Evidence map›Paper›PMID 42490622›Full record

ArticlePloS one2026

Evaluation of forage oat cultivars for alpine saline-alkaline environments: Trade-offs between yield, quality and stability.

Yangji Jia, Haiying Zhang, Fengjuan Xue, Hao Sun, Xiaoli Wei, Xiaojian Pu, Yuanyuan Zhao, Chengti Xu

Abstract read
In one paragraph

Article in PloS one, 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

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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

8 authors.

Yangji JiaCollege of Animal Science and Veterinary Science, Qinghai University, Xining, Qinghai Province, China.
Haiying ZhangCollege of Animal Science and Veterinary Science, Qinghai University, Xining, Qinghai Province, China.
Fengjuan XueCollege of Animal Science and Veterinary Science, Qinghai University, Xining, Qinghai Province, China.
Hao SunCollege of Animal Science and Veterinary Science, Qinghai University, Xining, Qinghai Province, China.
Xiaoli WeiCollege of Animal Science and Veterinary Science, Qinghai University, Xining, Qinghai Province, China.
Xiaojian PuCollege of Animal Science and Veterinary Science, Qinghai University, Xining, Qinghai Province, China.
Yuanyuan ZhaoCollege of Animal Science and Veterinary Science, Qinghai University, Xining, Qinghai Province, China.
Chengti XuCollege of Animal Science and Veterinary Science, Qinghai University, Xining, Qinghai Province, China.ORCID https://orcid.org/0009-0001-8636-4416

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Oat cultivation in the alpine saline-alkaline Qaidam Basin requires cultivars that balance yield, quality, and stability. Identifying suitable cultivars is key to sustainable forage production. Three oat cultivars ('Qinghai 444', 'Qingtian No. 1', and 'Zhengshi No. 1') were evaluated in a two-year (2024 and 2025) field trial. We measured agronomic traits, yield, photosynthetic parameters, and forage quality. Mixed linear models, correlation analysis, and principal component analysis (PCA) were used to assess genotypic effects, environmental stability, and trait relationships. Cultivars exhibited distinct strategies. 'Zhengshi No. 1' achieved the highest fresh yield (3.29 and 1.96 t/ha) linked to greater stem diameter and photosynthetic rates but with high environmental sensitivity. 'Qingtian No. 1' provided stable, superior forage quality (highest crude protein: 11.44% and 10.33%). 'Qinghai 444' showed the most stable agronomic performance and highest water-use efficiency. Key trade-offs were identified, including a negative correlation between yield-related traits and forage quality (Relative Feed Value). The choice of optimal cultivar depends on primary goals: 'Zhengshi No. 1' for maximum biomass, 'Qingtian No. 1' for high quality, and 'Qinghai 444' for reliable performance under variable conditions. This provides an actionable framework for cultivar selection in saline-alkaline regions.

Indexed as

AvenaBiomassGenotypePhotosynthesisPrincipal Component AnalysisSalinity

Identifiers

PMID42490622
PMCPMC13395352

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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.