Evidence map›Paper›PMID 35484294›Full record

ArticleScientific reports2022

Responses of butter leaf lettuce to mixed red and blue light with extended light/dark cycle period.

Xiao-Li Chen, You-Li Li, Li-Chun Wang, Qi-Chang Yang, Wen-Zhong Guo

Open access · goldAbstract read
In one paragraph

Article in Scientific reports, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 12 papers.

0numbers the graph read from it
0cells of the map it votes in
12citing papers in PubMed
5.3field-weighted citation impact, top 5% of its field
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

12 citing papers in PubMed, 30 citations in OpenAlex.

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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

5 authors at 1 institution in 1 country.

Xiao-Li ChenIntelligent Equipment Research Center, Beijing Academy of Agriculture and Forestry Sciences, Beijing, 100097, China.
You-Li LiIntelligent Equipment Research Center, Beijing Academy of Agriculture and Forestry Sciences, Beijing, 100097, China.
Li-Chun WangIntelligent Equipment Research Center, Beijing Academy of Agriculture and Forestry Sciences, Beijing, 100097, China.
Qi-Chang YangInstitute of Environment and Sustainable Development in Agriculture, Chinese Academy of Agricultural Sciences, Beijing, 100081, China. yangqichang@caas.cn.
Wen-Zhong GuoIntelligent Equipment Research Center, Beijing Academy of Agriculture and Forestry Sciences, Beijing, 100097, China. guowz@nercita.org.cn.
Beijing Academy of Agricultural and Forestry Sciences · CN

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

To investigate the effects of extended light/dark (L/D) cycle period (relative to the diurnal L/D cycle) on lettuce and explore potential advantages of abnormal L/D cycles, butter leaf lettuce were grown in a plant factory with artificial light (PFAL) and exposed to mixed red (R) and blue (B) LED light with different L/D cycles that were respectively 16 h light/8 h dark (L16/D8, as control), L24/D12, L48/D24, L96/D48 and L120/D60. The results showed that, all the abnormal L/D cycles increased shoot dry weight (DW) of lettuce (by 34-83%) compared with the control, and lettuce DW increased with the L/D cycle period prolonged. The contents of soluble sugar and crude fiber in lettuce showed an overall upward trend with the length of L/D cycle extended, and the highest vitamin C content as well as low nitrate content were both detected in lettuce treated with L120/D60. The light use efficiency (LUE) and electric use efficiency (EUE) of lettuce reached the maximum (respectively 5.37% and 1.76%) under L120/D60 treatment and so were DW, Assimilation rate (A), RC/CS, ABS/CS, TR

Indexed as

LactucaPhotosynthesisButterLightNitratesButterNitrates

Identifiers

PMID35484294
PMCPMC9051091
OpenAlexW4225117540

What OpenQuestion 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 OpenQuestion graph.