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United States Department of Agriculture

Agricultural Research Service

Research Project: USING REMOTE SENSING & MODELING FOR EVALUATING HYDROLOGIC FLUXES, STATES, & CONSTITUENT TRANSPORT PROCESSES WITHIN AGRICULTURAL LANDSCAPES Title: Database on Pathogen and Indicator Organism Survival in Soils and other Environmental Media

Authors
item Pachepsky, Ludmila
item Sadeghi, Ali
item Shelton, Daniel
item Pachepsky, Yakov

Submitted to: American Society of Agronomy
Publication Type: Abstract Only
Publication Acceptance Date: April 16, 2009
Publication Date: October 31, 2009
Citation: Pachepsky, L., Sadeghi, A.M., Shelton, D.R., Pachepsky, Y.A. 2009. Database on pathogen and indicator organism survival in soils and other environmental media. American Society of Agronomy. http://a-c-s.confex.com/crops/2009am/webprogram/Paper51997.html

Technical Abstract: Data on survival of pathogen and indicator organism in soils, sediments, organic waste, and waters represent the key information for evaluating management practices and predicting fate and transport of the microorganisms. Such data are, in general, available, but are spread across thousands of publications in the variety of formats. The objective of this work was to develop a database that could be readily accessible, portable, expandable, and had improved search functions. We designed the SUME (Survival of Microorganisms in Environment) database structure with special attention to the selection of terms and parameters that can be used in common searches. The prototype database has been built and tested with data on E. coli, fecal coliforms, and Salmonella. The datasets are taken from scientific publications. Properties of the media, environmental parameters, experimental conditions, and source description are included. Facing the fact that the exponential die-off model is rarely applicable to the real-world environmental data, we included in the database the raw survival data and parameters of several survival models fitted to these data along with model performance statistics. The latter are based on both goodness-of-fit and the number of parameters as related to the total number of observations. The database has the relational structure and is implemented using Microsoft Access. Along with the single-query search, we currently experiment with the fuzzy searches based on the membership and neighborhood relationships. Further development of the SUME database will help to integrate and apply knowledge of the effect of environmental characteristics on microbiological quality and safety.

Last Modified: 12/21/2014
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