Artificial intelligence-based approaches to evaluate and optimize phytoremediation potential of in vitro regenerated aquatic macrophyte Ceratophyllum demersum L.

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dc.contributor.authorAasim, Muhammad
dc.contributor.authorAli, Seyid Amjad
dc.contributor.authorAydin, Senar
dc.contributor.authorBakhsh, Allah
dc.contributor.authorSogukpinar, Canan
dc.contributor.authorKaratas, Mehmet
dc.contributor.authorKhawar, Khalid Mahmood
dc.date.accessioned2024-02-23T13:59:33Z
dc.date.available2024-02-23T13:59:33Z
dc.date.issued2023
dc.departmentNEÜen_US
dc.description.abstractWater bodies or aquatic ecosystem are susceptible to heavy metal accumulation and can adversely affect the environment and human health especially in underdeveloped nations. Phytoremediation techniques of water bodies using aquatic plants or macrophytes are well established and are recognized as eco-friendly world over. Phytoremediation of heavy metals and other pollutants in aquatic environments can be achieved by using Ceratophyllum demersum L. - a well-known floating macrophyte. In vitro regenerated plants of C. demersum (7.5 g/L) were exposed to 24, 72, and 120 h to 0, 0.5, 1.0, 2.0, and 4.0 mg/L of cadmium (CdSO4 & BULL;8H(2)O) in water. Results revealed significantly different relationship in terms of Cd in water, Cd uptake by plants, bioconcentration factor (BCF), and Cd removal (%) from water. The study showed that Cd uptake by plants and BCF values increased significantly with exposure time. The highest BCF value (3776.50) was recorded for plant samples exposed to 2 mg/L Cd for 72 h. Application of all Cd concentrations and various exposure duration yielded Cd removal (%) between the ranges of 93.8 and 98.7%. These results were predicted through artificial intelligence-based models, namely, random forest (RF), extreme gradient boosting (XGBoost), and multilayer perceptron (MLP). The tested models predicted the results accurately, and the attained results were further validated via three different performance metrics. The optimal regression coefficient (R-2) for the models was recorded as 0.7970 (Cd water, mg/L), 0.9661 (Cd plants, mg/kg), 0.9797 bioconcentration factor (BCF), and 0.9996 (Cd removal, %), respectively. These achieved results suggest that in vitro regenerated C. demersum can be efficaciously used for phytoremediation of Cd-contaminated aquatic environments. Likewise, the proposed modeling of phytoremediation studies can further be employed more comprehensively in future studies aimed at data prediction and optimization.en_US
dc.description.sponsorshipScientific Research Council (BAP) of Necmettin Erbakan University, Konya, Turkey [171715001]en_US
dc.description.sponsorshipThis work was supported by Scientific Research Council (BAP) of Necmettin Erbakan University, Konya, Turkey with grant no. 171715001.en_US
dc.identifier.doi10.1007/s11356-022-25081-3
dc.identifier.endpage40217en_US
dc.identifier.issn0944-1344
dc.identifier.issn1614-7499
dc.identifier.issue14en_US
dc.identifier.pmid36607572en_US
dc.identifier.scopus2-s2.0-85145828900en_US
dc.identifier.scopusqualityQ1en_US
dc.identifier.startpage40206en_US
dc.identifier.urihttps://doi.org/10.1007/s11356-022-25081-3
dc.identifier.urihttps://hdl.handle.net/20.500.12452/11237
dc.identifier.volume30en_US
dc.identifier.wosWOS:000910150200004en_US
dc.indekslendigikaynakWeb of Scienceen_US
dc.indekslendigikaynakScopusen_US
dc.indekslendigikaynakPubMeden_US
dc.language.isoenen_US
dc.publisherSpringer Heidelbergen_US
dc.relation.ispartofEnvironmental Science And Pollution Researchen_US
dc.relation.publicationcategoryMakale - Uluslararası Hakemli Dergi - Kurum Öğretim Elemanıen_US
dc.rightsinfo:eu-repo/semantics/closedAccessen_US
dc.subjectAquaticen_US
dc.subjectCadmiumen_US
dc.subjectCeratophyllum Demersumen_US
dc.subjectIn Vitroen_US
dc.subjectPhytoremediationen_US
dc.titleArtificial intelligence-based approaches to evaluate and optimize phytoremediation potential of in vitro regenerated aquatic macrophyte Ceratophyllum demersum L.en_US
dc.typeArticleen_US

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