Literature DB >> 32117154

Complex Interactions Between Weather, and Microbial and Physicochemical Water Quality Impact the Likelihood of Detecting Foodborne Pathogens in Agricultural Water.

Daniel Weller1, Natalie Brassill2, Channah Rock2, Renata Ivanek3, Erika Mudrak4, Sherry Roof1, Erika Ganda1, Martin Wiedmann1.   

Abstract

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.
Copyright © 2020 Weller, Brassill, Rock, Ivanek, Mudrak, Roof, Ganda and Wiedmann.

Entities:  

Keywords:  E. coli; Listeria; Salmonella; agricultural water; irrigation; produce safety

Year:  2020        PMID: 32117154      PMCID: PMC7015975          DOI: 10.3389/fmicb.2020.00134

Source DB:  PubMed          Journal:  Front Microbiol        ISSN: 1664-302X            Impact factor:   5.640


  10 in total

1.  Humans and Hoofed Livestock Are the Main Sources of Fecal Contamination of Rivers Used for Crop Irrigation: A Microbial Source Tracking Approach.

Authors:  Constanza Díaz-Gavidia; Carla Barría; Daniel L Weller; Marilia Salgado-Caxito; Erika M Estrada; Aníbal Araya; Leonardo Vera; Woutrina Smith; Minji Kim; Andrea I Moreno-Switt; Jorge Olivares-Pacheco; Aiko D Adell
Journal:  Front Microbiol       Date:  2022-06-30       Impact factor: 6.064

2.  Salmonella enterica Serovar Diversity, Distribution, and Prevalence in Public-Access Waters from a Central California Coastal Leafy Green-Growing Region from 2011 to 2016.

Authors:  Lisa Gorski; Anita S Liang; Samarpita Walker; Diana Carychao; Ashley Aviles Noriega; Robert E Mandrell; Michael B Cooley
Journal:  Appl Environ Microbiol       Date:  2021-12-15       Impact factor: 5.005

3.  Prevalence and Clonal Diversity of over 1,200 Listeria monocytogenes Isolates Collected from Public Access Waters near Produce Production Areas on the Central California Coast during 2011 to 2016.

Authors:  Lisa Gorski; Michael B Cooley; David Oryang; Diana Carychao; Kimberly Nguyen; Yan Luo; Leah Weinstein; Eric Brown; Marc Allard; Robert E Mandrell; Yi Chen
Journal:  Appl Environ Microbiol       Date:  2022-04-04       Impact factor: 5.005

4.  Interpretability Versus Accuracy: A Comparison of Machine Learning Models Built Using Different Algorithms, Performance Measures, and Features to Predict E. coli Levels in Agricultural Water.

Authors:  Daniel L Weller; Tanzy M T Love; Martin Wiedmann
Journal:  Front Artif Intell       Date:  2021-05-14

5.  Landscape, Water Quality, and Weather Factors Associated With an Increased Likelihood of Foodborne Pathogen Contamination of New York Streams Used to Source Water for Produce Production.

Authors:  Daniel Weller; Alexandra Belias; Hyatt Green; Sherry Roof; Martin Wiedmann
Journal:  Front Sustain Food Syst       Date:  2020-02-06

6.  Predictive Models May Complement or Provide an Alternative to Existing Strategies for Assessing the Enteric Pathogen Contamination Status of Northeastern Streams Used to Provide Water for Produce Production.

Authors:  Daniel L Weller; Tanzy M T Love; Alexandra Belias; Martin Wiedmann
Journal:  Front Sustain Food Syst       Date:  2020-10-06

7.  Environmental dissemination of pathogenic Listeria monocytogenes in flowing surface waters in Switzerland.

Authors:  Susanne Raschle; Roger Stephan; Marc J A Stevens; Nicole Cernela; Katrin Zurfluh; Francis Muchaamba; Magdalena Nüesch-Inderbinen
Journal:  Sci Rep       Date:  2021-04-27       Impact factor: 4.379

8.  Levels of Salmonella enterica and Listeria monocytogenes in Alternative Irrigation Water Vary Based on Water Source on the Eastern Shore of Maryland.

Authors:  Chanelle L Acheamfour; Salina Parveen; Fawzy Hashem; Manan Sharma; Megan E Gerdes; Eric B May; Koriante Rogers; Joseph Haymaker; Rico Duncan; Derek Foust; Maryam Taabodi; Eric T Handy; Cheryl East; Rhodel Bradshaw; Seongyun Kim; Shirley A Micallef; Mary Theresa Callahan; Sarah Allard; Brienna Anderson-Coughlin; Shani Craighead; Samantha Gartley; Adam Vanore; Kalmia E Kniel; Sultana Solaiman; Anthony Bui; Rianna Murray; Hillary A Craddock; Prachi Kulkarni; Rachel E Rosenberg Goldstein; Amy R Sapkota
Journal:  Microbiol Spectr       Date:  2021-10-06

9.  Pathogen and Surrogate Survival in Relation to Fecal Indicator Bacteria in Freshwater Mesocosms.

Authors:  Christopher A Baker; Giselle Almeida; Jung Ae Lee; Kristen E Gibson
Journal:  Appl Environ Microbiol       Date:  2021-07-13       Impact factor: 4.792

10.  Total Coliform and Generic E. coli Levels, and Salmonella Presence in Eight Experimental Aquaponics and Hydroponics Systems: A Brief Report Highlighting Exploratory Data.

Authors:  Daniel L Weller; Lauren Saylor; Paula Turkon
Journal:  Horticulturae       Date:  2020-07-30
  10 in total

北京卡尤迪生物科技股份有限公司 © 2022-2023.