Evidence map›Paper›PMID 35729221›Full record

ArticleScientific reports2022

Rice straw structure changes following green pretreatment with petha wastewater for economically viable bioethanol production.

Dolly Kumari, Radhika Singh

Open access · goldAbstract read
In one paragraph

Article in Scientific reports, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 9 papers.

0numbers the graph read from it
0cells of the map it votes in
9citing papers in PubMed
4.0field-weighted citation impact, top 5% of its field
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

9 citing papers in PubMed, 54 citations in OpenAlex.

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4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

2 authors at 1 institution in 1 country.

Dolly KumariBiohydrogen Production Lab, Department of Chemistry, Faculty of Science, Dayalbagh Educational Institute, Dayalbagh, Agra, 282005, India.
Radhika SinghBiohydrogen Production Lab, Department of Chemistry, Faculty of Science, Dayalbagh Educational Institute, Dayalbagh, Agra, 282005, India. radhikasingh@dei.ac.in.
Dayalbagh Educational Institute · IN

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Energy efficient and environment friendly pretreatment processes for the production of biofuel have remained elusive and the research is further compounded by the high cost of processing lignocellulosic biomass-an essential factor for producing sustainable biofuels. In the last few decades, a number of pretreatment methods have been proposed, specifically chemical pretreatments but are either expensive or harmful to the environment. To address this urgent need, we propose a green pretreatment method that utilises the highly alkaline by-product, petha wastewater to pretreat the lignocellulosic waste rice straw (RS). The effectiveness of the pretreatment was analysed by monitoring both enhanced cellulose content and reducing sugar yield along with removal of hemicellulose and lignin. We found that PWW pretreatment yielded five times more reducing sugar than native RS with 10.12% increment in cellulose content. SEM and EDX studies further revealed that our process enhanced surface roughness and carbon content (from 32.19% increased to 41.59% and 41.66% for A and D, respectively) along with reduction in silica content (from 8.68% in RS to 4.30% and 7.72% for A and D, respectively). XRD and FTIR analyses indicate crystallinity index (CI) and alteration in lignocellulosic structure of RS, respectively. Decrease in CI was about 43.4% in A whereas only 4.5% in D as compared to native RS (CI 54.55%). Thereby we found PWW to be better substitute of an alkali for pretreatment of RS with negligible environmental impacts.

Indexed as

OryzaBiofuelsBiomassCelluloseHydrolysisLigninSugarsWastewaterBiofuelsCelluloseLigninSugarsWastewater

Identifiers

PMID35729221
PMCPMC9213452
OpenAlexW4283212077

What OpenQuestion holds

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LicenceCC BY
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Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.