Machine Learning Approach to Predict Quality Parameters for Bacterial Consortium-Treated Hospital Wastewater and Phytotoxicity Assessment on Radish, Cauliflower, Hot Pepper, Rice and Wheat Crops

Machine Learning Approach to Predict Quality Parameters for Bacterial Consortium-Treated Hospital Wastewater and Phytotoxicity Assessment on Radish, Cauliflower, Hot Pepper, Rice and Wheat Crops

Raw hospital wastewater is a source of excessive heavy metals and pharmaceutical pollutants. In water-stressed countries such as Pakistan, the practice of unsafe reuse by local farmers for crop irrigation is of major concern. In our previous work, we developed a low-cost bacterial consortium wastewa...

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Bibliographic Details
Main Authors: Aneeba Rashid, Safdar A. Mirza, Ciara Keating, Umer Z. Ijaz, Sikander Ali, Luiza C. Campos
Format: Article
Language:English
Published: MDPI AG 2022-01-01
Series:Water
Subjects:
hospital wastewater
bacterial consortium treatment
machine learning
Random Forest classifier
phytotoxicity
crop irrigation
Online Access:https://www.mdpi.com/2073-4441/14/1/116

Internet

https://www.mdpi.com/2073-4441/14/1/116

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