Application of Experimental Design Method for the Optimisation of Xanthan Gum Production from Pineapple Peels Using Xanthomonas Campestris via Submerged Fermentation

Xanthan gum is a major biopolymer which finds a lot of applications industrially and domestically. Biotechnological production of xanthan gum from waste biomass has been reported to be sustainable in terms of economics and viability. In this study, xanthan gum was produced from pineapple peels using Xanthomonas campestris by submerged fermentation. A  three-variable,  three-level  Box-Behnken  design  (BBD)  was  used  to develop  a  statistical  model  to study the effects of fermentation time, concentration of nitrogen (NH4NO3) and phosphorus (KH2PO4) on the amount of xanthan gum produced. Response surface methodology (RSM) was used to optimise these process variables. Results obtained showed that the model was statistically significant (p<0.0001) and did not show lack of fit (R2=0.989). The results also showed that xanthan gum production was positively influenced by high levels of phosphorus and low levels of nitrogen. Increasing the fermentation time also favoured the production of xanthan gum. Results obtained from RSM revealed that the optimum fermentation time, nitrogen and phosphorus concentration were 3 days, 2 g/L and 15 g/L respectively. Under these conditions, the xanthan concentration was obtained as 8.48 g/L. Validation of the model indicated no significant difference between predicted and experimental values.http://dx.doi.org/10.4314/njt.v34i3.1

Modelling and Simulation of the Batch Hydrolysis of Acetic Anhydride to Produce Acetic Acid

The kinetic modelling of the batch synthesis of acetic acid from acetic anhydride was investigated. The kinetic data of the reaction was obtained by conducting the hydrolysis reaction in a batch reactor. A dynamic model was formulated for this process and simulation was carried out using gPROMS® an advanced process modelling and simulation software. The developed model was validated against experimental data by estimating the kinetic parameter (reaction rate constant k=0.11302 min-1) and comparing simulation results with experimental data. Results obtained show that the formulated model was able to predict the experimental data to a high level of confidence. The dynamic behaviour of the reaction process was assessed by simulating the validated model at the initial state to obtain time trajectories of all the variables of interest. The model developed in this work will provide insight as to how the process responds under dynamic conditions and its amenability to control

Optimization of Bioethanol Production from Cassava Peels

The bioethanol production from waste is acquiring attraction as a strategy for increasing energy security. This study aims to optimize the production of ethanol from cassava peel using Box Bhenken experimental design. The total carbohydrate content of about 90% in cassava peel was subjected to enzymatic hydrolysis using Alpha-amylase followed by Simultaneous Saccharification and Fermentation (SSF) by Saccharomyces cerevisiae for bioethanol production. The production of bioethanol from cassava peels was investigated for 1-4 hours (hydrolysis time), 0.5\u20131.5mg/L (enzyme loading), and 1-5 days (incubation time). A statistical model was developed and validated to predict the yield of bioethanol after fermentation, and the Response Surface Methodology (RSM) was used to optimize the conditions. The results revealed that the maximum ethanol yield of 1.911% was obtained at the optimum hydrolysis time, enzyme loading, and incubation time (i.e. 2.5 hours, 1 mg/L, and 3 days respectively)