Heavy metals, including chromium, are associated with developed industrialization and technological processes, causing imbalanced ecosystems and severe health concerns. The current study is of supreme priority because there is no previous work that dealt with the modeling of the optimization of the biosorption process by the immobilized cells. The significant parameters (immobilized bacterial cells, contact time, and initial Cr6+ concentrations), affecting Cr6+ biosorption by immobilized Pseudomonas alcaliphila, was verified, using the Plackett–Burman matrix. For modeling the maximization of Cr6+ biosorption, a comparative approach was created between rotatable central composite design (RCCD) and artificial neural network (ANN) to choose the most fitted model that accurately predicts Cr6+ removal percent by immobilized cells. Experimental data of RCCD was employed to train a feed-forward multilayered perceptron ANN algorithm. The predictive competence of the ANN model was more precise than RCCD when forecasting the best appropriate wastewater treatment. After the biosorption, a new shiny large particle on the bead surface was noticed by the scanning electron microscopy, and an additional peak of Cr6+ was appeared by the energy dispersive X-ray analysis, confirming the role of the immobilized bacteria in the biosorption of Cr6+ ions.

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Chromium is one of the heavy metal pollutants that causing risky health issues when discharged into the aquatic ecosystems. The current investigation focused on the bioremoval of Cr 6+ depending on the bacterial sorption process by using Pseudomonas sp. NEWG-2 which was identified on the basis of morphological, cultural characteristics, 16S rRNA sequencing and phylogenetic analysis as Pseudomonas alcaliphila strain NEWG-2. It is clear from the FCCD experiments that the bacterium can grow normally and remove 96.60% of 200 mg/l of Cr 6+ using yeast extract (5.6 g/l), glucose (4.9 g/l), pH (7) for 48 h incubation period. SEM and EDS analyses proved that the Cr 6+ was biosorbed by P. alcaliphila NEWG-2. FTIR spectra indicated that the phenolic, carbonyl ester, acetyl, carboxylate, alkanes and carbonyl were the main groups involved in the chromium biosorption. Of the equilibrium isotherms models, the Langmuir model was more obedient, with a maximum uptake ( q max ) of 10 mg/g (bacterial-alginate beads), than the Freundlich one. The findings reveal the efficiency of P. alcaliphila NEWG-2 in Cr 6+ biosorption, with feasibility in the treatment of chromium-contaminated water as a green-technology tool. Interestingly, to the best of our knowledge, this is the first report on Cr 6+ biosorption process by P. alcaliphila .

Heavy metals are environmental pollutants affect the integrity and distribution of living organisms in the ecosystem and also humans across the food chain. The study targeted the removal of copper (Cu2+) from aqueous solutions, depending on the biosorption process. The bacterial candidate was identified using 16S rRNA sequencing and phylogenetic analysis, in addition to morphological and cultural properties as Azotobacter nigricans NEWG-1. The Box-Behnken design was applied to optimize copper removal by Azotobacter nigricans NEWG-1 and to study possible interactive effects between incubation periods, pH and initial CuSO4 concentration. The data obtained showed that the maximum copper removal percentage of 80.56% was reached at run no. 12, under the conditions of 200 mg/L CuSO4, 4 days’ incubation period, pH, 8.5. Whereas, the lowest Cu2+ removal (12.12%) was obtained at run no.1. Cells of Azotobacter nigricans NEWG-1 before and after copper biosorption were analyzed using FTIR, EDS and SEM. FTIR analysis indicates that several functional groups have participated in the biosorption of metal ions including hydroxyl, methylene, carbonyl, carboxylate groups. Moreover, the immobilized bacterial cells in sodium alginate-beads removed 82.35 ± 2.81% of copper from the aqueous solution, containing an initial concentration of 200 mg/L after 6 h. Azotobacter nigricans NEWG-1 proved to be an efficient biosorbent in the elimination of copper ions from environmental effluents, with advantages of feasibility, reliability and eco-friendly.

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The model showed adequate validity to be applied in a large-scale production of both lysine and glutamic acids.

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Saccharification of five cellulosic wastes, i.e. rice husks, wheat bran, corn cobs, wheat straw and rice straw by three cellulytic fungi, i.e. Aspergillus glaums MN1, Aspergillus oryzae MN2 and Penicillium purpurogenum MN3, during solid-state fermentation (SSF) was laboratory studied. Rice husks, wheat bran, and corn cobs were selected as inducers of glucose production in the tested fungi. An incubation interval of 10 days was optimal for glucose production. Maximal activities of the cellulases FP-ase, CMC-ase, and p-glucosidase were detected during SSF of rice husks by P. purpurogenum; however, a-amylase activity (7.2 U/g) was comparatively reduced. Meanwhile, the productivities of FP-ase, CMC-ase, and β-glucosidase were high during SSF of rice husks by A glaucus; however, they decreased during SSF of corn cobs by P. purpurogenum. Addition of rock phosphate (RP) (75 mg P(2)O(5)) decreased the pH of SSF media. (NH(4))(2)SO(4) was found to be less inducer of cellulytic enzymes, during SSF of rice husks by A. glaucus or A. oryzae; it also induced phytase production and solubilization of RP. The organic acids associated with saccharification of the wastes studied have also been investigated. The highest concentration of levulinic acid was detected (46.15 mg/g) during SSF of corn cobs by P. purpurogenum. Likewise, oxalic acid concentration was 43.20 mg/g during SSF of rice husks by P. purpurogenum.