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                                       Details for article 17 of 58 found articles
 
 
  Deficit irrigation and organic amendments can reduce dietary arsenic risk from rice: Introducing machine learning-based prediction models from field data
 
 
Title: Deficit irrigation and organic amendments can reduce dietary arsenic risk from rice: Introducing machine learning-based prediction models from field data
Author: Sengupta, Sudip
Bhattacharyya, Kallol
Mandal, Jajati
Bhattacharya, Parijat
Halder, Sanjay
Pari, Arnab
Appeared in: Agriculture, ecosystems and environment
Paging: Volume 319 () nr. C pages p.
Year: 2021
Contents:
Publisher: Elsevier B.V.
Source file: Elektronische Wetenschappelijke Tijdschriften
 
 

                             Details for article 17 of 58 found articles
 
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