Title: Design and optimisation of enzymatic saccharification for bioethanol production from Parthenium hysterophorus biomass using response surface methodology
Authors: Shivani Bhagwat; Anil Kumar
Addresses: School of Biotechnology, Devi Ahilya University, Khandwa Road, Indore-452001, India ' School of Biotechnology, Devi Ahilya University, Khandwa Road, Indore-452001, India
Abstract: The critical conditions for saccharification of polysaccharides from pre-treated biomass of Parthenium hysterophorus were carried out using response surface methodology based on Plackett-Burman and Box-Behnken design. In this study, temperature, moisture contents, pH, substrate loading, enzyme loading and incubation time were taken into consideration for optimisation of the conditions before fermentation. Using Plackett-Burman design, regression was predicted to be 95.26%. The adjusted regression and predicted regression were 89.58% and 72.71%, respectively indicating coincidence. Box-Behnken design was employed to investigate optimum conditions from the factors deduced by Plackett-Burman design (PBD). The parameters taken for the second order polynomial equation analysis were temperature, pH, enzyme loading and substrate loading, where regression was predicted as 0.97. The standard deviation and coefficient of variation (CV%) were calculated to be 24.31 and 7.80%, respectively. The predicted regression and adjusted regression were 0.86 and 0.94, respectively indicating good agreement with the predicted model. It was found that 30°C temperature, pH 4.5, enzyme loading of 1.0 ml and substrate loading of 1.0 g was the optimum conditions for maximum release of fermentable sugars. 8% of substrate loading rate was maintained for the experiment. Ethanol yield was 70% of the maximum theoretical yield based on pre-treated biomass after 72 h using optimum conditions.
Keywords: biofuel; Box-Behnken design; BBD; cellulose degradation; enzymatic saccharification; fermentation; gas chromatography; saccharomyces cerevisiae; Plackett-Burman design; PBD; statistical modelling; scanning electron microscopy.
International Journal of Renewable Energy Technology, 2017 Vol.8 No.2, pp.154 - 170
Received: 25 Oct 2016
Accepted: 11 Apr 2017
Published online: 25 Sep 2017 *