کد مقاله | کد نشریه | سال انتشار | مقاله انگلیسی | نسخه تمام متن |
---|---|---|---|---|
8842592 | 1615776 | 2017 | 15 صفحه PDF | دانلود رایگان |
عنوان انگلیسی مقاله ISI
Optimizing culture conditions for production of intra and extracellular inulinase and invertase from Aspergillus niger ATCC 20611 by response surface methodology (RSM)
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کلمات کلیدی
موضوعات مرتبط
علوم زیستی و بیوفناوری
ایمنی شناسی و میکروب شناسی
میکروبیولوژی و بیوتکنولوژی کاربردی
پیش نمایش صفحه اول مقاله
چکیده انگلیسی
The aim of this study was obtain a model that maximizes growth and production of inulinase and invertase by Aspergillus niger ATCC 20611, employing response surface methodology (RSM). The RSM with a five-variable and three-level central composite design (CCD) was employed to optimize the medium composition. Results showed that the experimental data could be appropriately fitted into a second-order polynomial model with a coefficient of determination (R2) more than 0.90 for all responses. This model adequately explained the data variation and represented the actual relationships between the parameters and responses. The pH and temperature value of the cultivation medium were the most significant variables and the effects of inoculum size and agitation speed were slightly lower. The intra-extracellular inulinase, invertase production and biomass content increased 10-32 fold in the optimized medium condition (pH 6.5, temperature 30 °C, 6% (v/v), inoculum size and 150 rpm agitation speed) by RSM compared with medium optimized through the one-factor-at-a-time method. The process development and intensification for simultaneous production of intra-extracellular inulinase (exo and endo inulinase) and invertase from A. niger could be used for industrial applications.
ناشر
Database: Elsevier - ScienceDirect (ساینس دایرکت)
Journal: Brazilian Journal of Microbiology - Volume 48, Issue 3, JulyâSeptember 2017, Pages 427-441
Journal: Brazilian Journal of Microbiology - Volume 48, Issue 3, JulyâSeptember 2017, Pages 427-441
نویسندگان
Mojdeh Dinarvand, Malahat Rezaee, Majid Foroughi,