Optimization of Heavy Metals Biosorption via Artificial Neural Network: A Case Study of Cobalt (II) Sorption by Pseudomonas alcaliphila NEWG-2

Ashraf Elsayed; Zeiad Moussa; Salma Saleh Alrdahe; Maha Mohammed Alharbi; Abeer A Ghoniem; Ayman Y El-Khateeb; WesamEldin I A Saber

doi:10.3389/fmicb.2022.893603

Optimization of Heavy Metals Biosorption via Artificial Neural Network: A Case Study of Cobalt (II) Sorption by Pseudomonas alcaliphila NEWG-2

Front Microbiol. 2022 May 31:13:893603. doi: 10.3389/fmicb.2022.893603. eCollection 2022.

Authors

Ashraf Elsayed¹, Zeiad Moussa², Salma Saleh Alrdahe³, Maha Mohammed Alharbi³, Abeer A Ghoniem², Ayman Y El-Khateeb⁴, WesamEldin I A Saber²

Affiliations

¹ Botany Department, Faculty of Science, Mansoura University, Mansoura, Egypt.
² Department of Microbiology, Soils, Water and Environment Research Institute, Agricultural Research Center, Giza, Egypt.
³ Department of Biology, Faculty of Science, University of Tabuk, Tabuk, Saudi Arabia.
⁴ Department of Agricultural Chemistry, Faculty of Agriculture, Mansoura University, Mansoura, Egypt.

Abstract

The definitive screening design (DSD) and artificial neural network (ANN) were conducted for modeling the biosorption of Co(II) by Pseudomonas alcaliphila NEWG-2. Factors such as peptone, incubation time, pH, glycerol, glucose, K₂HPO₄, and initial cobalt had a significant effect on the biosorption process. MgSO₄ was the only insignificant factor. The DSD model was invalid and could not forecast the prediction of Co(II) removal, owing to the significant lack-of-fit (P < 0.0001). Decisively, the prediction ability of ANN was accurate with a prominent response for training (R² = 0.9779) and validation (R² = 0.9773) and lower errors. Applying the optimal levels of the tested variables obtained by the ANN model led to 96.32 ± 2.1% of cobalt bioremoval. During the biosorption process, Fourier transform infrared spectroscopy (FTIR), energy-dispersive X-ray spectroscopy, and scanning electron microscopy confirmed the sorption of Co(II) ions by P. alcaliphila. FTIR indicated the appearance of a new stretching vibration band formed with Co(II) ions at wavenumbers of 562, 530, and 531 cm^-1. The symmetric amino (NH₂) binding was also formed due to Co(II) sorption. Interestingly, throughout the revision of publications so far, no attempt has been conducted to optimize the biosorption of Co(II) by P. alcaliphila via DSD or ANN paradigm.

Keywords: Pseudomonas alcaliphila NEWG-2; artificial neural network; biosorption; cobalt; definitive screening design.