Evidence map›Paper›PMID 31557178›Full record

ArticlePloS one2019

Adjusting cotton planting density under the climatic conditions of Henan Province, China.

Liyuan Liu, Chuanzong Li, Yingchun Han, Zhanbiao Wang, Lu Feng, Xiaoyu Zhi, Beifang Yang, Yaping Lei, Wenli Du, Yabing Li

Abstract read
In one paragraph

Article in PloS one, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing 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

1 citing paper in PubMed.

  1. Article
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.

Liyuan LiuInstitute of Cotton Research of Chinese Academy of Agricultural Sciences, Anyang, Henan, China.
Chuanzong LiInstitute of Cotton Research of Chinese Academy of Agricultural Sciences, Anyang, Henan, China.
Yingchun HanInstitute of Cotton Research of Chinese Academy of Agricultural Sciences, Anyang, Henan, China.
Zhanbiao WangInstitute of Cotton Research of Chinese Academy of Agricultural Sciences, Anyang, Henan, China.
Lu FengInstitute of Cotton Research of Chinese Academy of Agricultural Sciences, Anyang, Henan, China.
Xiaoyu ZhiInstitute of Cotton Research of Chinese Academy of Agricultural Sciences, Anyang, Henan, China.
Beifang YangInstitute of Cotton Research of Chinese Academy of Agricultural Sciences, Anyang, Henan, China.
Yaping LeiInstitute of Cotton Research of Chinese Academy of Agricultural Sciences, Anyang, Henan, China.
Wenli DuInstitute of Cotton Research of Chinese Academy of Agricultural Sciences, Anyang, Henan, China.
Yabing LiInstitute of Cotton Research of Chinese Academy of Agricultural Sciences, Anyang, Henan, China.ORCID 0000-0002-4033-5433

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

The growth and development of cotton are closely related to climatic variables such as temperature and solar radiation. Adjusting planting density is one of the most effective measures for maximizing cotton yield under certain climatic conditions. The objectives of this study were (1) to determine the optimum planting density and the corresponding leaf area index (LAI) and yield under the climatic conditions of Henan Province, China, and (2) to learn how climatic conditions influence cotton growth, yield, and yield components. A three-year (2013-2015) field experiment was conducted in Anyang, Henan Province, using cultivar SCRC28 across six planting density treatments: 15,000, 33,000, 51,000, 69,000, 87,000, and 105,000 plants ha-1. The data showed that the yield attributes, including seed cotton yield, lint yield, dry matter accumulation, and the LAI, increased as planting density increased. Consequently, the treatment of the maximum density with 105,000 plants ha-1 was the highest-yielding over three years, with the LAIs averaged across the three years being 0.37 at the bud stage, 2.36 at the flower and boll-forming stage, and 1.37 at the boll-opening stage. Furthermore, the correlation between the cotton yield attributes and meteorological conditions indicated that light interception (LI) and the diurnal temperature range were the climatic factors that most strongly influenced cotton seed yield. Moreover, the influence of the number of growing degree days (GDD) on cotton was different at different growth stages. These observations will be useful for determining best management practices for cotton production under the climatic conditions of Henan Province, China.

Indexed as

GossypiumChinaClimateCrop Production

Identifiers

PMID31557178
PMCPMC6762138

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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.