Evidence map›Paper›PMID 38512412›Full record

ArticlePlanta2024

Root system architecture change in response to waterlogging stress in a 448 global collection of rapeseeds (Brassica napus L.).

Naseeb Ullah, Fang Qian, Rudan Geng, Yujun Xue, Wenjie Guan, Gaoxiang Ji, Hao Li, Qian Huang, Guangqin Cai, Guixin Yan and 1 more

Abstract read
PubMed Publisher
In one paragraph

Article in Planta, 2024. 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
–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

2 citing papers in PubMed.

  1. Article
  2. 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

11 authors.

Naseeb UllahThe Key Laboratory of Biology and Genetic Improvement of Oil Crops, The Ministry of Agriculture and Rural Affairs of the PRC, Oil Crops Research Institute of the Chinese Academy of Agricultural Sciences, Wuhan, 430062, China.
Fang QianThe Key Laboratory of Biology and Genetic Improvement of Oil Crops, The Ministry of Agriculture and Rural Affairs of the PRC, Oil Crops Research Institute of the Chinese Academy of Agricultural Sciences, Wuhan, 430062, China.
Rudan GengThe Key Laboratory of Biology and Genetic Improvement of Oil Crops, The Ministry of Agriculture and Rural Affairs of the PRC, Oil Crops Research Institute of the Chinese Academy of Agricultural Sciences, Wuhan, 430062, China.
Yujun XueThe Key Laboratory of Biology and Genetic Improvement of Oil Crops, The Ministry of Agriculture and Rural Affairs of the PRC, Oil Crops Research Institute of the Chinese Academy of Agricultural Sciences, Wuhan, 430062, China.
Wenjie GuanThe Key Laboratory of Biology and Genetic Improvement of Oil Crops, The Ministry of Agriculture and Rural Affairs of the PRC, Oil Crops Research Institute of the Chinese Academy of Agricultural Sciences, Wuhan, 430062, China.
Gaoxiang JiThe Key Laboratory of Biology and Genetic Improvement of Oil Crops, The Ministry of Agriculture and Rural Affairs of the PRC, Oil Crops Research Institute of the Chinese Academy of Agricultural Sciences, Wuhan, 430062, China.
Hao LiThe Key Laboratory of Biology and Genetic Improvement of Oil Crops, The Ministry of Agriculture and Rural Affairs of the PRC, Oil Crops Research Institute of the Chinese Academy of Agricultural Sciences, Wuhan, 430062, China.
Qian HuangThe Key Laboratory of Biology and Genetic Improvement of Oil Crops, The Ministry of Agriculture and Rural Affairs of the PRC, Oil Crops Research Institute of the Chinese Academy of Agricultural Sciences, Wuhan, 430062, China.
Guangqin CaiThe Key Laboratory of Biology and Genetic Improvement of Oil Crops, The Ministry of Agriculture and Rural Affairs of the PRC, Oil Crops Research Institute of the Chinese Academy of Agricultural Sciences, Wuhan, 430062, China.
Guixin YanThe Key Laboratory of Biology and Genetic Improvement of Oil Crops, The Ministry of Agriculture and Rural Affairs of the PRC, Oil Crops Research Institute of the Chinese Academy of Agricultural Sciences, Wuhan, 430062, China. ygx_928@126.com.
Xiaoming WuThe Key Laboratory of Biology and Genetic Improvement of Oil Crops, The Ministry of Agriculture and Rural Affairs of the PRC, Oil Crops Research Institute of the Chinese Academy of Agricultural Sciences, Wuhan, 430062, China. wuxm@oilcrops.cn.ORCID http://orcid.org/0000-0002-1917-1964

Funding

the Agricultural Science and Technology Innovation Project CAAS-ZDRW202105
6 · The paper itself

Abstract

MAIN

conclusionsA novel image-based screening method for precisely identifying genotypic variations in rapeseed RSA under waterlogging stress was developed. Five key root traits were confirmed as good indicators of waterlogging and might be employed in breeding, particularly when using the MFVW approach. Waterlogging is a vital environmental factor that has detrimental effects on the growth and development of rapeseed (Brassica napus L.). Plant roots suffer from hypoxia under waterlogging, which ultimately confers yield penalty. Therefore, it is crucially important to understand the genetic variation of root system architecture (RSA) in response to waterlogging stress to guide the selection of new tolerant cultivars with favorable roots. This research was conducted to investigate RSA traits using image-based screening techniques to better understand how RSA changes over time during waterlogging at the seedling stage. First, we performed a t-test by comparing the relative root trait value between four tolerant and four sensitive accessions. The most important root characteristics associated with waterlogging tolerance at 12 h are total root length (TRL), total root surface area (TRSA), total root volume (TRV), total number of tips (TNT), and total number of forks (TNF). The root structures of 448 rapeseed accessions with or without waterlogging showed notable genetic diversity, and all traits were generally restrained under waterlogging conditions, except for the total root average diameter. Additionally, according to the evaluation and integration analysis of 448 accessions, we identified that five traits, TRL, TRSA, TRV, TNT, and TNF, were the most reliable traits for screening waterlogging-tolerant accessions. Using analysis of the membership function value (MFVW) and D-value of the five selected traits, 25 extremely waterlogging-tolerant materials were screened out. Waterlogging significantly reduced RSA, inhibiting root growth compared to the control. Additionally, waterlogging increased lipid peroxidation, accompanied by a decrease in the activities of superoxide dismutase (SOD), peroxidase (POD), and catalase (CAT). This study effectively improves our understanding of the response of RSA to waterlogging. The image-based screening method developed in this study provides a new scientific guidance for quickly examining the basic RSA changes and precisely predicting waterlogging-tolerant rapeseed germplasms, thus expanding the genetic diversity of waterlogging-tolerant rapeseed germplasm available for breeding.

Indexed as

Brassica napusBrassica rapaGenotypePhenotypePlant BreedingSeedlingsBrassica napusImage analysisMembership function valueRoot system architectureSeedling stageWaterlogging tolerance

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.