Evidence map›Paper›PMID 33384904›Full record

ArticlePeerJ2020

Optimizing the amount of pig manure in the vermicomposting of spent mushroom (

Yajing Shi, Zhenyu Wang, Yurong Wang

Open access · goldAbstract read
In one paragraph

Article in PeerJ, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing papers in PubMed
0.6field-weighted citation impact, top 27% 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

0 citing papers in PubMed, 11 citations in OpenAlex.

No citing paper in PubMed yet.

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

3 authors.

Yajing Shi *School of Biological and Chemical Engineering, Liaoning Institute of Science and Technology, Benxi, Liaoning, China.
Zhenyu Wang *School of Biological and Chemical Engineering, Liaoning Institute of Science and Technology, Benxi, Liaoning, China.
Yurong WangSchool of Biological and Chemical Engineering, Liaoning Institute of Science and Technology, Benxi, Liaoning, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundThe mushroom industry produces a large amount of spent mushroom substrate (SMS), which requires a large geographical footprint and causes pollution.

methodsWe sought to optimize the C:N ratio of the initial feedstock used in vermicomposting of SMS by adding pig manure additions. We applied five treatments to the initial feedstock (S0, S1, S2, S3, and S4) with different C:N ratio of approximately 35, 30, 25, 20, and 15, respectively.

resultsOur results showed that lignin and cellulose in SMS were degraded after 56 days vermicomposting, especially in S2 (77.05% and 45.29%, respectively) and S3 (65.05% and 48.37%, respectively) treatments. We observed the degradation of the fibrous structure in SMS using pig manure treatments after vermicomposting by microscope and scanning electron microscope. Cellulase and polyphenol oxidase (PPO) were enhanced in pig manure treatments during vermicomposting, especially in the S2 and S3 treatments. The biomass of earthworms in the S2 treatments was at its highest level among all treatments at 28 to 56 days. The high level of PPO activity in the S2 treatment may protect cellulase and earthworms against the aromatic toxicity that is a byproduct of lignin degradation, particularly at 28 to 56 days of vermicomposting. Conclusively, it indicated that the C/N ratio of 25 in the S2 treatment was the optimal for SMS vermicomposting with the addition of pig manure. Our results provide a positive application for the recycling of both SMS and pig manure.

Indexed as

OptimizingPig manure additionSpent mushroom substrate (SMS)Vermicomposting

Identifiers

PMID33384904
PMCPMC7751411
OpenAlexW3114120535

What OpenQuestion holds

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LicenceCC BY
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Registered trials

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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.