2014
DOI: 10.1016/j.bej.2014.01.004
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Application of artificial neural network for the prediction of biosorption capacity of immobilized Bacillus subtilis for the removal of cadmium ions from aqueous solution

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Cited by 49 publications
(17 citation statements)
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“…The cell wall differs considerably from Gram-negative to Gram-positive bacteria, which is well documented in the literature [50][51][52]. Ahmad et al [54] investigated the biosorption capacity of Bacillus subtilis biomass immobilized in calcium alginate, in batch mode toward Cd(II) ions. Ahmad et al [54] investigated the biosorption capacity of Bacillus subtilis biomass immobilized in calcium alginate, in batch mode toward Cd(II) ions.…”
Section: Immobilized Bacterial Biosorbentsmentioning
confidence: 99%
“…The cell wall differs considerably from Gram-negative to Gram-positive bacteria, which is well documented in the literature [50][51][52]. Ahmad et al [54] investigated the biosorption capacity of Bacillus subtilis biomass immobilized in calcium alginate, in batch mode toward Cd(II) ions. Ahmad et al [54] investigated the biosorption capacity of Bacillus subtilis biomass immobilized in calcium alginate, in batch mode toward Cd(II) ions.…”
Section: Immobilized Bacterial Biosorbentsmentioning
confidence: 99%
“…strains can be applied to the improvement of soil fertility, treatment of wastewater and environmental restoration of metal mining areas. For instance, Bacillus licheniformis can be utilized in the treatment of wastewater (Shih et al, 2001); Bacillus cereus and Bacillus subtilis have been extensively studied for their ability to adsorb the heavy metals chromium and cadmium (Ahmad et al, 2014;Naik et al, 2012). Moreover, B. thuringiensis has been applied to control insect pests of plants due to its higher expression of insecticidal (Cry) proteins (Betz et al, 2000).…”
Section: Plant Growth Promotion By Strain Nl-11mentioning
confidence: 99%
“…ANN modeling has been successfully applied for biosorption in the past few years (Ahmad et al, 2014;Bingol et al, 2012;Shojaeimehr et al, 2014;Mandal et al, 2015;Roy et al, 2014) The present study investigates the application of response surface methodology and artificial neural network approaches to predict biosorption capacity of waste flax meal for the removal of copper(II) ions from aqueous solution. Polish industry is largely based on the processing of copper, thus methods of removal as well as recovery of this metal are widely investigated by Polish scientists.…”
Section: Introductionmentioning
confidence: 99%