Optimization Of Sorbitol Production Using Immobilized Of Lactobacillus Plantarum Strain (BAA-793) Via Solid State Fermentation (SSF) Process: Response Surface Methodology (RSM)

• Main Authors: Zuriana, Sidi Ahmad, Mimi Sakinah, A. M., Farhan, Mohd Said
• Format: Article
• Language: English
• Published: AENSI Publishing 2016
• Subjects: TP Chemical technology
• Online Access: http://umpir.ump.edu.my/id/eprint/17288/1/ftech-2016-mimi-Optimization%20Of%20Sorbitol%20Production%20Using%20Immobilized.pdf; http://umpir.ump.edu.my/id/eprint/17288/; http://www.ajbasweb.com/old/ajbas/2016/Special%20ICCEIB/90-100.pdf

Background: The process introduced in this work is the production of sorbitol via solid state fermentation (SSF) using immobilized cells of bacteria. The raw material that was used in this study is Meranti wood sawdust (MWS) that was obtained from Kilang Kayu Aman, Gambang Kuantan, Pahang. The bacterium used was Lactobacillus plantarum (BAA-793) and was immobilized using the entrapment technique (entrapped in sodium alginate). The pretreatment processes used for the treatment of the MWS to recover the cellulose from MWS are the physical pretreatment and chemical pretreatments. The last phase of this works was fermentation using solid state (SSF) process to convert the cellulose to sorbitol. Objective: This study aim to optimize sorbitol production via solid state fermentation (SSF) process using response surface methodology (RSM) and the central composite design (CCD) was used in order to reduce the total number of experiments; besides, to determine the best combination of parameters for optimization of the process. Results: The result shows that the interactions between parameters like moisture content and substrate amount have a very significant effect and the p-value was < 0.0001. The highest yield of sorbitol production (13.607 g/L) was obtained at the condition comprised of 50 % of moisture content, 4 h of fermentation time and 1.0 gram of substrate amount. Conclusion: The production of sorbitol will increase when all the process parameters in the solid state fermentation (SSF) process have been optimized. The RSM was also suitable for fitting a quadratic surface and it also helped to optimize the effective parameters with a minimum number of experiments as well as to analyze the interaction between the parameters.