초록
<P><B>Abstract</B></P> <P>The xylanase production from <I>Thermomyces lanuginosus</I> VAPS-24 has been optimized using OFAT (One factor at a time) approach using agro-industrial substrates. Further, central composite design (CCD) has been employed to optimize various process parameters such as temperature (45–55°C), carbon source concentration (1.5–2.5%), fermentation time (72–120h) and production medium pH (6−8). Maximum xylanase yield after RSM optimization was approximately double (119.91±2.53UmL<SUP>−1</SUP>) than un-optimized conditions (61.09±0.91UmL<SUP>−1</SUP>). Several hybrid statistical tools such as Genetic Algorithm-Response Surface Methodology (GA-RSM), Artificial Neural Network (ANN), Genetic Algorithm-Artificial Neural Network (GA-ANN) were employed to obtain more optimized process parameters to maximize the xylanase production and observed an increase of 10.50% xylanase production (132.51±3.27UmL<SUP>−1</SUP>) as compared to RSM response (119.91±2.53UmL<SUP>−1</SUP>). The various pretreated and untreated agricultural residues were subjected to saccharification by using crude xylanase in which the pretreated rice straw yielded maximum fermentable sugars 126.89mgg<SUP>−1</SUP>.</P> <P><B>Highlights</B></P> <P> <UL> <LI> Xylanase from <I>T. lanuginosus</I> VAPS-24 was optimized using OFAT and CCD approach. </LI> <LI> Xylanase yield after optimization was reported as double (i.e. 112.87UmL<SUP>−1</SUP>). </LI> <LI> GA-RSM, ANN, GA-ANN resulted high xylanase yield (i.e. 9.94% increase). </LI> <LI> Saccharification of agro-residues yielded sugars 126.89mgg<SUP>−1</SUP> with rice straw. </LI> <LI> This xylanase proves its industrial applicability for saccharification. </LI> </UL> </P> <P><B>Graphical abstract</B></P> <P>[DISPLAY OMISSION]</P>