Evidence map›Paper›PMID 37309518›Full record

ArticleMolecular breeding : new strategies in plant improvement2021

Genetic dissection of seed appearance quality using recombinant inbred lines in soybean.

Quan Hu, Yanwei Zhang, Ruirui Ma, Jie An, Wenxuan Huang, Yueying Wu, Jingjing Hou, Dajian Zhang, Feng Lin, Ran Xu and 2 more

Open access · greenAbstract read
PubMed Full text at PMC Publisher
In one paragraph

Article in Molecular breeding : new strategies in plant improvement, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing papers in PubMed
0.9field-weighted citation impact, top 19% 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

2 citing papers in PubMed, 4 citations in OpenAlex.

  1. Article
  2. Article
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

12 authors at 4 institutions in 2 countries.

Quan HuState Key Laboratory of Agrobiotechnology, and College of Agronomy and Biotechnology, China Agricultural University, Beijing, 100193 China.
Yanwei ZhangCrop Research Institute, Shandong Academy of Agricultural Sciences, Jinan, 250131 Shandong China.
Ruirui MaState Key Laboratory of Agrobiotechnology, and College of Agronomy and Biotechnology, China Agricultural University, Beijing, 100193 China.
Jie AnState Key Laboratory of Agrobiotechnology, and College of Agronomy and Biotechnology, China Agricultural University, Beijing, 100193 China.
Wenxuan HuangState Key Laboratory of Agrobiotechnology, and College of Agronomy and Biotechnology, China Agricultural University, Beijing, 100193 China.
Yueying WuState Key Laboratory of Agrobiotechnology, and College of Agronomy and Biotechnology, China Agricultural University, Beijing, 100193 China.
Jingjing HouState Key Laboratory of Agrobiotechnology, and College of Agronomy and Biotechnology, China Agricultural University, Beijing, 100193 China.
Dajian ZhangCollege of Agronomy, Shandong Agricultural University, Tai'an, 271018 Shandong China.
Feng LinDepartment of Plant, Soil and Microbial Sciences, Michigan State University, East Lansing, MI 48824 USA.
Ran XuCrop Research Institute, Shandong Academy of Agricultural Sciences, Jinan, 250131 Shandong China.
Qun SunBeijing Key Laboratory for Crop Genetic Improvement, College of Agronomy and Biotechnology, China Agricultural University, Beijing, 100193 China.
Lianjun SunState Key Laboratory of Agrobiotechnology, and College of Agronomy and Biotechnology, China Agricultural University, Beijing, 100193 China.ORCID 0000-0003-1541-6837
China Agricultural University · CNShandong Academy of Agricultural Sciences · CNMichigan State University · USShandong Agricultural University · CN

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Soybean seed appearance quality greatly affects the marketability. The objective of this study was to identify the quantitative trait loci (QTLs) that control the appearance quality of soybean seeds. A total of 256 recombinant inbred lines from Qi Huang No.34 × Ji Dou No.17 were utilized for QTL mapping. We innovatively applied a machine vision system to quantify the seed appearance of each line. As a result of QTL mapping, a total of 145 QTLs for the machine vision parameters were detected across three environments. We integrated QTLs mapped overlapped and obtained 16 QTL hotspots in total. Of these hotspots, Supplementary Information: The online version contains supplementary material available at 10.1007/s11032-021-01262-9.

Indexed as

Machine visionQTL mappingSeed appearance qualitySoybean

Identifiers

PMID37309518
PMCPMC10236129
OpenAlexW3216854308

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.