Evidence map›Paper›PMID 37117734›Full record

ArticleNature food2021

Forecasting rice latitude adaptation through a daylength-sensing-based environment adaptation simulator.

Leilei Qiu, Qinqin Wu, Xiaoying Wang, Jiupan Han, Gui Zhuang, Hao Wang, Zhiyun Shang, Wei Tian, Zhuo Chen, Zechuan Lin and 18 more

Abstract read
PubMed Publisher
In one paragraph

Article in Nature food, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 13 papers.

0numbers the graph read from it
0cells of the map it votes in
13citing 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

13 citing papers in PubMed.

  1. Article
  2. Article
  3. Article
  4. Article
  5. Article
  6. Article
  7. Review
  8. New Horizons in Plant Photoperiodism.Annual review of plant biology · 2023
    Review
  9. Article
  10. Article
  11. Article
  12. Article
  13. Review
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

28 authors.

Leilei Qiu *State Key Laboratory of Cellular Stress Biology, School of Life Sciences, Xiamen University, Xiamen, China.
Qinqin Wu *State Key Laboratory of Cellular Stress Biology, School of Life Sciences, Xiamen University, Xiamen, China.
Xiaoying Wang *State Key Laboratory of Cellular Stress Biology, School of Life Sciences, Xiamen University, Xiamen, China.
Jiupan Han *State Key Laboratory of Cellular Stress Biology, School of Life Sciences, Xiamen University, Xiamen, China.
Gui ZhuangState Key Laboratory of Cellular Stress Biology, School of Life Sciences, Xiamen University, Xiamen, China.
Hao WangState Key Laboratory of Crop Gene Exploration and Utilization in Southwest China, Rice Research Institute, Sichuan Agricultural University, Chengdu, China.
Zhiyun ShangState Key Laboratory of Cellular Stress Biology, School of Life Sciences, Xiamen University, Xiamen, China.
Wei TianState Key Laboratory of Cellular Stress Biology, School of Life Sciences, Xiamen University, Xiamen, China.
Zhuo ChenState Key Laboratory of Plant Genomics, Institute of Genetics and Developmental Biology, Innovation Academy for Seed Design, Chinese Academy of Sciences, Beijing, China.
Zechuan LinSchool of Advanced Agriculture Sciences and School of Life Sciences, Peking University, Beijing, China.
Hang HeSchool of Advanced Agriculture Sciences and School of Life Sciences, Peking University, Beijing, China.ORCID http://orcid.org/0000-0003-3165-283X
Jie HuSchool of Mathematical Sciences, Xiamen University, Xiamen, China.
Qiming LvState Key Laboratory of Hybrid Rice, Hunan Hybrid Rice Research Center, Changsha, China.ORCID http://orcid.org/0000-0001-7480-3015
Juansheng RenCrop Research Institute of Sichuan Academy of Agricultural Science, Chengdu, China.
Jun XuDeyang Agricultural Science and Education Management Station, Deyang, China.
Chen LiRice Research Institute, Guangdong Academy of Agricultural Sciences, Guangzhou, China.
Xiangfeng WangDepartment of Crop Genomics and Bioinformatics, College of Agronomy and Biotechnology, China Agricultural University, Beijing, China.
Yang LiPhotobiological Industry Institute, Sanan Sino-Science Photobiotech, Xiamen, China.
Shaohua LiPhotobiological Industry Institute, Sanan Sino-Science Photobiotech, Xiamen, China.
Rongyu HuangState Key Laboratory of Cellular Stress Biology, School of Life Sciences, Xiamen University, Xiamen, China.
Xu ChenHaixia Institute of Science and Technology, Horticultural Plant Biology and Metabolomics Center, Fujian Agriculture and Forestry University, Fuzhou, China.
Cheng ZhangLiaoning Rice Research Institute, Shenyang, China.
Ming LuJilin Academy of Agricultural Sciences, Changchun, China.
Chengzhi LiangState Key Laboratory of Plant Genomics, Institute of Genetics and Developmental Biology, Innovation Academy for Seed Design, Chinese Academy of Sciences, Beijing, China.ORCID http://orcid.org/0000-0001-8913-3552
Peng QinState Key Laboratory of Crop Gene Exploration and Utilization in Southwest China, Rice Research Institute, Sichuan Agricultural University, Chengdu, China.
Xi HuangState Key Laboratory of Cellular Stress Biology, School of Life Sciences, Xiamen University, Xiamen, China.
Shigui LiState Key Laboratory of Crop Gene Exploration and Utilization in Southwest China, Rice Research Institute, Sichuan Agricultural University, Chengdu, China.
Xinhao OuyangState Key Laboratory of Cellular Stress Biology, School of Life Sciences, Xiamen University, Xiamen, China. ouyangxinhao@xmu.edu.cn.ORCID http://orcid.org/0000-0001-6141-3501

Funding

National Natural Science Foundation of China (National Science Foundation of China) 31671378
6 · The paper itself

Abstract

Global climate change necessitates crop varieties with good environmental adaptability. As a proxy for climate adaptation, crop breeders could select for adaptability to different latitudes, but the lengthy procedures for that slow development. Here, we combined molecular technologies with a streamlined in-house screening method to facilitate rapid selection for latitude adaptation. We established the daylength-sensing-based environment adaptation simulator (DEAS) to assess rice latitude adaptation status via the transcriptional dynamics of florigen genes at different latitudes. The DEAS predicted the florigen expression profiles in rice varieties with high accuracy. Furthermore, the DEAS showed potential for application in different crops. Incorporating the DEAS into conventional breeding programmes would help to develop cultivars for climate adaptation.

Identifiers

What OpenQuestion holds

Textmetadata
Read underepoch 390

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.