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

  • Erfan Ghasemi Tousi (Creator)
  • Jennifer Guohong Duan (Creator)
  • Patricia M. Gundy (Creator)
  • Kelly R. Bright (Creator)
  • Charles P. Gerba (Creator)

Dataset

Description

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 [email protected]
Date made available2022
PublisherUniversity of Arizona Research Data Repository

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