GIS tools

GIS tools and approaches to food safety at the pre-harvest level

Improve GIS tools and approaches to reduce produce microbial food safety hazard introduction from agricultural water, environmental and animal sources at the pre-harvest level.

The goal is to develop models that allow for the prediction of times and locations with an increased risk of microbial hazards on-farm in different US growing regions. Models will be built using a combination of pathogen and indicator data, remotely sensed weather and adjacent land-use buffer data, and on-site physiochemical data. Outputs from model predictions will assist with region-specific guidance for industry on reducing microbial hazards on-farm from water and soil; as well as, educational programming for extension educators (targeted efforts).

Examples of previous work that illustrates applications of GIS tools and prediction models:

Weller, D. L., Love, T. M. T., Belias, A., & Wiedmann, M. 2020. 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 [Original Research]. Frontiers in Sustainable Food Systems, 4(151). https://doi.org/10.3389/fsufs.2020.561517
Weller, D., Belias, A., Green, H., Roof, S., & Wiedmann, M. 2020. 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 [Original Research]. Frontiers in Sustainable Food Systems, 3(124). https://doi.org/10.3389/fsufs.2019.00124
Weller, D., Shiwakoti, S., Bergholz, P., Grohn, Y., Wiedmann, M., & Strawn, L. K. 2016. Validation of a Previously Developed Geospatial Model That Predicts the Prevalence of Listeria monocytogenes in New York State Produce Fields. Applied and Environmental Microbiology, 82(3), 797-807. https://doi.org/10.1128/aem.03088-15
Murphy, C.M., D.L. Weller, T.M.T. Love, M.D. Danyluk, and L.K. Strawn. 2024. The Probability of Detecting Host-Specific Microbial Source Tracking Markers in Surface Waters Was Strongly Associated with Method and Season. Spectrum (ASM Journal). Accepted - 01972-24.
Cook, C., Diekman, C. M., Weller, D. L., Murphy, C. M., Hamilton, A. M., Ponder, Boyer, R.R., Rideout, S.L., Maguire, R.O., Danyluk, M.D. and Strawn, L. K. 2023. Factors associated with foodborne pathogens and indicator organisms in agricultural soils. Frontiers in Sustainable Food Systems, 7, 1269117.
Murphy, C.M., Weller, D.L., Ovissipour, R., Boyer, R. and Strawn, L.K., 2023. Spatial versus nonspatial variance in fecal indicator bacteria differs within and between ponds. Journal of Food Protection, 86(3), p.100045.
Murphy, C.M., Weller, D.L. and Strawn, L.K., 2024. Scale and detection method impacted Salmonella prevalence and diversity in ponds. Science of The Total Environment, 907, p.167812.
Weller, D.L., Love, T.M., Weller, D.E., Murphy, C.M. and Strawn, L.K., 2023. Scale of analysis drives the observed ratio of spatial to non-spatial variance in microbial water quality: insights from two decades of citizen science data. Journal of Applied Microbiology, 134(10), p.lxad210.
Weller, D.L., Murphy, C.M., Love, T.M., Danyluk, M.D. and Strawn, L.K., 2024. Methodological differences between studies confound one-size-fits-all approaches to managing surface waterways for food and water safety. Applied and Environmental Microbiology, 90(2), pp.e01835-23.
Diekman, C.M., Cook, C., Strawn, L.K. and Danyluk, M.D., 2024. Factors Associated with the Prevalence of Salmonella, Generic Escherichia coli, and Coliforms in Florida’s Agricultural Soils. Journal of Food Protection, 87(5), p.100265.
Murphy, C.M., Strawn, L.K., Chapin, T.K., McEgan, R., Gopidi, S., Friedrich, L., Goodridge, L.D., Weller, D.L., Schneider, K.R. and Danyluk, M.D., 2022. Factors associated with E. coli levels in and Salmonella contamination of agricultural water differed between north and South Florida waterways. Frontiers in Water, 3, p.750673.
Weller, D.L., Murphy, C.M., Johnson, S., Green, H., Michalenko, E.M., Love, T.M. and Strawn, L.K., 2022. Land use, weather, and water quality factors associated with fecal contamination of northeastern streams that span an urban-rural gradient. Frontiers in Water, 3, p.741676.

Other project relevant literature:

Broman, K. W., & Woo, K. H. 2018. Data Organization in Spreadsheets. The American Statistician, 72(1), 2-10. https://doi.org/10.1080/00031305.2017.1375989
Wickham, H. 2014. Tidy Data. 2014, 59(10), 23. https://doi.org/10.18637/jss.v059.i10
Murphy, C.M., D.L. Weller, M.D. Danyluk, and L.K. Strawn. 2024. Water Clarity: The Need for Standardized Data Collection and Methods for Assessing and Managing Water Quality. Food Safety Resource Clearinghouse. https://foodsafetyclearinghouse.org/resources/water-clarity-need-standardized-data-collection-and-methods-assessing-and-managing-water

Contact

Associate Professor, Department of Food Science & Technology at Virginia Tech.

Dr. Strawn holds both a research (50%) and extension (50%) appointment, both focus on reducing foodborne pathogen contamination throughout the produce supply chain. To pair both appointments, Dr. Strawn applies research/extension objectives that include both field (e.g., sampling commercial packinghouses or harvesters) and laboratory (e.g., benchtop, growth chamber). Discovery from these projects is disseminated directly to stakeholders through numerous extension activities. Her program empowers produce growers, packers, and other stakeholders in the supply chain to make risk-based decisions for their operations by providing them with science-based information and practical solutions to limit contamination events.

Email: laurakstrawn@vt.edu

Professor of Food Science at University of Florida.

Email: mddanyluk@ufl.edu