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.

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作者： Daniel L,Weller ^[1] ; Tanzy M T,Love ^[2] ; Alexandra,Belias ^[3] ; Martin,Wiedmann ^[3]

作者单位： Department of Food Science, Cornell University, Ithaca, NY, United States.;Department of Biostatistics and Computational Biology, University of Rochester, Rochester, NY, United States. ^[1] Department of Biostatistics and Computational Biology, University of Rochester, Rochester, NY, United States. ^[2] Department of Food Science, Cornell University, Ithaca, NY, United States. ^[3]

关键词 E. coli Salmonella agricultural water eaeA machine learning predictive model stx

DOI 10.3389/fsufs.2020.561517

PMID 33791594

发布时间 2025-01-18

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Frontiers in sustainable food systems

2020年4卷

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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.

Frontiers in sustainable food systems

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Frontiers in sustainable food systems

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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.

Frontiers in sustainable food systems

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Frontiers in sustainable food systems

相关期刊

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