Evidence map›Paper›PMID 31988629›Full record

ArticleBreeding science2019

Novel haplotype combinations reveal enhanced seedling vigor traits in rice that can accurately predict dry biomass accumulation in seedlings.

Liang Xu, Leizhou Guo, Hui You, Ouling Zhang, Xunchao Xiang

Abstract read
In one paragraph

Article in Breeding science, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.

0numbers the graph read from it
0cells of the map it votes in
3citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

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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.

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3 · Its place in the literature

Who cites it

3 citing papers in PubMed.

  1. Superior haplotypes for transforming crop breeding.TAG. Theoretical and applied genetics. Theoretische und angewandte Genetik · 2026
    Review
  2. Enhancement of genetic gain for early seedling vigor traits through marker-assisted pedigree selection in rice (Physiology and molecular biology of plants : an international journal of functional plant biology · 2025
    Article
  3. Article
4 · The record

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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.

Liang XuLaboratory of Plant Molecular Genetics and Breeding, Southwest University of Science and Technology, 59 Qinglong Road, Mianyang 621010, China.
Leizhou GuoLaboratory of Plant Molecular Genetics and Breeding, Southwest University of Science and Technology, 59 Qinglong Road, Mianyang 621010, China.
Hui YouLaboratory of Plant Molecular Genetics and Breeding, Southwest University of Science and Technology, 59 Qinglong Road, Mianyang 621010, China.
Ouling ZhangLaboratory of Plant Molecular Genetics and Breeding, Southwest University of Science and Technology, 59 Qinglong Road, Mianyang 621010, China.
Xunchao XiangLaboratory of Plant Molecular Genetics and Breeding, Southwest University of Science and Technology, 59 Qinglong Road, Mianyang 621010, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Seedling vigor is of vital importance for the initial plant establishment of direct-seeded rice. Here, 166 recombinant inbred lines were employed to assess eight seedling vigor traits over the first 25 days of germination. Significant correlations were found between most traits, and statistical analysis has revealed, for the first time, a linear relationship that uses seedling height and fresh weight to accurately predict the accumulation of dry biomass. Further, a subset of 20 lines, spanning the phenotypic range of the larger population, were genotyped by using 16 simple sequence repeats (SSR) markers known to be associated with seedling vigor traits. Markers RM317 and RM348 linked with significantly different phenotypes, including seedling height and fresh weight. One combination, haplotype II-1 (RM317 (I/II) and RM348 (1/2)), consistently produced superior values for seedling height, root length, and leaf length. The new prediction tool for seedling dry weight, namely the haplotype of RM317 and RM348, will have a wide range of applications in breeding strategies by using marker-assisted selection to produce elite lines that optimize genetic composition contributing to seedling vigor.

Indexed as

haplotypemarker-assisted selectionrecombinant inbred lines (RILs)rice (Oryza sativa L.)seedling vigor

Identifiers

PMID31988629
PMCPMC6977453

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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.