Evidence map›Paper›PMID 32849421›Full record

ArticleFrontiers in microbiology2020

Assessment of Diazotrophic

Manoj Kumar Solanki, Zhen Wang, Fei-Yong Wang, Chang-Ning Li, Chhedi Lal Gupta, Rajesh Kumar Singh, Mukesh Kumar Malviya, Pratiksha Singh, Li-Tao Yang, Yang-Rui Li

Abstract read
In one paragraph

Article in Frontiers in microbiology, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 11 papers.

0numbers the graph read from it
0cells of the map it votes in
11citing papers in PubMed
–field-weighted citation impact
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

11 citing papers in PubMed.

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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

10 authors.

Manoj Kumar SolankiGuangxi Crop Genetic Improvement and Biotechnology Lab, Guangxi Academy of Agricultural Sciences, Nanning, China.
Zhen WangGuangxi Crop Genetic Improvement and Biotechnology Lab, Guangxi Academy of Agricultural Sciences, Nanning, China.
Fei-Yong WangGuangxi Crop Genetic Improvement and Biotechnology Lab, Guangxi Academy of Agricultural Sciences, Nanning, China.
Chang-Ning LiGuangxi Crop Genetic Improvement and Biotechnology Lab, Guangxi Academy of Agricultural Sciences, Nanning, China.
Chhedi Lal GuptaThe Volcani Center, Institute of Soil, Water and Environmental Sciences, Agricultural Research Organization, Rishon LeZion, Israel.
Rajesh Kumar SinghGuangxi Crop Genetic Improvement and Biotechnology Lab, Guangxi Academy of Agricultural Sciences, Nanning, China.
Mukesh Kumar MalviyaGuangxi Crop Genetic Improvement and Biotechnology Lab, Guangxi Academy of Agricultural Sciences, Nanning, China.
Pratiksha SinghGuangxi Crop Genetic Improvement and Biotechnology Lab, Guangxi Academy of Agricultural Sciences, Nanning, China.
Li-Tao YangCollege of Biology and Pharmacy, Yulin Normal University, Yulin, China.
Yang-Rui LiGuangxi Crop Genetic Improvement and Biotechnology Lab, Guangxi Academy of Agricultural Sciences, Nanning, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Several factors influenced the sugarcane production, and among them, higher use of nitrogen and depletion of soil nutrient constitutes a significant concern in China. Sugarcane-legume intercropping may help to regulate the microbial structure and functions. In the present study, sugarcane rhizosphere soils of three cropping systems: Sugarcane only (S-only), sugarcane with peanut (S + P), and sugarcane + soybean (S + S) were sampled in tillering, elongation, and maturation stages from two different experimental fields. High-throughput sequencing technologies applied to assess the effects of different cropping systems on the structure of nitrogenase (

Indexed as

high throughput sequencingintercroppingmicrobial communityNifH genesugarcane

Identifiers

PMID32849421
PMCPMC7412970

What OpenQuestion holds

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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.