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Deficit irrigation and organic amendments can reduce dietary arsenic risk from rice: Introducing machine learning-based prediction models from field data

Sudip Sengupta, Kallol Bhattacharyya, Jajati Mandal, P. Bhattacharya, Sanjay Halder, Arnab Pari

2021Agriculture Ecosystems & Environment83 citationsDOIOpen Access PDF

Topics & Concepts

IrrigationAgricultural engineeringField (mathematics)Environmental sciencePaddy fieldArsenicRisk assessmentAgronomyComputer scienceMathematicsEngineeringChemistryBiologyPure mathematicsComputer securityOrganic chemistryArsenic contamination and mitigationHeavy metals in environment
Deficit irrigation and organic amendments can reduce dietary arsenic risk from rice: Introducing machine learning-based prediction models from field data | Litcius