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RSM based optimization of nutritional conditions for cellulase mediated Saccharification by Bacillus cereus

Overview of attention for article published in Journal of Biological Engineering, May 2018
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Title
RSM based optimization of nutritional conditions for cellulase mediated Saccharification by Bacillus cereus
Published in
Journal of Biological Engineering, May 2018
DOI 10.1186/s13036-018-0097-4
Pubmed ID
Authors

Fouzia Tabssum, Muhammad Irfan, Hafiz Abdullah Shakir, Javed Iqbal Qazi

Abstract

Cellulases are enzyme which have potential applications in various industries. Researchers are looking for potential cellulolytic bacterial strains for industrial exploitation. In this investigation, cellulase production of Bacillus cereus was explored while attacking poplar twigs. The bacterium was isolated from the gut of freshwater fish, Labeo rohita and identified by 16S rRNA gene sequencing technology. Various nutritional conditions were screened and optimized through response surface methodology. Initially, Plackett-Burman design was used for screening purpose and optimization was conducted through Box-Bhenken design. The maximum cellulase production occurred at 0.5% yeast extract, 0.09% MgSO4, 0.04% peptone, 2% poplar waste biomass, initial medium pH of 9.0, and inoculum size of 2% v/v at 37 °C with agitation speed of 120 rpm for 24 h of submerged fermentation. The proposed model for optimization of cellulase production was found highly significant. The indigenously produced cellulase enzyme was employed for saccharification purpose at 50 °C for various time periods. Maximum total sugars of 31.42 mg/ml were released after 6 h of incubation at 50 °C.The efficiency of this enzyme was compared with commercial cellulase enzyme revealing significant findings. These results suggested potential utilization of this strain in biofuel industry.

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Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 55 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 55 100%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 10 18%
Student > Bachelor 5 9%
Student > Doctoral Student 4 7%
Lecturer 3 5%
Student > Master 3 5%
Other 9 16%
Unknown 21 38%
Readers by discipline Count As %
Biochemistry, Genetics and Molecular Biology 9 16%
Agricultural and Biological Sciences 7 13%
Environmental Science 4 7%
Immunology and Microbiology 4 7%
Chemical Engineering 2 4%
Other 9 16%
Unknown 20 36%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 1. This is our high-level measure of the quality and quantity of online attention that it has received. This Attention Score, as well as the ranking and number of research outputs shown below, was calculated when the research output was last mentioned on 15 May 2018.
All research outputs
#20,490,710
of 23,053,613 outputs
Outputs from Journal of Biological Engineering
#238
of 265 outputs
Outputs of similar age
#287,420
of 326,454 outputs
Outputs of similar age from Journal of Biological Engineering
#3
of 4 outputs
Altmetric has tracked 23,053,613 research outputs across all sources so far. This one is in the 1st percentile – i.e., 1% of other outputs scored the same or lower than it.
So far Altmetric has tracked 265 research outputs from this source. They typically receive more attention than average, with a mean Attention Score of 7.7. This one is in the 1st percentile – i.e., 1% of its peers scored the same or lower than it.
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We're also able to compare this research output to 4 others from the same source and published within six weeks on either side of this one.