Evidence map›Paper›PMID 42780664›Full record

ArticleFrontiers in plant science2026

Red light regulation on growth, root-leaf architecture and photosynthetic performance of rice seedlings.

Maofei Ren, Guiling Mao, Zhihao Wang, Jinping Ding, Junna Liu, Lingling Zhao, Xiangyan Wang, Boyan Du, Lijun Zhao, Hongxing Zheng and 3 more

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

13 authors.

Maofei RenHenan Environmental and Health Engineering Research Center, Henan Agricultural Remote Sensing Big Data Development and Innovation Laboratory & Henan Green Technology Innovation Demonstration Base, Shangqiu Normal University, Shangqiu, China.
Guiling MaoCollege of Horticulture, Hunan Agricultural University, Changsha, China.
Zhihao WangHenan Fengcai Agricultural Development Co. LTD, Suixian, China.
Jinping DingHenan Environmental and Health Engineering Research Center, Henan Agricultural Remote Sensing Big Data Development and Innovation Laboratory & Henan Green Technology Innovation Demonstration Base, Shangqiu Normal University, Shangqiu, China.
Junna LiuHenan Environmental and Health Engineering Research Center, Henan Agricultural Remote Sensing Big Data Development and Innovation Laboratory & Henan Green Technology Innovation Demonstration Base, Shangqiu Normal University, Shangqiu, China.
Lingling ZhaoHenan Fengcai Agricultural Development Co. LTD, Suixian, China.
Xiangyan WangHenan Environmental and Health Engineering Research Center, Henan Agricultural Remote Sensing Big Data Development and Innovation Laboratory & Henan Green Technology Innovation Demonstration Base, Shangqiu Normal University, Shangqiu, China.
Boyan DuHenan Environmental and Health Engineering Research Center, Henan Agricultural Remote Sensing Big Data Development and Innovation Laboratory & Henan Green Technology Innovation Demonstration Base, Shangqiu Normal University, Shangqiu, China.
Lijun ZhaoHenan Environmental and Health Engineering Research Center, Henan Agricultural Remote Sensing Big Data Development and Innovation Laboratory & Henan Green Technology Innovation Demonstration Base, Shangqiu Normal University, Shangqiu, China.
Hongxing ZhengHenan Environmental and Health Engineering Research Center, Henan Agricultural Remote Sensing Big Data Development and Innovation Laboratory & Henan Green Technology Innovation Demonstration Base, Shangqiu Normal University, Shangqiu, China.
Chenyao SongHenan Environmental and Health Engineering Research Center, Henan Agricultural Remote Sensing Big Data Development and Innovation Laboratory & Henan Green Technology Innovation Demonstration Base, Shangqiu Normal University, Shangqiu, China.
Qiankun DingHenan Environmental and Health Engineering Research Center, Henan Agricultural Remote Sensing Big Data Development and Innovation Laboratory & Henan Green Technology Innovation Demonstration Base, Shangqiu Normal University, Shangqiu, China.
Yanhao MaHenan Environmental and Health Engineering Research Center, Henan Agricultural Remote Sensing Big Data Development and Innovation Laboratory & Henan Green Technology Innovation Demonstration Base, Shangqiu Normal University, Shangqiu, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Given that the problem of insufficient light intensity is prevalent in the cultivation of rice seedlings under facility conditions, and light quality plays a crucial role in regulating crop growth, it is necessary to explore the most suitable proportion of red light for improving the quality and photosynthetic capacity of the seedlings. In this study, two different types of rice varieties (conventional rice, Xiangzaoxian 24, XZX24 and hybrid rice, Huazheyou 261, HZY261) were selected as experimental materials. A systematic investigation was conducted to examine the effects of different red light ratios on the morphological development of rice seedlings, the structure development of leaves and roots, as well as the photosynthetic characteristics. Six light quality treatments were applied, including white light (W, control), monochromatic red light (R), and combined white plus red light with different ratios (WR20, WR40, WR60, WR80). The results demonstrated that appropriate compound white-red light significantly coordinated shoot and root development; under the WR40 treatment (60% white light + 40% red light), the total seedling dry weight of the two varieties increased by 25.75% and 28.56% relative to the white light control, respectively. Gradually elevated red light proportion continuously boosted leaf pigment accumulation, with WR80 achieving the maximum total chlorophyll content, while WR60 optimized the non-photochemical quenching (NPQ) photoprotective capacity of leaves. Moderate red supplementation (WR20-WR60) maintained high Rubisco activity and upregulated the transcription of

Indexed as

leaf-root structuremorphogenesisphotosynthesisred lightrice

Identifiers

PMID42780664
PMCPMC13597676

What OpenQuestion holds

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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.