Evidence map›Paper›PMID 40963836›Full record

ArticleFrontiers in plant science2025

Genetic diversity analysis of phenotypic and agronomic traits in oat germplasm resources.

Yan Zhao, Jiaqi Fang, René Gislum, Baowen Zhao, Zhiming Zhong, Yingxia Lei, Donghai Yan, Ruzhi He, Youjun Chen, Qingping Zhou and 1 more

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PubMed Full text at PMC Publisher
In one paragraph

Article in Frontiers in plant science, 2025. 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

11 authors.

Yan ZhaoSichuan Zoige Alpine Wetland Ecosystem National Observation and Research Station, Southwest Minzu University, Chengdu, China.
Jiaqi FangSichuan Zoige Alpine Wetland Ecosystem National Observation and Research Station, Southwest Minzu University, Chengdu, China.
René GislumDepartment of Agroecology, Aarhus University, Slagelse, Denmark.
Baowen ZhaoSichuan Zoige Alpine Wetland Ecosystem National Observation and Research Station, Southwest Minzu University, Chengdu, China.
Zhiming ZhongInstitute of Geographic Sciences and Natural Resources Research, Chinese Academy of Sciences, Beijing, China.
Yingxia LeiSichuan Zoige Alpine Wetland Ecosystem National Observation and Research Station, Southwest Minzu University, Chengdu, China.
Donghai YanGrassland Technology Research and Extension Center of Sichuan Province, Chengdu, China.
Ruzhi HeGansu Puruituo (PRT) Eco-agricultural Science and Technology Co., Ltd., Zhangye, China.
Youjun ChenSichuan Zoige Alpine Wetland Ecosystem National Observation and Research Station, Southwest Minzu University, Chengdu, China.
Qingping ZhouSichuan Zoige Alpine Wetland Ecosystem National Observation and Research Station, Southwest Minzu University, Chengdu, China.
Hui WangSichuan Zoige Alpine Wetland Ecosystem National Observation and Research Station, Southwest Minzu University, Chengdu, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

The evaluation of genetic diversity in germplasm resources is fundamental to crop breeding. A total of 183 oat germplasm resources were evaluated through field trials at Xinjin District and Shandan County, located in southern and northern China, respectively. Phenotypic and agronomic traits were assessed, including six qualitative and sixteen quantitative characteristics. Results revealed significant variation in panicle attitude and grain color, based on the statistical analysis using SPSS. Among the sixteen quantitative traits, coefficient of variation ranged from 4.92% to 48.02% with the second internode thickness exhibiting the highest genetic diversity index. Correlation analysis of sixteen quantitative traits was performed using R Studio, and the results indicated significant positive relationships between grain weight and several ear characteristics, including spikelet number, ear length, layer numbers, and grain numbers per ear. Principal component analysis categorized the sixteen quantitative phenotypic traits into five independent factors. The structural equation modeling using SPSS-AMOS indicated that ear characteristics showed strong direct contributions to grain weight, establishing it as a key indicator for future breeding efforts. The multiple correspondence analysis by R Studio suggested that a total of nineteen oat germplasm resources showed the grain and biomass production potential across both experimental regions.

Indexed as

Avena sativaprincipal component analysisquantitative traitresource evaluationstructural equation modeling

Identifiers

PMID40963836
PMCPMC12436339

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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.