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http://dx.doi.org/10.5338/KJEA.2021.40.4.29

Investigation of Microbial Safety and Correlations Between the Level of Sanitary Indicator Bacteria and the Detection Ratio of Pathogens in Agricultural Water  

Hwang, Injun (Microbial Safety Division, National Institute of Agricultural Sciences, Rural Development Administration)
Lee, Tae Kwon (Department of Environment Engineering, Yonsei University)
Park, Daesoo (Microbial Safety Division, National Institute of Agricultural Sciences, Rural Development Administration)
Kim, Eunsun (Microbial Safety Division, National Institute of Agricultural Sciences, Rural Development Administration)
Choi, Song-Yi (Microbial Safety Division, National Institute of Agricultural Sciences, Rural Development Administration)
Hyun, Jeong-Eun (Microbial Safety Division, National Institute of Agricultural Sciences, Rural Development Administration)
Rajalingam, Nagendran (Microbial Safety Division, National Institute of Agricultural Sciences, Rural Development Administration)
Kim, Se-Ri (Microbial Safety Division, National Institute of Agricultural Sciences, Rural Development Administration)
Cho, Min (Division of Biotechnology, Chonbuk National University)
Publication Information
Korean Journal of Environmental Agriculture / v.40, no.4, 2021 , pp. 248-259 More about this Journal
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 coliform 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.
Keywords
Agricultural water; Food-borne pathogens; Indicator bacteria; Monitoring; Water quality;
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