Data from: Temporal and agricultural factors influence E. coli survival in soil and transfer to cucumbers
Principal Investigator(s): View help for Principal Investigator(s) US Department of Agriculture; National Agricultural Library
Version: View help for Version V1
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Project Citation:
US Department of Agriculture, and National Agricultural Library. Data from: Temporal and agricultural factors influence E. coli survival in soil and transfer to cucumbers. Ann Arbor, MI: Inter-university Consortium for Political and Social Research [distributor], 2026-06-27. https://doi.org/10.3886/E250436V1
Project Description
Project Title:
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Data from: Temporal and agricultural factors influence E. coli survival in soil and transfer to cucumbers
Summary:
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Escherichia coli survival in soils containing either composted poultry litter (CPL), heat-treated poultry pellets (HTPP), poultry litter (PL) or unamended (chemical fertilizer). Test plots were either covered with plastic mulch (M) or not mulched (NoM). The study was conducted in 2018 and 2019 during cucumber growing seasons at the University of Delaware research farm and each study lasted 120 days. Data from the current study were collected to examine the survival of non-pathogenic Escherichia coli and transfer to cucumbers grown in same field in two separate years. Soil moisture, total nitrogen, nitrate, total carbon, soluble carbon, soluble solids, rainfall, soil temperature and air temperature, along with the number of days needed for E. coli to decline by 4 log CFU/gdw, were included in random forest models used to a) predict 4-log declines of E. coli inoculated to soils and b) transfer of E. coli to cucumbers from soils with different biological soil amendments.
The data included here are specifically for other investigators to use to make different forms or versions of three different statistical models used in the submitted manuscript. Data for three models are included:
1) Dpi4log, the number of days needed for E. coli levels in various combinations of year, amendment and mulch, were calculated by applying sigmoidal (single, double, triple, or quadruple) model to E. coli data collected over time.
2) A random forest model using soil and weather data was used to determine which factors listed above best predicted dpi4log values. This model accounted for 98% of the observed variance.
3) A random forest model using soil and weather data, along with dpi4log, was used to predict transfer of E. coli to soils from cucumbers (log MPN/cucumber). This model accounted for approximately 63% of the variance in the study.
Resources in this dataset:
Resource Title: Graph of E. coli levels over 120 days in soils under various conditions. File Name: Graphs of Fitted Sigmoidal Regression Models onto Observed gEclog vs DPI.pdfResource Description: Graph of *E. coli* levels in 24 different combinations of year, amendment, and mulch status over 120 days
Resource Title: Graph of E. coli levels over 120 days in soils under various conditions.
File Name: Graphs of Fitted Sigmoidal Regression Models onto Observed gEclog vs DPI.pdf
Resource Description: Graph of *E. coli* levels in 24 different combinations of year, amendment, and mulch status over 120 days
Resource Title: Comparison of actual model-generated log CFU/gdw data . File Name: Observed and Sigmoidal Model Predicted gEcLog values - Daily Increment.csvResource Description: Comparison of sigmoidal model-generated log CFU/gdw vs observed data
Resource Title: Comparison of actual model-generated log CFU/gdw data .
File Name: Observed and Sigmoidal Model Predicted gEcLog values - Daily Increment.csv
Resource Description: Comparison of sigmoidal model-generated log CFU/gdw vs observed data
Resource Title: Soil temperature, Air temperature and Cumulative Rainfall observed in 2018 and 2019. File Name: Soil air temp cumulative rainfall 2018 2019.xlsxResource Description: These are the climate data used to inform and predict E. coli survival in soils containing biological and chemical fertilizer
Resource Title: Soil temperature, Air temperature and Cumulative Rainfall observed in 2018 and 2019.
File Name: Soil air temp cumulative rainfall 2018 2019.xlsx
Resource Description: These are the climate data used to inform and predict E. coli survival in soils containing biological and chemical fertilizer
Resource Title: Data set used in Random Forest model to predict transfer of E. coli from soils to cucumber fruits . File Name: UD ARS Cucumber Study Consolidated Data Version 2 Single Transference Column Original Data Scale.csvResource Description: This data set includes the sigmoidal model-estimated values of dpi4log (the number of days needed to achieve 4 log decline in E. coli levels) in this model
Resource Title: Data set used in Random Forest model to predict transfer of E. coli from soils to cucumber fruits .
File Name: UD ARS Cucumber Study Consolidated Data Version 2 Single Transference Column Original Data Scale.csv
Resource Description: This data set includes the sigmoidal model-estimated values of dpi4log (the number of days needed to achieve 4 log decline in E. coli levels) in this model
Resource Title: Dataset used in Random Forest model to identify variables and factors which predict dpi4log values of E. coli in soils containing biological soil amendment of animal origin. File Name: Formatted Soil Data for Random Forest Analysis.xlsxResource Description: Dataset used in the Random Forest model to identify variables and factors which predict dpi4log values - the number of days needed to observe a 4 log reduction, estimated by sigmoidal modeling of collected E. coli data - of E. coli in soils containing biological soil amendment of animal origin
Resource Title: Dataset used in Random Forest model to identify variables and factors which predict dpi4log values of E. coli in soils containing biological soil amendment of animal origin.
File Name: Formatted Soil Data for Random Forest Analysis.xlsx
Resource Description: Dataset used in the Random Forest model to identify variables and factors which predict dpi4log values - the number of days needed to observe a 4 log reduction, estimated by sigmoidal modeling of collected E. coli data - of E. coli in soils containing biological soil amendment of animal origin
Resources in this dataset:
Resource Title: Graph of E. coli levels over 120 days in soils under various conditions. File Name: Graphs of Fitted Sigmoidal Regression Models onto Observed gEclog vs DPI.pdfResource Description: Graph of *E. coli* levels in 24 different combinations of year, amendment, and mulch status over 120 days
Resource Title: Graph of E. coli levels over 120 days in soils under various conditions.
File Name: Graphs of Fitted Sigmoidal Regression Models onto Observed gEclog vs DPI.pdf
Resource Description: Graph of *E. coli* levels in 24 different combinations of year, amendment, and mulch status over 120 days
Resource Title: Comparison of actual model-generated log CFU/gdw data . File Name: Observed and Sigmoidal Model Predicted gEcLog values - Daily Increment.csvResource Description: Comparison of sigmoidal model-generated log CFU/gdw vs observed data
Resource Title: Comparison of actual model-generated log CFU/gdw data .
File Name: Observed and Sigmoidal Model Predicted gEcLog values - Daily Increment.csv
Resource Description: Comparison of sigmoidal model-generated log CFU/gdw vs observed data
Resource Title: Soil temperature, Air temperature and Cumulative Rainfall observed in 2018 and 2019. File Name: Soil air temp cumulative rainfall 2018 2019.xlsxResource Description: These are the climate data used to inform and predict E. coli survival in soils containing biological and chemical fertilizer
Resource Title: Soil temperature, Air temperature and Cumulative Rainfall observed in 2018 and 2019.
File Name: Soil air temp cumulative rainfall 2018 2019.xlsx
Resource Description: These are the climate data used to inform and predict E. coli survival in soils containing biological and chemical fertilizer
Resource Title: Data set used in Random Forest model to predict transfer of E. coli from soils to cucumber fruits . File Name: UD ARS Cucumber Study Consolidated Data Version 2 Single Transference Column Original Data Scale.csvResource Description: This data set includes the sigmoidal model-estimated values of dpi4log (the number of days needed to achieve 4 log decline in E. coli levels) in this model
Resource Title: Data set used in Random Forest model to predict transfer of E. coli from soils to cucumber fruits .
File Name: UD ARS Cucumber Study Consolidated Data Version 2 Single Transference Column Original Data Scale.csv
Resource Description: This data set includes the sigmoidal model-estimated values of dpi4log (the number of days needed to achieve 4 log decline in E. coli levels) in this model
Resource Title: Dataset used in Random Forest model to identify variables and factors which predict dpi4log values of E. coli in soils containing biological soil amendment of animal origin. File Name: Formatted Soil Data for Random Forest Analysis.xlsxResource Description: Dataset used in the Random Forest model to identify variables and factors which predict dpi4log values - the number of days needed to observe a 4 log reduction, estimated by sigmoidal modeling of collected E. coli data - of E. coli in soils containing biological soil amendment of animal origin
Resource Title: Dataset used in Random Forest model to identify variables and factors which predict dpi4log values of E. coli in soils containing biological soil amendment of animal origin.
File Name: Formatted Soil Data for Random Forest Analysis.xlsx
Resource Description: Dataset used in the Random Forest model to identify variables and factors which predict dpi4log values - the number of days needed to observe a 4 log reduction, estimated by sigmoidal modeling of collected E. coli data - of E. coli in soils containing biological soil amendment of animal origin
Original Distribution URL:
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https://agdatacommons.nal.usda.gov/articles/dataset/Data_from_Temporal_and_agricultural_factors_influence_E_coli_survival_in_soil_and_transfer_to_cucumbers/24665826
Scope of Project
Subject Terms:
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Escherichia coli;
Agroecosystems & Environment Soil;
Food Safety;
biological soil amendments;
poultry litter;
plastic mulch;
rainfall;
NP108;
data.gov;
ARS
Geographic Coverage:
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Delaware
Data Type(s):
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observational data
Collection Notes:
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DOI: 10.15482/USDA.ADC/1520517
Citation: Sharma, Manan; Litt, Pushpinder K.; Vinyard, Bryan T.; Kniel, Kali E. (2020). Data from: Temporal and agricultural factors influence E. coli survival in soil and transfer to cucumbers. Ag Data Commons. https://doi.org/10.15482/USDA.ADC/1520517 (Downloaded 2026-06-26)
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