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A simple scaled down system to mimic the industrial production of first generation fuel ethanol in Brazil

Overview of attention for article published in Antonie van Leeuwenhoek, May 2017
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Title
A simple scaled down system to mimic the industrial production of first generation fuel ethanol in Brazil
Published in
Antonie van Leeuwenhoek, May 2017
DOI 10.1007/s10482-017-0868-9
Pubmed ID
Authors

Vijayendran Raghavendran, Thalita Peixoto Basso, Juliana Bueno da Silva, Luiz Carlos Basso, Andreas Karoly Gombert

Abstract

Although first-generation fuel ethanol is produced in Brazil from sugarcane-based raw materials with high efficiency, there is still little knowledge about the microbiology, the biochemistry and the molecular mechanisms prevalent in the non-aseptic fermentation environment. Learning-by-doing has hitherto been the strategy to improve the process so far, with further improvements requiring breakthrough technologies. Performing experiments at an industrial scale are often expensive, complicated to set up and difficult to reproduce. Thus, developing an appropriate scaled down system for this process has become a necessity. In this paper, we present the design and demonstration of a simple and effective laboratory-scale system mimicking the industrial process used for first generation (1G) fuel ethanol production in the Brazilian sugarcane mills. We benchmarked this system via the superior phenotype of the Saccharomyces cerevisiae PE-2 strain, compared to other strains from the same species: S288c, baker's yeast, and CEN.PK113-7D. We trust that such a system can be easily implemented in different laboratories worldwide, and will allow a better understanding of the S. cerevisiae strains that can persist and dominate in this industrial, non-aseptic and peculiar environment.

Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 65 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 65 100%

Demographic breakdown

Readers by professional status Count As %
Student > Master 12 18%
Student > Ph. D. Student 12 18%
Student > Bachelor 6 9%
Researcher 6 9%
Student > Doctoral Student 4 6%
Other 11 17%
Unknown 14 22%
Readers by discipline Count As %
Agricultural and Biological Sciences 15 23%
Biochemistry, Genetics and Molecular Biology 13 20%
Engineering 10 15%
Chemical Engineering 5 8%
Chemistry 3 5%
Other 4 6%
Unknown 15 23%