Evidence map›Paper›PMID 26111541›Full record

ArticlePlant physiology2015

Integrating Image-Based Phenomics and Association Analysis to Dissect the Genetic Architecture of Temporal Salinity Responses in Rice.

Malachy T Campbell, Avi C Knecht, Bettina Berger, Chris J Brien, Dong Wang, Harkamal Walia

Abstract read
PubMed Full text at PMC Publisher
In one paragraph

Article in Plant physiology, 2015. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 80 papers.

0numbers the graph read from it
0cells of the map it votes in
80citing 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

80 citing papers in PubMed.

  1. Review
  2. Harnessing artificial intelligence in plant breeding: innovations in digital phenotyping and breeding methodologies.TAG. Theoretical and applied genetics. Theoretische und angewandte Genetik · 2026
    Review
  3. Article
  4. Integration of crop modeling and sensing into molecular breeding for nutritional quality and stress tolerance.TAG. Theoretical and applied genetics. Theoretische und angewandte Genetik · 2025
    Review
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20 more citing papers are in PubMed but not listed here.

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

6 authors.

Malachy T CampbellDepartment of Agronomy and Horticulture (M.T.C., H.W.), Holland Computing Center (A.C.K.), and Department of Statistics (D.W.), University of Nebraska, Lincoln, Nebraska 68583;The Plant Accelerator, Australian Plant Phenomics Facility, University of Adelaide, Urrbrae, South Australia 5064, Australia (B.B.); andPhenomics and Bioinformatics Research Centre, University of South Australia, Adelaide, South Australia 5001, Australia (C.J.B.).ORCID http://orcid.org/0000-0002-8257-3595
Avi C KnechtDepartment of Agronomy and Horticulture (M.T.C., H.W.), Holland Computing Center (A.C.K.), and Department of Statistics (D.W.), University of Nebraska, Lincoln, Nebraska 68583;The Plant Accelerator, Australian Plant Phenomics Facility, University of Adelaide, Urrbrae, South Australia 5064, Australia (B.B.); andPhenomics and Bioinformatics Research Centre, University of South Australia, Adelaide, South Australia 5001, Australia (C.J.B.).
Bettina BergerDepartment of Agronomy and Horticulture (M.T.C., H.W.), Holland Computing Center (A.C.K.), and Department of Statistics (D.W.), University of Nebraska, Lincoln, Nebraska 68583;The Plant Accelerator, Australian Plant Phenomics Facility, University of Adelaide, Urrbrae, South Australia 5064, Australia (B.B.); andPhenomics and Bioinformatics Research Centre, University of South Australia, Adelaide, South Australia 5001, Australia (C.J.B.).ORCID http://orcid.org/0000-0003-1195-4478
Chris J BrienDepartment of Agronomy and Horticulture (M.T.C., H.W.), Holland Computing Center (A.C.K.), and Department of Statistics (D.W.), University of Nebraska, Lincoln, Nebraska 68583;The Plant Accelerator, Australian Plant Phenomics Facility, University of Adelaide, Urrbrae, South Australia 5064, Australia (B.B.); andPhenomics and Bioinformatics Research Centre, University of South Australia, Adelaide, South Australia 5001, Australia (C.J.B.).ORCID http://orcid.org/0000-0003-0581-1817
Dong WangDepartment of Agronomy and Horticulture (M.T.C., H.W.), Holland Computing Center (A.C.K.), and Department of Statistics (D.W.), University of Nebraska, Lincoln, Nebraska 68583;The Plant Accelerator, Australian Plant Phenomics Facility, University of Adelaide, Urrbrae, South Australia 5064, Australia (B.B.); andPhenomics and Bioinformatics Research Centre, University of South Australia, Adelaide, South Australia 5001, Australia (C.J.B.).
Harkamal WaliaDepartment of Agronomy and Horticulture (M.T.C., H.W.), Holland Computing Center (A.C.K.), and Department of Statistics (D.W.), University of Nebraska, Lincoln, Nebraska 68583;The Plant Accelerator, Australian Plant Phenomics Facility, University of Adelaide, Urrbrae, South Australia 5064, Australia (B.B.); andPhenomics and Bioinformatics Research Centre, University of South Australia, Adelaide, South Australia 5001, Australia (C.J.B.) hwalia2@unl.edu.ORCID http://orcid.org/0000-0002-9712-5824

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Salinity affects a significant portion of arable land and is particularly detrimental for irrigated agriculture, which provides one-third of the global food supply. Rice (Oryza sativa), the most important food crop, is salt sensitive. The genetic resources for salt tolerance in rice germplasm exist but are underutilized due to the difficulty in capturing the dynamic nature of physiological responses to salt stress. The genetic basis of these physiological responses is predicted to be polygenic. In an effort to address this challenge, we generated temporal imaging data from 378 diverse rice genotypes across 14 d of 90 mm NaCl stress and developed a statistical model to assess the genetic architecture of dynamic salinity-induced growth responses in rice germplasm. A genomic region on chromosome 3 was strongly associated with the early growth response and was captured using visible range imaging. Fluorescence imaging identified four genomic regions linked to salinity-induced fluorescence responses. A region on chromosome 1 regulates both the fluorescence shift indicative of the longer term ionic stress and the early growth rate decline during salinity stress. We present, to our knowledge, a new approach to capture the dynamic plant responses to its environment and elucidate the genetic basis of these responses using a longitudinal genome-wide association model.

Indexed as

Polymorphism, Single NucleotideChlorophyllChromosome MappingChromosomes, PlantFluorescenceGenome, PlantGenomicsGenotypeLuminescent MeasurementsOryzaPhenotypeReproducibility of ResultsSalt ToleranceSodium ChlorideStress, PhysiologicalChlorophyllSodium Chloride

Identifiers

PMID26111541
PMCPMC4528749

What OpenQuestion holds

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Registered trials

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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.