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Modeling the Environmental Biology of Foodborne Pathogens to Support the Safety of Local Fresh Food in the Upper Great Plains

Objective

<p>Objective 1. Empirically measure and model the farm and landscape scale factors constraining abundance of foodborne pathogens.Hypothesis: The abundance of foodborne pathogens in croplands will vary spatially according to environmental factors among farms and within them. Some farms will have higher baseline levels of foodborne pathogens.</p><p>Objective 2. Empirically measure and model the farm and landscape scale factors constraining the dispersal of foodborne pathogens.Hypothesis: Farm fields in landscapes with greater density of tree cover or closer proximity to water bodies will exhibit greater connectivity for foodborne pathogens to other locations on the landscape.</p><p>Objective 3. Link adaptive variation in foodborne pathogens to their prevalence in farm environments.</p><p>Hypothesis: The most prevalent foodborne pathogen strains in soils and sediments will have adaptive genetic polymorphisms in membrane stress response genes, stress response regulators and outer membrane proteins. <p>

More information

This work will be used to support local food and community supported agriculture in North Dakota by providing growers with much needed information on how to manage their lands to ensure the safest food possible. Engaging in thinking about food safety in farm fields is important for growers in North Dakota, because fresh fruits and vegetables can reach large numbers of families, including communities like schools and nursing homes that are populated by people who are especially vulnerable to severe outcomes from foodborne illnesses. The most likely economic impacts of this research for North Dakota are through improvements to public health both through improved nutrition and reduced medical and business costs-associated with food safety practices and foodborne illnesses. A grower who can say that they have followed the Good Agricultural Practices and FDA recommendations is: a) less likely to grow food that ultimately causes illness, b) open to a larger customer base, including large grocery store chains that benefit from selling locally sourced food, and c) less vulnerable to civil suits associated with foodborne illness. Conversely, uncertainties about good food safety practices, regulations and audit requirements from retailers are among the biggest hurdles to entering the local food marketplace. This begs the question, "how does this research relate to GAPs and the proposed produce safety rule?" The proposed work directly tests the environmental behavior of foodborne pathogens in North Dakota, thus verifying the value of GAPs and Produce Safety Rule recommendations for growers in North Dakota. But a second, more direct benefit to growers, packers and retailers in North Dakota can be realized by translating our results directly into a GIS mapping algorithm. Such an algorithm can: a) make predictions about which parts of a grower's land, if any, are especially vulnerable to pathogen contamination, and b) be used to devise harvesting and planting strategies that will minimize chances for contamination. Work on this has already begun in my laboratory, with an initial version of a mapping algorithm that predicts the prevalence of Listeria monocytogenes in mixed-use agricultural landscapes in the Northeastern United States.

Investigators
Bergholz, Peter W
Institution
North Dakota State University
Start date
2015
End date
2019
Project number
ND02428
Accession number
1008073