risk", Communicable Disease and Public Health, 3(1), pp.8~13 (2000)[DOI]
- Divya AH, "Effects of some water quality parameters especially total coliform and fecal coliform in surface water of Chalakudy river", Procedia Technology, 24, pp.631~638 (2016)[DOI]
- Pachepsky Y, "Can E. coli or thermotolerant coliform concentrations predict pathogen presence or prevalence in irrigation waters?", Critical Reviews in Microbiology, 42(3), pp.384~393 (2016)[DOI]
- Tran NH, "Fecal pollution source tracking toolbox for identification, evaluation and characterization of fecal contamination in receiving urban surface waters and groundwater", Science of the Total Environment, 538, pp.38~57 (2015)[DOI]
- Isobe KO, "Effect of environmental factors on the relationship between concentrations of coprostanol and fecal indicator bacteria in tropical(Mekong Delta)and temperate(Tokyo)freshwaters", Applied and Environmental Microbiology, 70(2), pp.814~821 (2004)[DOI]
- Truchado P, "Correlation between E. coli levels and the presence of foodborne pathogens in surface irrigation water : establishment of a sampling program", Water Research, 128, pp.226~233 (2018)[DOI]
- Savichtcheva O, "Relationships between Bacteroides 16S rRNA genetic markers and presence of bacterial enteric pathogens and conventional fecal indicators", Water Research, 41(16), pp.3615~3628 (2007)[DOI]
- Boyd CR, "Evaluating trauma care : the TRISS method, Trauma Score and the Injury Severity Score", The Journal of Trauma, 27(4), pp.370~378 (1987)
- Harrell FE, "Regression modeling strategies: with applications to linear models, logistic regression, and survival analysis", pp.215~330 (2001), Springer
- Berry MJ, "Data mining techniques: for marketing, sales, and customer relationship management", pp.227~230 (2004), John Wiley & Sons
- Cox DR, "The regression analysis of binary sequences", Journal of the Royal Statistical Society : Series B(Methodological), 20(2), pp.215~232 (1958)[DOI]
- Xue J, "Quantitative assessment of Naegleria fowleri and fecal indicator bacteria in brackish water of Lake Pontchartrain, Louisiana", Science of the Total Environment, 622, pp.8~16 (2018)[DOI]
- de Brauwere A, "Modeling fecal indicator bacteria concentrations in natural surface waters: a review", Critical Reviews in Environmental Science and Technology, 44(21), pp.2380~2453 (2014)[DOI]
- Goh SG, "Occurrence of microbial indicators, pathogenic bacteria and viruses in tropical surface waters subject to contrasting land use", Water Research, 150, pp.200~215 (2019)[DOI]
- Bojarczuk A, "The effect of anthropogenic and natural factors on the prevalence of physicochemical parameters of water and bacterial water quality indicators along the river Białka, southern Poland", Environmental Science and Pollution Research, 25(10), pp.10102~10114 (2018)[DOI]
- Buckerfield SJ, "Rainfall-driven E. coli transfer to the stream-conduit network observed through increasing spatial scales in mixed land-use paddy farming karst terrain", Water Research X, 5, pp.100038~ (2019)[DOI]
- Kleinheinz GT, "Effects of rainfall on E. coli concentrations at Door County, Wisconsin beaches", International Journal of Microbiology, 2009, pp.876050~ (2009)[DOI]
- Coulliette AD, "Impacts of rainfall on the water quality of the Newport River Estuary(Eastern North Carolina, USA)", Journal of Water and Health, 6(4), pp.473~482 (2008)[DOI]
- Traister E, "Variability of indicator bacteria at different time scales in the upper Hoosic River watershed", Environmental Science & Technology, 40(16), pp.4990~4995 (2006)[DOI]
- Shehane SD, "The influence of rainfall on the incidence of microbial faecal indicators and the dominant sources of faecal pollution in a Florida river", Journal of Applied Microbiology, 98(5), pp.1127~1136 (2005)[DOI]
- Auld H, "Heavy rainfall and waterborne disease outbreaks : the Walkerton example", Journal of Toxicology and Environmental Health, Part A, 67(20-22), pp.1879~1887 (2004)[DOI]
- Haile RW, "The health effects of swimming in ocean water contaminated by storm drain runoff", Epidemiology, 10, pp.355~363 (1999)[DOI]
- Mandrekar JN, "Receiver operating characteristic curve in diagnostic test assessment", Journal of Thoracic Oncology, 5(9), pp.1315~1316 (2010)[DOI]
