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Biotechnology

Year: 2015 | Volume: 14 | Issue: 2 | Page No.: 47-57
DOI: 10.3923/biotech.2015.47.57
An Innovative Synergism Between Aspergillus oryzae and Azotobacter chroococcum for Bioconversion of Cellulosic Biomass into Organic Acids under Restricted Nutritional Conditions Using Multi-Response Surface Optimization
Wesam I.A. Saber, Noura E. El-Naggar, Mohammad S. El-Hersh and Ayman Y. El-Khateeb

Abstract: The ready available biomass of Rice Straw (RS) and Faba Bean Straw (FBS) cause serious environmental problems to several countries. A novel synergistic technique was applied using Aspergillus oryzae S2 in association with Azotobacter chroococcum to mediate the bioconversion of RS, FBS and Rock Phosphate (RP) into organic acids. Six-days of fermentation were optimal for improving C/N ratio and biodegradation of Fermented Biomass (FM) without previous pretreatment. Box-Behnken factorial design, with three independent variables: RP, (NH4)2SO4 and FBS has been adopted for multi-response surface optimization for biodegradation of FM, using the Desirability function (D) approach. Solving the obtained equation model, determines the optimum levels of the independent variables at 120 mg P from RP, 10.39 mg (NH4)2SO4 and 0.92 g FBS per 10 g RS. These levels were validated, the responses were 37.11% RDW and 17.13, 4.70 and 12.43 mg g-1 FM for total, soluble and insoluble sugars, respectively, with D value of 0.892, indicating the efficacy of biodegradation process. The HPLC analysis of the filtrate of the optimized FM contained (mg g-1 FM) 15.270 citric and 13.715 succinic acids as the major acids, beside minor amounts of ascorbic, oxalic, itaconic and maleic acids. The fungal strain was molecularly identified as A. oryzae S2 (KJ487973).

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How to cite this article
Wesam I.A. Saber, Noura E. El-Naggar, Mohammad S. El-Hersh and Ayman Y. El-Khateeb, 2015. An Innovative Synergism Between Aspergillus oryzae and Azotobacter chroococcum for Bioconversion of Cellulosic Biomass into Organic Acids under Restricted Nutritional Conditions Using Multi-Response Surface Optimization. Biotechnology, 14: 47-57.

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