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
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Rashid, A.; Mirza, S.A.; Keating, C.; Ijaz, U.Z.; Ali, S.; Campos, L.C. 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. Water 2022, 14, 116. https://doi.org/10.3390/w14010116
Rashid A, Mirza SA, Keating C, Ijaz UZ, Ali S, Campos LC. 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. Water. 2022; 14(1):116. https://doi.org/10.3390/w14010116
Chicago/Turabian StyleRashid, Aneeba, Safdar A. Mirza, Ciara Keating, Umer Z. Ijaz, Sikander Ali, and Luiza C. Campos. 2022. "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" Water 14, no. 1: 116. https://doi.org/10.3390/w14010116