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Ponte Academic Journal
Apr 2021, Volume 77, Issue 4

OPTIMIZATION OF ENDOGLUCANASE PRODUCTION FROM SAROCLADIUM KILIENSE STRAIN BBV1 UNDER SOLID STATE FERMENTATION, USING RESPONSE SURFACE METHODOLOGY

Author(s): Gahfif Ouahiba ,Souagui Yasmina, Bettache Azzeddine, Azzouz Zahra, Sadrati Nouari

J. Ponte - Apr 2021 - Volume 77 - Issue 4
doi: 10.21506/j.ponte.2021.4.3



Abstract:
Cellulases are group of enzymes that hydrolyse celluloses, they stimulate a great interest due to their large industrial and biotechnological applications. Forty fungal strains isolated from Algerian soil rich in organic matter were screened for cellulolytic activity by agar plate method. After screening the BbV1 isolate showed high and most interesting cellulose production, based on the morphological and molecular identification, the BbV1 isolate was identified as Sarocladium kiliense species. The optimization of endoglucanase production by Sarocladium kiliense strain BbV1 from a wheat straw as a solid-state fermentation (SSF) substrate, was performed using both one factor at a time (OFAT) and response surface methodology (RSM) approaches. The results of the preliminary study by OFAT revealed that the incubation time, moisture, temperature, and inoculum size have significantly influenced the endoglucanase production, the optimum of these parameters are respectively: 8 days, 90%, 26 °C and 105 spores/g with a maximum activity value of 12,13 U/gds. The Box Benckhen design was used to improve the endoglucanase production by studying the interaction effect between the selected parameters. The analysis of variance was carried out and endoglucanase production was explained with a mathematical equation as a function of the four variables (incubation time, moisture, temperature, and inoculum size) with three levels (-1, 0, +1). The optimal endoglucanase activity of 15,03 U/gds was achieved under the following conditions: 10 days of fermentation time, a moisture of 60%, incubation temperature of 24 °C and inoculum size of 1.9 x 105 spores/g. RSM has proven to be an effective method to obtain optimal parameters for enzyme production.
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