Evidence map›Paper›PMID 41656294›Full record

ArticleScientific reports2026

Effects of film mulching on cotton yield and water use efficiency in China: a meta-analysis.

Zhihao Yang, Yajin Hu, Yanan Zhao, Ling Li, Siyuan Liu, Qingxiang Meng, Yali Zhang

Abstract read
In one paragraph

Article in Scientific reports, 2026. 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
–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

0 citing papers in PubMed.

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

7 authors.

Zhihao YangCollege of Resources and Environment, Henan Agricultural University, Zhengzhou, 450046, China.
Yajin HuCollege of Resources and Environment, Henan Agricultural University, Zhengzhou, 450046, China. huyajinnd@henau.edu.cn.
Yanan ZhaoCollege of Resources and Environment, Henan Agricultural University, Zhengzhou, 450046, China. zhaoyanan@henau.edu.cn.
Ling LiCollege of Resources and Environment, Henan Agricultural University, Zhengzhou, 450046, China.
Siyuan LiuCollege of Resources and Environment, Henan Agricultural University, Zhengzhou, 450046, China.
Qingxiang MengCollege of Resources and Environment, Henan Agricultural University, Zhengzhou, 450046, China.
Yali ZhangCollege of Resources and Environment, Henan Agricultural University, Zhengzhou, 450046, China.

Funding

High level Talent Special Support Fund of Henan Agricultural University 30501358National Key Research and Development Program of China 2021YFD1700900Postdoctoral research grant from Henan Province 1040010Research project of Henan Provincial Federation of Social Sciences SKL-2025-469the National Key Research and Development Program of China 2021YFD1901000the Natural Science Foundation of Henan Province 252300423246
6 · The paper itself

Abstract

Film mulching (FM) has the positive effectiveness of increasing production and retaining soil water, which indicated that film mulching is a widespread technique. However, the agreement about the effects on cotton yield and water use efficiency (WUE) has not yet been established. We collected 222 yield and 55 WUE observations from 68 articles and used meta-analysis to investigate whether FM is effective on cotton yield and WUE. FM markedly enhanced cotton yield and WUE by 30.11% and 40.03%, respectively, in comparison to no mulching. Importantly, FM performed better at mean annual precipitation (MAP) < 200 mm and mean annual temperature (MAT) < 12 ℃. Higher cotton yield and WUE under FM was observed in medium and fine-textured soils with soil bulk density (BD) < 1.4 g cm

Indexed as

CottonFilm mulchingMeta-analysisWUEYield

Identifiers

PMID41656294
PMCPMC12949007

What OpenQuestion holds

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LicenceCC BY-NC-ND
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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.