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

The 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 network-based models are developed for prediction of batch Cr(VI) bioreduction using the cells immobilized on glass and Ca-alginate beads.