Experimental investigation and artificial neural network-based modeling of batch reduction of hexavalent chromium by immobilized cells of newly isolated strain of chromium-resistant bacteria

dc.contributor.authorShetty K, K.V.
dc.contributor.authorNamitha, L.
dc.contributor.authorRao, S.N.
dc.contributor.authorNarayani, M.
dc.date.accessioned2026-02-05T09:35:19Z
dc.date.issued2012
dc.description.abstractThe batch bioreduction of Cr(VI) by the cells of newly isolated chromium-resistant Acinetobacter sp. bacteria, immobilized on glass beads and Ca-alginate beads, was investigated. The rate of reduction and percentage reduction of Cr(VI) decrease with the increase in initial Cr(VI) concentration, indicating the inhibitory effect of Cr(VI). Efficiency of bioreduction can be improved by increasing the bioparticle loading or the initial biomass loading. Glass bioparticles have shown better performance as compared to Ca-alginate bioparticles in terms of batch Cr(VI) reduction achieved and the rate of reduction. Glass beads may be considered as better cell carrier particles for immobilization as compared to Ca-alginate beads. Around 90% reduction of 80 ppm Cr(VI) could be achieved after 24 h with initial biomass loading of 14.6 mg on glass beads. Artificial neural networkbased models are developed for prediction of batch Cr(VI) bioreduction using the cells immobilized on glass and Ca-alginate beads. © Springer Science+Business Media B.V. 2011.
dc.identifier.citationWater, Air, and Soil Pollution, 2012, 223, 4, pp. 1877-1893
dc.identifier.issn496979
dc.identifier.urihttps://doi.org/10.1007/s11270-011-0992-5
dc.identifier.urihttps://idr.nitk.ac.in/handle/123456789/27017
dc.subjectAcinetobacter sp
dc.subjectBiomass loading
dc.subjectBioparticles
dc.subjectBioreductions
dc.subjectCa-alginate
dc.subjectCa-alginate bead
dc.subjectCell carrier
dc.subjectCr reductions
dc.subjectExperimental investigations
dc.subjectGlass bead
dc.subjectHexavalent chromium
dc.subjectImmobilized cells
dc.subjectInhibitory effect
dc.subjectIsolated strains
dc.subjectNetwork-based
dc.subjectNetwork-based modeling
dc.subjectRate of reduction
dc.subjectAlginate
dc.subjectCalcium
dc.subjectCells
dc.subjectChromium
dc.subjectChromium compounds
dc.subjectGlass
dc.subjectGranular materials
dc.subjectLoading
dc.subjectNeural networks
dc.subjectCell immobilization
dc.subjectcalcium alginate
dc.subjectchromium
dc.subjectartificial neural network
dc.subjectbacterium
dc.subjectbiomass
dc.subjectconcentration (composition)
dc.subjectexperimental study
dc.subjectglass
dc.subjectimmobilization
dc.subjectmodeling
dc.subjectreduction
dc.subjectAcinetobacter
dc.subjectantibiotic resistance
dc.subjectarticle
dc.subjectbacterial strain
dc.subjectbacterium isolate
dc.subjectbatch process
dc.subjectchemical structure
dc.subjectconcentration response
dc.subjectcontrolled study
dc.subjecteffluent
dc.subjectexperimentation
dc.subjectheavy metal removal
dc.subjectimmobilized cell
dc.subjectnonhuman
dc.subjectprediction
dc.subjectprocess model
dc.subjectAcinetobacter sp.
dc.titleExperimental investigation and artificial neural network-based modeling of batch reduction of hexavalent chromium by immobilized cells of newly isolated strain of chromium-resistant bacteria

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