Evidence map›Paper›PMID 34314420›Full record

ArticlePloS one2021

Identification for surrogate drought tolerance in maize inbred lines utilizing high-throughput phenomics approach.

Zahoor A Dar, Showket A Dar, Jameel A Khan, Ajaz A Lone, Sapna Langyan, B A Lone, R H Kanth, Asif Iqbal, Jagdish Rane, Shabir H Wani and 4 more

RetractedOpen access · goldAbstract readRetracted Publication
In one paragraph

Article in PloS one, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. It has been retracted, and should not be counted. Cited by 7 papers.

0numbers the graph read from it
0cells of the map it votes in
7citing papers in PubMed
3.3field-weighted citation impact, top 8% 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

7 citing papers in PubMed, 18 citations in OpenAlex.

  1. Review
  2. Heat Stress-Mediated Constraints in Maize (Frontiers in plant science · 2022
    Review
  3. Review
  4. Article
  5. Article
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  7. Article
4 · The record

Corrections and comments

5 · Who and what money

Authors and funding

14 authors at 7 institutions in 3 countries.

Zahoor A DarDryland Agricultural Research Station, Sher-e-Kashmir University of Agricultural Sciences &Technology-Kashmir, Rangreth Srinagar, Jammu and Kashmir, India.
Showket A DarDepartment of Entomology, Sher-e-Kashmir University of Agricultural Sciences & Technology of Kashmir, Srinagar-Kargil, Ladakh, India.ORCID 0000-0001-5511-9509
Jameel A KhanDepartment of Biotechnology, University of Agricultural Sciences, Bangalore, India.
Ajaz A LoneDryland Agricultural Research Station, Sher-e-Kashmir University of Agricultural Sciences &Technology-Kashmir, Rangreth Srinagar, Jammu and Kashmir, India.
Sapna LangyanICAR-National Bureau for Plant Genetic Resources, New Delhi, India.
B A LoneDepartment of Agronomy, Sher-e-Kashmir University of Agricultural Sciences &Technology-Kashmir, Srinagar, Jammu and Kashmir, India.ORCID 0000-0002-4645-8733
R H KanthDepartment of Agronomy, Sher-e-Kashmir University of Agricultural Sciences &Technology-Kashmir, Wadura Sopore, Jammu and Kashmir, India.
Asif IqbalDepartment of Soil Science, Sher-e-Kashmir University of Agricultural Sciences &Technology-Kashmir, Srinagar, Jammu and Kashmir, India.
Jagdish RaneDepartment of Drought Science, ICAR-NIASM, Baramati, New Delhi, India.
Shabir H WaniMRCFCF, Sher-e-Kashmir University of Agricultural Sciences &Technology-Kashmir, Srinagar, Jammu and Kashmir, India.
Saleh AlfarrajZoology Department, College of Science, King Saud University, Riyadh, Saudi Arabia.
Sulaiman Ali AlharbiDepartment of Botany & Microbiology, College of Science, King Saud University, Riyadh, Saudi Arabia.
Marian BresticDepartment of Plant Physiology, Slovak University of Agriculture, Nitra, Slovakia.
Mohammad Javed AnsariDepartment of Botany, Hindu College Moradabad (Mahatma Jyotiba Phule Rohilkhand University Bareilly), Moradabad, India.ORCID 0000-0002-8718-3078
Sher-e-Kashmir University of Agricultural Sciences and Technology of Kashmir · INKing Saud University · SAIndian Council of Agricultural Research · INM.J.P. Rohilkhand University · INNational Bureau of Plant Genetic Resources · INSlovak University of Agriculture in Nitra · SKUniversity of Agricultural Sciences, Bangalore · IN

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Screening for drought tolerance requires precise techniques like phonemics, which is an emerging science aimed at non-destructive methods allowing large-scale screening of genotypes. Large-scale screening complements genomic efforts to identify genes relevant for crop improvement. Thirty maize inbred lines from various sources (exotic and indigenous) maintained at Dryland Agriculture Research Station were used in the current study. In the automated plant transport and imaging systems (LemnaTec Scanalyzer system for large plants), top and side view images were taken of the VIS (visible) and NIR (near infrared) range of the light spectrum to capture phenes. All images were obtained with a thermal imager. All sensors were used to collect images one day after shifting the pots from the greenhouse for 11 days. Image processing was done using pre-processing, segmentation and flowered by features' extraction. Different surrogate traits such as pixel area, plant aspect ratio, convex hull ratio and calliper length were estimated. A strong association was found between canopy temperature and above ground biomass under stress conditions. Promising lines in different surrogates will be utilized in breeding programmes to develop mapping populations for traits of interest related to drought resilience, in terms of improved tissue water status and mapping of genes/QTLs for drought traits.

Indexed as

DroughtsBiomassCrops, AgriculturalGenotypeImage Processing, Computer-AssistedPhenotypePlant ShootsQuantitative Trait LociWaterZea maysWater

Identifiers

PMID34314420
PMCPMC8315520
OpenAlexW3183853793

What OpenQuestion holds

Textmetadata
LicenceCC BY
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.