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Mendeley readers
Attention Score in Context
| Title |
An effective surfactant-assisted hydrothermal pretreatment strategy for bioethanol production from chili post-harvest residue by separate hydrolysis and fermentation
|
|---|---|
| Published in |
Bioprocess and Biosystems Engineering, January 2018
|
| DOI | 10.1007/s00449-018-1891-6 |
| Pubmed ID | |
| Authors |
Raveendran Sindhu, Parameswaran Binod, Anil Kuruvilla Mathew, Amith Abraham, Ashok Pandey, Edgard Gnansounou, Galliano Eulogio Castro |
| Abstract |
Surfactants play major role in the delignification of lignocellulosic biomass. Surfactant-assisted hydrothermal pretreatment was evaluated for chili post-harvest residue. Maximum reducing sugar yield of 0.445 g per g of dry biomass (g/g) was obtained when surfactant PEG 6000 was used. Compositional analysis revealed an efficient removal of lignin and hemicelluloses from the pretreated biomass. Fermentation inhibitors such as furfural, 5-hydroxymethylfurfural and organic acids were absent in the hydrolyzate. After pretreatment, the biomass can be directly hydrolyzed without any neutralization, washing and drying, and the hydrolyzate is devoid of major fermentation inhibitors. Fermentation with Saccharomyces cerevisiae yielded 1.84% of ethanol with a fermentation efficiency of 63.88%. |
X Demographics
The data shown below were collected from the profile of 1 X user who shared this research output. Click here to find out more about how the information was compiled.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| France | 1 | 100% |
Demographic breakdown
| Type | Count | As % |
|---|---|---|
| Members of the public | 1 | 100% |
Mendeley readers
The data shown below were compiled from readership statistics for 23 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Unknown | 23 | 100% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Researcher | 4 | 17% |
| Student > Ph. D. Student | 4 | 17% |
| Student > Doctoral Student | 2 | 9% |
| Student > Bachelor | 2 | 9% |
| Professor | 2 | 9% |
| Other | 4 | 17% |
| Unknown | 5 | 22% |
| Readers by discipline | Count | As % |
|---|---|---|
| Chemical Engineering | 4 | 17% |
| Agricultural and Biological Sciences | 4 | 17% |
| Engineering | 3 | 13% |
| Energy | 2 | 9% |
| Biochemistry, Genetics and Molecular Biology | 2 | 9% |
| Other | 3 | 13% |
| Unknown | 5 | 22% |
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 21 January 2018.
All research outputs
#22,834,739
of 25,461,852 outputs
Outputs from Bioprocess and Biosystems Engineering
#477
of 604 outputs
Outputs of similar age
#391,976
of 451,760 outputs
Outputs of similar age from Bioprocess and Biosystems Engineering
#1
of 1 outputs
Altmetric has tracked 25,461,852 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 604 research outputs from this source. They receive a mean Attention Score of 3.1. This one is in the 1st percentile – i.e., 1% of its peers scored the same or lower than it.
Older research outputs will score higher simply because they've had more time to accumulate mentions. To account for age we can compare this Altmetric Attention Score to the 451,760 tracked outputs that were published within six weeks on either side of this one in any source. This one is in the 1st percentile – i.e., 1% of its contemporaries scored the same or lower than it.
We're also able to compare this research output to 1 others from the same source and published within six weeks on either side of this one. This one has scored higher than all of them