Evidence map›Paper›PMID 42211488›Full record

ArticleFrontiers in plant science2026

Optimizing nitrogen reduction for improved grain yield and nitrogen-use-efficiency in two rice genotypes grown in hilly regions of Sichuan.

Peng Ma, Xiaohong Qin, Jianli Chai, Ran Wang, Lubing Jia, Xiaotian Jiang, Guotao Yang, Yungao Hu

Abstract read
In one paragraph

Article in Frontiers in plant science, 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

8 authors.

Peng Ma *College of Life Science and Agri-forestry, Southwest University of Science and Technology, Mianyang, China.
Xiaohong Qin *College of Life Science and Agri-forestry, Southwest University of Science and Technology, Mianyang, China.
Jianli Chai *College of Life Science and Agri-forestry, Southwest University of Science and Technology, Mianyang, China.
Ran WangCollege of Life Science and Agri-forestry, Southwest University of Science and Technology, Mianyang, China.
Lubing JiaCollege of Life Science and Agri-forestry, Southwest University of Science and Technology, Mianyang, China.
Xiaotian JiangCollege of Life Science and Agri-forestry, Southwest University of Science and Technology, Mianyang, China.
Guotao YangCollege of Life Science and Agri-forestry, Southwest University of Science and Technology, Mianyang, China.
Yungao HuCollege of Life Science and Agri-forestry, Southwest University of Science and Technology, Mianyang, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Introduction: The hilly region of Sichuan is a core rice-producing area in Southwest China.Long-term excessive fertilization has resulted in low nitrogen-use-efficiency and aggravated agricultural non-point source pollution, which seriously restricts the green and high-yield development of rice production. Methods: To determine the optimal nitrogen reduction rate for nitrogen-efficient rice varieties in this region and to reveal the regulatory effects of nitrogen reduction on rice yield, nitrogen utilization, and physiological metabolism, a two-year field experiment was conducted using two rice cultivars, Byou 3611 and Yixiangyou 2115. Four nitrogen treatments were applied: 180 kg·hm Results: The results showed that 150 kg·hm Discussion: This study indicates that Byou 3611 is superior to Yixiangyou 2115 in terms of grain yield and nitrogen-use-efficiency. The application rate of 150 kg·hm

Indexed as

enzyme activitygrain yieldnitrogen reductionnitrogen-use-efficiencyricesugar content

Identifiers

PMID42211488
PMCPMC13212099

What Socratic holds

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LicenceCC BY
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Registered trials

None linked

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 Socratic graph.