Evidence map›Paper›PMID 32989486›Full record

ArticleCurrent microbiology2020

Comparative Study on Soil Microbial Diversity and Structure Under Wastewater and Groundwater Irrigation Conditions.

Xiaotao Xu, Sen Liu, Xiwang Zhu, Xiaoming Guo

Abstract read
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In one paragraph

Article in Current microbiology, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing 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

2 citing papers in PubMed.

  1. Article
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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

4 authors.

Xiaotao XuInstitute of Resources and Environment, Henan Polytechnic University, Jiaozuo, China.
Sen LiuCollege of Life Sciences, Henan Normal University, Xinxiang, China.
Xiwang ZhuInstitute of Resources and Environment, Henan Polytechnic University, Jiaozuo, China.
Xiaoming GuoInstitute of Resources and Environment, Henan Polytechnic University, Jiaozuo, China. guoxiaoming@hpu.edu.cn.

Funding

Henan Postdoctoral Foundation 001702041National Natural Science Foundation of China 31870354National Natural Science Foundation of China 41502241
6 · The paper itself

Abstract

Wastewater (WW) irrigation to agricultural soils is one of the most economical and effective water-saving strategies. The effects of WW irrigation on soil microbial communities have gained increasing focus as these effects are not well understood. In this study, the effects of WW and groundwater (GW) irrigation on microbial diversity and structure were compared using the high-throughput sequencing analysis of 16S rDNA amplicons. Soil samples irrigated by WW for several decades and maize soil (loamy) samples irrigated by GW were collected from Luancheng Town, Shijiazhuang City, China. Compared to the GW groups, WW groups exhibited non-significant soil bacterial community abundance at the 0-20 and 20-40 cm depths. WW irrigation significantly altered the bacterial community composition and structures compared to GW irrigation. The relative abundance of Proteobacteria and Firmicutes increased in WW irrigated soil, while Actinobacteria decreased. Moreover, 14 significantly abundant biomarkers from Proteobacteria and Firmicutes that corresponded with WW irrigation were identified. Additionally, WW irrigation enriched some KEGG pathways that corresponded with metabolism and human diseases. The physical and chemical properties of WW irrigated soil may shape the compositions and structures of soil bacterial communities. The findings of this study illuminated the effects of wastewater irrigation on microbial characteristics, which is important for estimating the effects of long-term wastewater irrigation on soil environmental health.

Indexed as

GroundwaterSoilAgricultural IrrigationChinaHumansSoil MicrobiologyWastewaterSoilWastewater

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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.