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Data and Code for evaluation of E. Coli in sediment for assessing irrigation water quality using machine learning

posted on 21.09.2022, 18:43 authored by Jennifer Guohong DuanJennifer Guohong Duan, Erfan Tousi, Patricia M. Gundy, Kelly Bright, Charles P. Gerba

This data repository contains the field collected data of sediment quality in irrigation canals. The Python code is to used in the paper entitled "Evaluation of E. Coli in Sediment for assessing irrigation water quality" published in the Science of the Total Environment Journal.

For inquiries regarding the contents of this dataset, please contact the Corresponding Author listed in the README.txt file. Administrative inquiries (e.g., removal requests, trouble downloading, etc.) can be directed to data-management@arizona.edu


The Center for Produce Safety grant #2019CPS04