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首页> 外文期刊>Frontiers in Microbiology >Complex Interactions Between Weather, and Microbial and Physicochemical Water Quality Impact the Likelihood of Detecting Foodborne Pathogens in Agricultural Water
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Complex Interactions Between Weather, and Microbial and Physicochemical Water Quality Impact the Likelihood of Detecting Foodborne Pathogens in Agricultural Water

机译:天气与微生物和物理化学水质之间的复杂相互作用会影响检测农业水中食源性病原体的可能性

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Agricultural water is an important source of foodborne pathogens on produce farms. Managing water-associated risks does not lend itself to one-size-fits-all approaches due to the heterogeneous nature of freshwater environments. To improve our ability to develop location-specific risk management practices, a study was conducted in two produce-growing regions to (i) characterize the relationship between Escherichia coli levels and pathogen presence in agricultural water, and (ii) identify environmental factors associated with pathogen detection. Three AZ and six NY waterways were sampled longitudinally using 10-L grab samples (GS) and 24-h Moore swabs (MS). Regression showed that the likelihood of Salmonella detection (Odds Ratio [OR] = 2.18), and eaeA-stx codetection (OR = 6.49) was significantly greater for MS compared to GS, while the likelihood of detecting L. monocytogenes was not. Regression also showed that eaeA-stx codetection in AZ (OR = 50.2) and NY (OR = 18.4), and Salmonella detection in AZ (OR = 4.4) were significantly associated with E. coli levels, while Salmonella detection in NY was not. Random forest analysis indicated that interactions between environmental factors (e.g., rainfall, temperature, turbidity) (i) were associated with likelihood of pathogen detection and (ii) mediated the relationship between E. coli levels and likelihood of pathogen detection. Our findings suggest that (i) environmental heterogeneity, including interactions between factors, affects microbial water quality, and (ii) E. coli levels alone may not be a suitable indicator of food safety risks. Instead, targeted methods that utilize environmental and microbial data (e.g., models that use turbidity and E. coli levels to predict when there is a high or low risk of surface water being contaminated by pathogens) are needed to assess and mitigate the food safety risks associated with preharvest water use. By identifying environmental factors associated with an increased likelihood of detecting pathogens in agricultural water, this study provides information that (i) can be used to assess when pathogen contamination of agricultural water is likely to occur, and (ii) facilitate development of targeted interventions for individual water sources, providing an alternative to existing one-size-fits-all approaches.
机译:农业水是农产品农产品食品源病原体的重要来源。由于淡水环境的异质性质,管理水相关风险并未为单尺寸适合的方法提供。为了提高我们开发特定地点风险管理实践的能力,在两种生长的地区进行了一项研究,以(i)表征了大肠杆菌水平与农业水中病原体存在的关系,(ii)识别与之相关的环境因素病原体检测。使用10-L抓斗样品(GS)和24-H Moore拭子(MS)纵向对三AZ和六个纽约水道进行取样。回归表明,与GS相比,MS的沙门氏菌检测的可能性(O或= 6.18)和EAEA-STX译民(或= 6.49)显着更大,而检测L.单核细胞增生的可能性则不是。回归也表明,AZ(或= 50.2)和NY(或= 18.4)中的EAEA-STX译民和AZ(或= 4.4)中的沙门氏菌检测与大肠杆菌水平显着相关,而NY中的沙门氏菌检测则不是。随机森林分析表明,环境因素(例如,降雨,温度,浊度)(I)之间的相互作用与病原体检测的可能性与(ii)介导的大肠杆菌水平与病原体检测的可能性之间的关系。我们的研究结果表明(i)环境异质性,包括因子之间的相互作用,影响微生物水质,(ii)单独的大肠杆菌水平可能不是食品安全风险的合适指标。相反,需要使用环境和微生物数据的靶向方法(例如,使用浊度和大肠杆菌水平的模型来预测由病原体污染的地表水的高或低风险)来评估和减轻食品安全风险与预汽水使用相关。通过识别与检测农业水中病原体的可能性相关的环境因素,本研究提供了(i)可用于评估农业水可能发生的病原体污染,并促进目标干预措施的发展各个水源,为现有的单尺寸适合所有方法提供替代方案。

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