.png){kind=icon}
.png){kind=icon}
Return
AI-assisted bioprocessing for sewage wastewater treatment using cyanobacteria-graphene nanohybrid for exploring anti-oxidant analysis and their impact on seed germination of Vigna radiata
.png){kind=icon}
PRE
AI
A
J
S
D
K
J
P
U
K
S
DOI：10.1016/j.procbio.2026.03.013.png)
.png){kind=icon}
Original request for help.png){kind=icon}
Share.png){kind=icon}
Save
Abstract
En 中文
The advent of amine-functionalized graphene (AF-G), has shown significant potential for enhancing cyanobacterial photosynthesis while simultaneously removing toxicants from wastewater and producing high-value metabolites. This study investigated the synergistic effect of AF-G and the cyanobacterium Synechocystis sp. SS123_AK to improve nutrient removal alongside biomass and lipid production. 25 ppm AF-G achieved 95.07%, 93.24%, 97.67%, and 98.46% of total nitrogen, total phosphorus, total organic carbon and chemical oxygen demand, with augmented biomass and lipid on the 10th day, outperforming pristine graphene (P-G), where the initial concentrations of TN, TP, TOC and COD in SWW (before treatment) was experimentally analysed as 164.01, 180.36, 351.39 and 405.6 mg/L. Various regression-based machine learning models were applied to predict the optical density of cyanobacteria grown with AF-G and P-G where, the stacked ensemble model achieved the highest performance with an R2 of 0.9839 and low MAE, confirming strong predictive capability for biomass estimation. Lipid profiling revealed a high yield of PUFA including C 18:3, 22:5, 22:6 etc. followed by MUFA and SFA, which were further assessed for antioxidant potential in human neutrophils stimulated by E. coli and S. aureus. Additionally, treated water supported the irrigation of Vigna radiata seeds, demonstrating its agricultural potential.
Keywords:
Cyanobacteria
Phycoremediation
Amine graphene
Fatty acids
Antioxidant
Machine learning
Journal
IF:
4
Papers:
8.1K
Citations:
2.0W
Organization
Cited Papers