search
for
 About Bioline  All Journals  Testimonials  Membership  News


Electronic Journal of Biotechnology
Universidad Católica de Valparaíso
ISSN: 0717-3458
Vol. 18, No. 3, 2015, pp. 143-147
Bioline Code: ej15025
Full paper language: English
Document type: Research Article
Document available free of charge

Electronic Journal of Biotechnology, Vol. 18, No. 3, 2015, pp. 143-147

 en Statistical optimization for tannase production by Aspergillus tubingensis check for this species in other resources in solid-state fermentation using tea stalks
Xiao, Anfeng; Huang, Yufeng; Ni, Hui; Cai, Huinong & Yang, Qiuming

Abstract

Background: A sequential statistical strategy was used to optimize tannase production from Aspergillus tubingensis check for this species in other resources using tea stalks by solid-state fermentation.
Results: First, using a Plackett–Burman design, inoculum size and incubation time (among seven tested variables) were identified as the most significant factors for tannase yield. The effects of significant variables were further evaluated through a single steepest ascent experiment and central composite design with response surface analysis. Under optimal conditions, the experimental value of 84.24 units per gram of dry substrate (U/gds) closely matched the predicted value of 87.26 U/gds.
Conclusions: The result of the statistical approach was 2.09 times higher than the basal medium (40.22 U/gds). The results were fitted onto a second-order polynomial model with a correlation coefficient (R2) of 0.9340, which implied an adequate credibility of the model.

Keywords
Aspergillus tubingensis; Process optimization; Response surface methodology; Tea stalks; Tannase fermentation

 
© Copyright 2015 - Electronic Journal of Biotechnology
Alternative site location: http://www.ejbiotechnology.info

Home Faq Resources Email Bioline
© Bioline International, 1989 - 2024, Site last up-dated on 01-Sep-2022.
Site created and maintained by the Reference Center on Environmental Information, CRIA, Brazil
System hosted by the Google Cloud Platform, GCP, Brazil